HomeMy Public PortalAboutMSD Disparity Study Final Report 1.9.22METROPOLITAN ST. LOUIS SEWER D ISTRICT DISPARITY S TUDY UPDATE
FINAL REPORT (JANUARY 2022)
PREPARED BY
Mason Tillman Associates, LTD
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Table of Contents
Table of Contents
CHAPTER 1: LEGAL REVIEW ................................................................................................. 1-1
I.INTRODUCTION ........................................................................................................ 1-1
II.STANDARD OF REVIEW ............................................................................................. 1-2
A.MINORITY BUSINESS ENTERPRISE PROGRAMS ................................................... 1-2
B.WOMEN BUSINESS ENTERPRISE PROGRAMS ....................................................... 1-3
C.LOCAL BUSINESS ENTERPRISE PROGRAMS ......................................................... 1-6
D.SMALL BUSINESS ENTERPRISE PROGRAMS ......................................................... 1-7
III.BURDEN OF PROOF ................................................................................................... 1-8
A.INITIAL BURDEN OF PROOF ............................................................................... 1-8
B.ULTIMATE BURDEN OF PROOF ........................................................................... 1-9
IV.CROSON EVIDENTIARY FRAMEWORK .................................................................... 1-11
A.ACTIVE AND PASSIVE PARTICIPATION.............................................................. 1-11
B.SYSTEMIC DISCRIMINATORY EXCLUSION ......................................................... 1-13
C.ANECDOTAL EVIDENCE ................................................................................... 1-21
D.REMEDIAL STATUTORY SCHEME ..................................................................... 1-26
V.CONSIDERATION OF RACE-NEUTRAL OPTIONS ...................................................... 1-29
VI.CONCLUSION .......................................................................................................... 1-30
VII.LIST OF AUTHORITIES ............................................................................................ 1-31
CHAPTER 2: PRIME CONTRACTOR UTILIZATION ANALYSIS .................................................... 2-1
I.INTRODUCTION ........................................................................................................ 2-1
II.PRIME CONTRACT DATA SOURCES .......................................................................... 2-2
III.THRESHOLDS FOR ANALYSIS.................................................................................... 2-3
A.INFORMAL THRESHOLD ..................................................................................... 2-3
B.FORMAL CONTRACT THRESHOLD ...................................................................... 2-4
IV.PRIME CONTRACTOR UTILIZATION ......................................................................... 2-4
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A. ALL PRIME CONTRACTORS ................................................................................ 2-4
B. DISTRIBUTION OF PRIME CONTRACT DOLLARS .................................................. 2-5
C. HIGHLY USED BUILDING CONSTRUCTION PRIME CONTRACTORS ........................ 2-5
D. HIGHLY USED NON-BUILDING CONSTRUCTION PRIME CONTRACTORS ............... 2-6
E. HIGHLY USED ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTORS .... 2-7
F. HIGHLY USED PURCHASES AND OTHER SERVICES PRIME CONTRACTORS ........... 2-8
G. ALL PRIME CONTRACTS BY INDUSTRY............................................................. 2-10
H. INFORMAL PRIME CONTRACTS BY INDUSTRY ................................................... 2-18
I. FORMAL PRIME CONTRACTS BY INDUSTRY ...................................................... 2-24
V. SUMMARY .............................................................................................................. 2-32
CHAPTER 3: SUBCONTRACTOR UTILIZATION ANALYSIS ......................................................... 3-1
I. INTRODUCTION ........................................................................................................ 3-1
II. DATA SOURCES ........................................................................................................ 3-1
A. DATA COLLECTION PROCESS............................................................................. 3-2
B. SUBCONTRACT DATA ANALYSIS ....................................................................... 3-2
III. SUBCONTRACTOR UTILIZATION ............................................................................... 3-3
A. ALL SUBCONTRACTS ......................................................................................... 3-3
B. SUBCONTRACTS BY INDUSTRY........................................................................... 3-4
IV. SUMMARY .............................................................................................................. 3-10
CHAPTER 4: MARKET AREA ANALYSIS .................................................................................. 4-1
I. INTRODUCTION ........................................................................................................ 4-1
A. LEGAL CRITERIA FOR GEOGRAPHIC MARKET AREA ........................................... 4-1
B. APPLICATION OF THE CROSON STANDARD ......................................................... 4-1
II. MARKET AREA ANALYSIS ........................................................................................ 4-4
A. SUMMARY OF THE DISTRIBUTION OF ALL PRIME CONTRACTS AWARDED .............. 4-4
B. DISTRIBUTION OF BUILDING CONSTRUCTION PRIME CONTRACTS .......................... 4-5
III. DISTRIBUTION OF NON-BUILDING CONSTRUCTION PRIME CONTRACTS .................. 4-5
A. DISTRIBUTION OF ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS ... 4-6
B. DISTRIBUTION OF PURCHASES AND OTHER SERVICES PRIME CONTRACTS ........... 4-6
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IV. SUMMARY ................................................................................................................ 4-7
CHAPTER 5: PRIME CONTRACTOR AND SUBCONTRACTOR AVAILABILITY ANALYSIS ................ 5-1
I. INTRODUCTION ........................................................................................................ 5-1
II. PRIME CONTRACTOR AVAILABILITY DATA SOURCES ............................................. 5-1
A. IDENTIFICATION OF WILLING BUSINESSES WITHIN THE MARKET AREA .............. 5-1
B. PRIME CONTRACTOR SOURCES .......................................................................... 5-2
C. DETERMINATION OF WILLINGNESS .................................................................... 5-4
D. DISTRIBUTION OF AVAILABLE PRIME CONTRACTORS BY SOURCE, ETHNICITY,
AND GENDER .................................................................................................... 5-4
III. CAPACITY ................................................................................................................ 5-6
A. PRIME CONTRACT SIZE DISTRIBUTION ............................................................... 5-7
B. LARGEST MWBE PRIME CONTRACTS AWARDED BY INDUSTRY ......................... 5-9
C. FORMAL CONTRACT THRESHOLD ANALYSIS ...................................................... 5-9
D. CONCLUSION .................................................................................................. 5-16
IV. PRIME CONTRACTOR AVAILABILITY ANALYSIS .................................................... 5-17
A. BUILDING CONSTRUCTION PRIME CONTRACTOR AVAILABILITY ....................... 5-17
B. NON-BUILDING CONSTRUCTION PRIME CONTRACTOR AVAILABILITY .............. 5-19
C. ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTOR AVAILABILITY ... 5-21
D. PURCHASES AND OTHER SERVICES PRIME CONTRACTOR AVAILABILITY........... 5-23
V. SUBCONTRACTOR AVAILABILITY ANALYSIS .......................................................... 5-25
A. SOURCE OF WILLING AND ABLE SUBCONTRACTORS ......................................... 5-25
B. BUILDING CONSTRUCTION SUBCONTRACTOR AVAILABILITY ............................ 5-25
C. NON-BUILDING CONSTRUCTION SUBCONTRACTOR AVAILABILITY ................... 5-27
D. ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTOR AVAILABILITY ....... 5-29
VI. SUMMARY .............................................................................................................. 5-31
CHAPTER 6: PRIME CONTRACT DISPARITY ANALYSIS ............................................................ 6-1
I. INTRODUCTION ........................................................................................................ 6-1
II. DISPARITY ANALYSIS ............................................................................................... 6-2
A. DISPARITY ANALYSIS: INFORMAL PRIME CONTRACTS BY INDUSTRY .................. 6-4
B. DISPARITY ANALYSIS: FORMAL PRIME CONTRACTS, BY INDUSTRY .................. 6-13
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III. DISPARITY ANALYSIS SUMMARY ........................................................................... 6-25
A. BUILDING CONSTRUCTION PRIME CONTRACTS ................................................ 6-25
B. NON-BUILDING CONSTRUCTION PRIME CONTRACTS ........................................ 6-26
C. ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS ............................ 6-27
D. PURCHASES AND OTHER SERVICES PRIME CONTRACTS .................................... 6-28
CHAPTER 7: SUBCONTRACT DISPARITY ANALYSIS ................................................................. 7-1
I. INTRODUCTION ........................................................................................................ 7-1
II. DISPARITY ANALYSIS ............................................................................................... 7-1
III. DISPARITY ANALYSIS: ALL SUBCONTRACTS BY INDUSTRY ...................................... 7-3
A. BUILDING CONSTRUCTION SUBCONTRACTS ....................................................... 7-3
B. NONBUILDING CONSTRUCTION SUBCONTRACTS ................................................ 7-6
C. ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTS ................................... 7-9
IV. SUBCONTRACT DISPARITY SUMMARY .................................................................... 7-12
CHAPTER 8: REGRESSION ANALYSIS ..................................................................................... 8-1
I. INTRODUCTION ........................................................................................................ 8-1
II. LEGAL ANALYSIS ..................................................................................................... 8-2
A. PASSIVE DISCRIMINATION ................................................................................. 8-2
B. NARROW TAILORING ........................................................................................ 8-2
C. CONCLUSION .................................................................................................... 8-4
III. REGRESSION ANALYSIS METHODOLOGY ................................................................. 8-4
IV. DATASETS ANALYZED .............................................................................................. 8-5
V. REGRESSION MODELS DEFINED ............................................................................... 8-5
A. BUSINESS OWNERSHIP ANALYSIS ...................................................................... 8-5
B. EARNINGS DISPARITY ANALYSIS ....................................................................... 8-6
C. BUSINESS LOAN APPROVAL ANALYSIS .............................................................. 8-7
VI. FINDINGS .................................................................................................................. 8-9
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A. BUSINESS OWNERSHIP ANALYSIS ...................................................................... 8-9
B. BUSINESS EARNINGS ANALYSIS ...................................................................... 8-15
C. BUSINESS LOAN APPROVAL ANALYSIS ............................................................ 8-20
VII. CONCLUSION .......................................................................................................... 8-26
A. BUSINESS OWNERSHIP ANALYSIS .................................................................... 8-26
B. BUSINESS EARNINGS ANALYSIS ...................................................................... 8-27
C. BUSINESS LOAN APPROVAL ANALYSIS ............................................................ 8-28
D. REGRESSION FINDINGS .................................................................................... 8-29
CHAPTER 9: ANECDOTAL ANALYSIS ...................................................................................... 9-1
I. INTRODUCTION ........................................................................................................ 9-1
A. ANECDOTAL EVIDENCE OF DISCRIMINATION - ACTIVE AND PASSIVE
PARTICIPATION ................................................................................................. 9-1
B. ANECDOTAL METHODOLOGY ............................................................................ 9-2
II. ANECDOTAL FINDINGS ............................................................................................. 9-4
A. RACIAL BARRIERS AND SEXISM ......................................................................... 9-4
B. DIFFICULTY BREAKING INTO THE CONTRACTING NETWORK ............................... 9-7
C. GOOD OLD BOY NETWORK ............................................................................... 9-9
D. DIFFICULTY NAVIGATING THE BID PROCESS .................................................... 9-11
E. EXCESSIVE CERTIFICATION PROCEDURES ....................................................... 9-12
F. BARRIERS TO FINANCING ................................................................................ 9-13
G. LATE PAYMENTS............................................................................................. 9-15
H. SUPPLIER DIVERSITY PROGRAM ...................................................................... 9-16
I. EXEMPLARY PRACTICES OF MSD .................................................................... 9-19
III. SUMMARY .............................................................................................................. 9-24
CHAPTER 10: RECOMMENDATIONS ..................................................................................... 10-1
I. INTRODUCTION ...................................................................................................... 10-1
II. DISPARITY ANALYSIS FINDINGS ............................................................................. 10-2
A. PRIME CONTRACT DISPARITY FINDINGS .......................................................... 10-2
B. SUBCONTRACTOR DISPARITY FINDINGS ........................................................... 10-7
III. RACE AND GENDER-CONSCIOUS REMEDIES .......................................................... 10-8
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A. PRIME CONTRACT REMEDIES .......................................................................... 10-8
B. IMPLEMENT SUBCONTRACT REMEDIES ............................................................ 10-8
IV. RACE AND GENDER-NEUTRAL REMEDIES .............................................................. 10-9
A. CAPACITY BUILDING MEASURES ..................................................................... 10-9
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List of Tables
List of Tables
TABLE 2.1: BUSINESS ETHNIC AND GENDER GROUPS ................................................................ 2-2
TABLE 2.2: INFORMAL CONTRACT THRESHOLDS BY INDUSTRY ................................................. 2-3
TABLE 2.3: FORMAL CONTRACT THRESHOLD BY INDUSTRY ...................................................... 2-4
TABLE 2.4: TOTAL PRIME CONTRACTS AND DOLLARS EXPENDED ALL INDUSTRIES,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ............................................................. 2-5
TABLE 2.5: BUILDING CONSTRUCTION PRIME CONTRACTS ........................................................ 2-5
TABLE 2.6: MOST HIGHLY USED BUILDING CONSTRUCTION PRIME CONTRACTOR ..................... 2-6
TABLE 2.7: NON-BUILDING CONSTRUCTION PRIME CONTRACTS ............................................... 2-6
TABLE 2.8: NON-BUILDING CONSTRUCTION PRIME CONTRACTS DISTRIBUTED BY NUMBER OF
BUSINESSES .......................................................................................................... 2-6
TABLE 2.9: TOP TWO MOST HIGHLY USED NON-BUILDING CONSTRUCTION PRIME
CONTRACTORS ...................................................................................................... 2-7
TABLE 2.10: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS .................................. 2-7
TABLE 2.11: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS DISTRIBUTED BY
NUMBER OF BUSINESSES ....................................................................................... 2-7
TABLE 2.12: TOP THREE MOST HIGHLY USED ENGINEERING PROFESSIONAL SERVICES PRIME
CONTRACTORS ...................................................................................................... 2-8
TABLE 2.13: PURCHASES AND OTHER SERVICES PRIME CONTRACTS ......................................... 2-8
TABLE 2.14: PURCHASES AND OTHER SERVICES PRIME CONTRACTS DISTRIBUTED BY
NUMBER OF BUSINESSES ....................................................................................... 2-8
TABLE 2.15: TOP FOUR HIGHLY USED PURCHASES AND OTHER SERVICES PRIME
CONTRACTORS ...................................................................................................... 2-9
TABLE 2.16: BUILDING CONSTRUCTION PRIME CONTRACT UTILIZATION ALL CONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ........................................................... 2-11
TABLE 2.17: NON-BUILDING CONSTRUCTION PRIME CONTRACT UTILIZATION ALL
CONTRACTS, JANUARY 1, 2013 TO DECEMBER 31, 2017 ....................................... 2-13
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TABLE 2.18: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACT UTILIZATION ALL
CONTRACTS, JANUARY 1, 2013 TO DECEMBER 31, 2017 ....................................... 2-15
TABLE 2.19: PURCHASES AND OTHER SERVICES PRIME CONTRACT UTILIZATION ALL
CONTRACTS, JANUARY 1, 2013 TO DECEMBER 31, 2017 ....................................... 2-17
TABLE 2.20: NON-BUILDING CONSTRUCTION PRIME CONTRACT UTILIZATION CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 .................... 2-19
TABLE 2.21: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACT UTILIZATION
CONTRACTS VALUED UNDER $25,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 . 2-21
TABLE 2.22: PURCHASES AND OTHER SERVICES PRIME CONTRACT UTILIZATION CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 .................... 2-23
TABLE 2.23: BUILDING CONSTRUCTION PRIME CONTRACT UTILIZATION CONTRACTS VALUED
FROM $25,000 TO $8,270,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 ............ 2-25
TABLE 2.24: NON-BUILDING CONSTRUCTION PRIME CONTRACT UTILIZATION CONTRACTS
VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 .. 2-27
TABLE 2.25: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACT UTILIZATION
CONTRACTS VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013 TO
DECEMBER 31, 2017............................................................................................ 2-29
TABLE 2.26: PURCHASES AND OTHER SERVICES PRIME CONTRACT UTILIZATION CONTRACTS
VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013 TO DECEMBER 31, 2017 .. 2-31
TABLE 3.1: SUBCONTRACTS AWARDED AND DOLLARS EXPENDED BY INDUSTRY, JANUARY 1,
2013, TO DECEMBER 31, 2017 ............................................................................... 3-3
TABLE 3.2: BUILDING CONSTRUCTION SUBCONTRACTOR UTILIZATION, JANUARY 1, 2013, TO
DECEMBER 31, 2017.............................................................................................. 3-5
TABLE 3.3: NON-BUILDING CONSTRUCTION SUBCONTRACTOR UTILIZATION, JANUARY 1,
2013, TO DECEMBER 31, 2017 ............................................................................... 3-7
TABLE 3.4: ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTOR UTILIZATION,
JANUARY 1, 2013, TO DECEMBER 31, 2017 ............................................................ 3-9
TABLE 4.1: DISTRIBUTION OF ALL CONTRACTS AWARDED ........................................................ 4-4
TABLE 4.2: DISTRIBUTION OF BUILDING CONSTRUCTION PRIME CONTRACTS............................. 4-5
TABLE 4.3: DISTRIBUTION OF NON-BUILDING CONSTRUCTION PRIME CONTRACTS..................... 4-5
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TABLE 4.4: DISTRIBUTION OF ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS ........ 4-6
TABLE 4.5: DISTRIBUTION OF PURCHASES AND OTHER SERVICES PRIME CONTRACTS ................ 4-6
TABLE 4.6: DISTRIBUTION OF MSD CONTRACTS ....................................................................... 4-8
TABLE 5.1: PRIME CONTRACTOR AVAILABILITY DATA SOURCES .............................................. 5-2
TABLE 5.2: DISTRIBUTION OF PRIME CONTRACTOR AVAILABILITY DATA SOURCES, BUILDING
CONSTRUCTION ..................................................................................................... 5-5
TABLE 5.3: DISTRIBUTION OF PRIME CONTRACTOR AVAILABILITY DATA SOURCES,
NON-BUILDING CONSTRUCTION ............................................................................ 5-5
TABLE 5.4: DISTRIBUTION OF PRIME CONTRACTOR AVAILABILITY DATA SOURCES,
ENGINEERING PROFESSIONAL SERVICES ................................................................ 5-6
TABLE 5.5: DISTRIBUTION OF PRIME CONTRACTOR AVAILABILITY DATA SOURCES,
PURCHASES AND OTHER SERVICES ........................................................................ 5-6
TABLE 5.6: ALL INDUSTRY CONTRACTS BY SIZE JANUARY 1, 2013, TO DECEMBER 31, 2017 ...... 5-8
TABLE 5.7: LARGEST PRIME CONTRACTS AWARDED BY MSD TO MWBES ............................... 5-9
TABLE 5.8: ETHNICITY AND GENDER OF BUSINESS OWNERS ................................................... 5-10
TABLE 5.9: PRIMARY INDUSTRY OF BUSINESS ......................................................................... 5-10
TABLE 5.10: ANNUAL GROSS REVENUE .................................................................................. 5-11
TABLE 5.11: NUMBER OF EMPLOYEES .................................................................................... 5-12
TABLE 5.12: NUMBER OF ANNUAL CONTRACTS ...................................................................... 5-13
TABLE 5.13: YEARS IN BUSINESS ............................................................................................ 5-14
TABLE 5.14: EDUCATION LEVEL OF BUSINESS OWNERS .......................................................... 5-15
TABLE 5.15: AVAILABLE BUILDING CONSTRUCTION PRIME CONTRACTORS JANUARY 1, 2013,
TO DECEMBER 31, 2017 ..................................................................................... 5-18
TABLE 5.16: AVAILABLE NON-BUILDING CONSTRUCTION PRIME CONTRACTORS
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 5-20
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TABLE 5.17: AVAILABLE ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTORS
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 5-22
TABLE 5.18: AVAILABLE PURCHASES AND OTHER SERVICES PRIME CONTRACTORS
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 5-24
TABLE 5.19: AVAILABLE BUILDING CONSTRUCTION SUBCONTRACTORS JANUARY 1, 2013,
TO DECEMBER 31, 2017 ..................................................................................... 5-26
TABLE 5.20: AVAILABLE NON-BUILDING CONSTRUCTION SUBCONTRACTORS JANUARY 1,
2013, TO DECEMBER 31, 2017 ............................................................................ 5-28
TABLE 5.21: AVAILABLE ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTORS
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 5-30
TABLE 6.1: INFORMAL THRESHOLDS FOR ANALYSIS BY INDUSTRY ............................................ 6-2
TABLE 6.2: FORMAL CONTRACT THRESHOLDS FOR ANALYSIS BY INDUSTRY ............................. 6-3
TABLE 6.3: STATISTICAL OUTCOME DESCRIPTIONS ................................................................... 6-3
TABLE 6.4: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-5
TABLE 6.5: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-8
TABLE 6.6: DISPARITY ANALYSIS: PURCHASES AND OTHER SERVICES PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ................... 6-11
TABLE 6.7: DISPARITY ANALYSIS: BUILDING CONSTRUCTION PRIME CONTRACTS VALUED
$25,000 TO $8,270,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-14
TABLE 6.8: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION PRIME CONTRACTS
VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 . 6-17
TABLE 6.9: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES PRIME
CONTRACTS VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013, TO
DECEMBER 31, 2017............................................................................................ 6-20
TABLE 6.10: DISPARITY ANALYSIS: PURCHASES AND OTHER SERVICES PRIME CONTRACTS
VALUED $25,000 TO $500,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ......... 6-23
TABLE 6.11: DISPARITY SUMMARY: BUILDING CONSTRUCTION PRIME CONTRACT DOLLARS,
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 6-25
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TABLE 6.12: DISPARITY SUMMARY: NON-BUILDING CONSTRUCTION PRIME CONTRACT
DOLLARS, JANUARY 1, 2013, TO DECEMBER 31, 2017 ........................................ 6-26
TABLE 6.13: DISPARITY SUMMARY: ENGINEERING PROFESSIONAL SERVICES PRIME
CONTRACT DOLLARS, ........................................................................................ 6-27
TABLE 6.14: DISPARITY SUMMARY: PURCHASES AND OTHER SERVICES PRIME CONTRACT
DOLLARS, JANUARY 1, 2013, TO DECEMBER 31, 2017......................................... 6-28
TABLE 7.1: STATISTICAL OUTCOME DESCRIPTIONS ................................................................... 7-2
TABLE 7.2: DISPARITY ANALYSIS: BUILDING CONSTRUCTION SUBCONTRACTS, JANUARY 1,
2013 TO DECEMBER 31, 2017 ................................................................................ 7-4
TABLE 7.3: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION SUBCONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ............................................................. 7-7
TABLE 7.4: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ........................................................... 7-10
TABLE 7.5: SUBCONTRACT DISPARITY SUMMARY, JANUARY 1, 2013 TO DECEMBER 31, 2017 .. 7-12
TABLE 8.1: INDEPENDENT VARIABLES USED IN THE BUSINESS OWNERSHIP ANALYSIS ............... 8-6
TABLE 8.2: INDEPENDENT VARIABLES USED FOR EARNINGS DISPARITY ANALYSIS .................... 8-7
TABLE 8.3: INDEPENDENT VARIABLES USED FOR BUSINESS LOAN APPROVAL ANALYSIS ........... 8-9
TABLE 8.4: CONSTRUCTION INDUSTRY LOGISTIC MODEL ........................................................ 8-10
TABLE 8.5: PROFESSIONAL SERVICES LOGISTIC MODEL .......................................................... 8-12
TABLE 8.6: SUPPLIES AND CONTRACTUAL SERVICES LOGISTIC MODEL ................................... 8-14
TABLE 8.7: CONSTRUCTION INDUSTRY OLS REGRESSION ....................................................... 8-16
TABLE 8.8: PROFESSIONAL SERVICES OLS REGRESSION ......................................................... 8-17
TABLE 8.9: SUPPLIES AND CONTRACTUAL SERVICES OLS REGRESSION ................................... 8-19
TABLE 8.10: ORDERED LOGISTIC MODEL FOR THE BUSINESS LOAN APPROVAL ANALYSIS IN
THE CONSTRUCTION INDUSTRY .......................................................................... 8-21
TABLE 8.11: ORDERED LOGISTIC MODEL FOR THE BUSINESS LOAN APPROVAL ANALYSIS IN
THE PROFESSIONAL SERVICES INDUSTRY ............................................................ 8-23
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TABLE 8.12: ORDERED LOGISTIC MODEL FOR THE BUSINESS LOAN APPROVAL ANALYSIS
IN THE SUPPLIES AND CONTRACTUAL SERVICES INDUSTRY ................................. 8-25
TABLE 8.13: STATISTICALLY SIGNIFICANT BUSINESS OWNERSHIP DISPARITIES ....................... 8-27
TABLE 8.14: STATISTICALLY SIGNIFICANT BUSINESS EARNINGS DISPARITIES .......................... 8-28
TABLE 8.15: STATISTICALLY SIGNIFICANT BUSINESS LOAN APPROVAL DISPARITIES ............... 8-28
TABLE 9.1: METROPOLITAN ST. LOUIS SEWER DISTRICT COMMUNITY MEETINGS ...................... 9-3
TABLE 9.2: BARRIERS REPORTED IN MSD 2012 DISPARITY STUDY ......................................... 9-24
TABLE 9.3: BARRIERS REPORTED IN MSD 2021 DISPARITY STUDY ......................................... 9-24
TABLE 10.1: TOTAL PRIME CONTRACTS AND DOLLARS EXPENDED ALL INDUSTRIES,
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 10-2
TABLE 10.2: DISPARITY SUMMARY: BUILDING CONSTRUCTION PRIME CONTRACT DOLLARS,
JANUARY 1, 2013, TO DECEMBER 31, 2017 ......................................................... 10-3
TABLE 10.3: DISPARITY SUMMARY: NON-BUILDING CONSTRUCTION PRIME CONTRACT
DOLLARS, JANUARY 1, 2013, TO DECEMBER 31, 2017......................................... 10-4
TABLE 10.4: DISPARITY SUMMARY: ENGINEERING PROFESSIONAL SERVICES PRIME
CONTRACT DOLLARS, JANUARY 1, 2013, TO DECEMBER 31, 2017 ....................... 10-5
TABLE 10.5: DISPARITY SUMMARY: PURCHASES AND OTHER SERVICES PRIME CONTRACT
DOLLARS, JANUARY 1, 2013, TO DECEMBER 31, 2017......................................... 10-6
TABLE 10.6: SUBCONTRACT DISPARITY SUMMARY, JANUARY 1, 2013, TO
DECEMBER 31, 2017............................................................................................ 10-7
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List of Charts
List of Charts
CHART 5.1: ALL INDUSTRY CONTRACTS BY SIZE JANUARY 1, 2013, TO DECEMBER 31, 2017 ..... 5-8
CHART 5.2: ANNUAL GROSS REVENUE ................................................................................... 5-11
CHART 5.3: NUMBER OF EMPLOYEES ...................................................................................... 5-13
CHART 5.4: NUMBER OF ANNUAL CONTRACTS ....................................................................... 5-14
CHART 5.5: YEARS IN BUSINESS ............................................................................................. 5-15
CHART 5.6: EDUCATIONAL ATTAINMENT ................................................................................ 5-16
CHART 6.1: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-6
CHART 6.2: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-9
CHART 6.3: DISPARITY ANALYSIS: PURCHASES AND OTHER SERVICES PRIME CONTRACTS
VALUED UNDER $25,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ................... 6-12
CHART 6.4: DISPARITY ANALYSIS: BUILDING CONSTRUCTION PRIME CONTRACTS VALUED
$25,000 TO $8,270,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 ..................... 6-15
CHART 6.5: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION PRIME CONTRACTS
VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013, TO
DECEMBER 31, 2017............................................................................................ 6-18
CHART 6.6: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES PRIME CONTRACTS
VALUED FROM $25,000 TO $500,000, JANUARY 1, 2013, TO
DECEMBER 31, 2017............................................................................................ 6-21
CHART 6.7: DISPARITY ANALYSIS: PURCHASES AND OTHER SERVICES PRIME CONTRACTS
VALUED $25,000 TO $500,000, JANUARY 1, 2013, TO DECEMBER 31, 2017 .......... 6-24
CHART 7.1: DISPARITY ANALYSIS: BUILDING CONSTRUCTION SUBCONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ............................................................. 7-5
CHART 7.2: DISPARITY ANALYSIS: NON-BUILDING CONSTRUCTION SUBCONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ............................................................. 7-8
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CHART 7.3: DISPARITY ANALYSIS: ENGINEERING PROFESSIONAL SERVICES SUBCONTRACTS,
JANUARY 1, 2013 TO DECEMBER 31, 2017 ........................................................... 7-11
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CHAPTER 1: Legal Review
I. Introduction
This Metropolitan St. Louis Sewer District (MSD) Minority and Woman Business Enterprise
(MWBE) Update Disparity Study is MSD’s second-generation disparity study. The first disparity
study, which measured the utilization of available MWBEs on MSD’s building construction, non-
building construction, engineering professional services, non-engineering professional services,
and goods and contractual services, was completed in 2012. The study documented a disparity in
the award of prime contracts and subcontracts to available MWBEs. To address the documented
disparity, the MSD Board of Trustees adopted an MWBE program with race and gender-based
remedies and authorized an update disparity study. This Update Disparity Study was
commissioned in 2019 to determine whether there is still evidence of disparity in the utilization of
available MWBEs on MSD’s building construction, non-building construction, state funded
construction, engineering professional services, and purchases and other services contracts.
Two United States Supreme Court decisions, City of Richmond v. J.A. Croson Co. (Croson)1 and
Adarand v. Pena (Adarand),2 review local governments’ affirmative action public contracting
programs involving both local and federal funds. The legal standards affirmed in these two cases
were applied in the performance of both of MSD’s disparity studies.
Croson applied the most stringent evidentiary standard of review for race-based programs in its
examination of the City of Richmond’s locally funded Minority Business Enterprise (MBE)
Program. Justice O’Connor, delivering the opinion for the Supreme Court, adjudicated that
programs employing racial classification would be subject to the “strict scrutiny” standard. Strict
scrutiny is the highest standard of review that must be applied to determine the constitutionality of
affirmative action laws. The standard requires government entities to prove a “compelling interest”
in remedying identified discrimination based upon “strong evidence,” and that the measures
adopted to remedy the discrimination are “narrowly tailored” to evidence documented.3
Adarand extended the application of the strict scrutiny standard to federal affirmative action
contracting programs. This chapter presents the law applicable to local public contracting
programs as set forth in Croson and its progeny.4 There were no relevant legal decisions
subsequent to the completion of MSD’s 2012 Disparity Study that modified the methodology of
1 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
2 Adarand Constructors, Inc. v. Peña, 515 U.S. 200 (1995).
3 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
4 In Houston Contractors Association v. Metropolitan Transit Authority of Harris County, 993 F. Supp 545, the District Court for the Southern
District of Texas found the Metro DBE unconstitutional and entered an injunction prohibiting the collection of race, sex religion, or national
origin data from its contractors, subcontractors and suppliers until a project was completed and prohibiting the use of race, race and ethnicity
in the contracting process.
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the statistical analysis for compiling the requisite factual predicate for a constitutionally sound
public contracting program.
II. Standard of Review
The standard of review refers to the level of scrutiny a court applies during its analysis of whether
or not a particular law is constitutional. This section discusses the relevant standard of review
applied to remedial programs based on race or gender, including the heightened standard of review
that the United States Supreme Court set forth in Croson for race-conscious and gender-conscious
programs.
A. Minority Business Enterprise Programs
MBE programs are designed to ensure that minority-owned businesses are afforded equal access
to public contracting opportunities. MBE programs can contain both race-conscious and race-
neutral policies and procedures to achieve the objectives of the program. In Croson, the United
States Supreme Court affirmed that, pursuant to the Fourteenth Amendment, the proper standard
of review for state and local race-based MBE programs is strict scrutiny.5 Under a strict scrutiny
analysis, the government must show that the race-conscious measures in a challenged program are
narrowly tailored to achieve a compelling state interest.6 In practice, strict scrutiny requires that a
government entity prove both a “compelling interest” in remedying identified discrimination based
upon “strong evidence,” and that the measures adopted to remedy the discrimination are “narrowly
tailored” to that evidence. The Court recognized that a state or local entity may act, in the form of
an MBE program, to rectify the effects of identified, systemic racial discrimination within its
jurisdiction.7
In Croson, the plaintiff was a construction firm and sole bidder that was denied a contract because
it failed to meet the 30 percent MBE goal under the City of Richmond’s MBE Plan. The plaintiff
argued that the MBE Plan was unconstitutional under the Fourteenth Amendment’s Equal
Protection Clause. The City’s MBE plan imposed a 30 percent MBE subcontracting goal on prime
contractors that were awarded City construction contracts but imposed no geographic limitation
on the available pool of MBEs and did not provide for the possibility of waiver in the application
of the MBE goals. The Court affirmed that the City of Richmond’s MBE Plan violated both prongs
of strict scrutiny—there was not a compelling governmental interest and the 30 percent set-aside
was not narrowly tailored.
The City failed to demonstrate a compelling governmental interest because the evidence did not
establish prior discrimination by the City in awarding contracts. The City presented generalized
data of past discrimination within the construction industry as a whole and included nonracial
factors that would affect any group seeking to establish a new business enterprise, such as
deficiencies in working capital and inability to meet bonding requirements. The Court held that
5 Croson, 488 U.S. at 493-95.
6 Id.
7 Id. at 509.
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evidence of general application is not sufficiently particularized, was not germane to the City’s
local contracting market, and is insufficient to implement race-based relief under the Fourteenth
Amendment’s Equal Protection Clause. Additionally, the Court rejected the statistical
methodology used to determine disparity. The City of Richmond relied upon a statistical disparity
analysis to identify the discrimination that the MBE Plan was seeking to remedy. The City’s
disparity analysis was calculated based on the number of prime contracts awar ded to MBEs
compared to the City’s MBE population. According to the Court, the proper calculation should
have been based on the percentage of MBEs in the relevant market area that are qualified, willing,
and able to work on the City’s contracts compared to the percentage of total City construction
dollars that were awarded to MBEs.
The City failed to demonstrate that the MBE Plan was narrowly tailored to remedy the effects of
prior discrimination because it entitled MBEs located anywhere in the country to an absolute
preference based solely on race and failed to establish discrimination within the City’s local
contracting market. Furthermore, the 30 percent goal was not based on the availability of MBEs
in the City’s local contracting market. The Court determined that the 30 percent goal was
predicated upon an unrealistic assumption that MBEs will choose to work on the City’s contracts.
Additionally, the Court determined that the City did not seriously consider race-neutral alternatives
as a remedy to address the identified discrimination.
Justice O’Connor, speaking for the majority, articulated various methods of demonstrating
discrimination and set forth guidelines for crafting MBE programs that are “narrowly tailored” to
address systemic racial discrimination.8 To demonstrate discrimination and survive strict scrutiny,
the government must show that it had become a “passive participant” in a system of racial
exclusion practiced by the local industry.9 Methods available to demonstrate patterns of
discrimination that appropriately satisfy the strict scrutiny analysis include evidence of the
government entity’s active and passive participation in the discrimination to be remedied by the
proposed race and gender-conscious goals, systemic discriminatory exclusion, and supporting
anecdotal evidence. These methods to construct a strong evidentiary framework are discussed in
greater detail below, in Section IV: Croson Evidentiary Framework.
B. Women Business Enterprise Programs
WBE programs are designed to ensure that women-owned businesses are afforded equal access to
public contracting opportunities. WBE programs may contain both gender -conscious and gender-
neutral policies and procedures to achieve the objectives of the program. Since Croson, which
dealt exclusively with the review of race-conscious plans, the United States Supreme Court has
remained silent with respect to the appropriate standard of review for geographically based Women
Business Enterprise (WBE) programs and Local Business Enterprise (LBE) program s. In other
contexts, however, the United States Supreme Court has ruled that gender classifications are not
8 Croson, 488 U.S. at 501-2. Cases involving education and employment frequently refer to the principal concepts applicable to the use of race
in government contracting: compelling interest and narrowly tailored remedies. The Supreme Court in Croson and subsequent cases provided
a fairly detailed guidance on how those concepts are to be treated in contracting. In education and employment, the concepts are not explicated
to nearly the same extent. Therefore, references in those cases to “compelling governm ental interest” and “narrow tailoring” for purposes of
contracting are essentially generic and of little value in determining the appropriate methodology for disparity studies.
9 Croson, 488 U.S. at 492-93.
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subject to the rigorous strict scrutiny standard applied to racial classifications. Instead, gender
classifications have been subject only to an “intermediate” standard of review, regardless of the
favored gender.
The Sixth Circuit applies both the strict scrutiny standard and the intermediate standard of review
to WBE programs depending on the application of the program’s policies. In Brunet v. City of
Columbus, the Sixth Circuit held that the strict scrutiny standard of review is applied to an
affirmative action plan based on gender classification when challenged under the Equal Protection
Clause.10 The Court made a distinction between “gender-conscious” plans and “gender-
preference” plans. Pursuant to Sixth Circuit precedent, gender -conscious plans are subject to the
intermediate standard of review, while gender-preference plans are subject to the strict scrutiny
standard of review.11 The Court classifies a program as “gender conscious” if its policies utilize
gender as a factor but are gender neutral in their application and have no disparate impact on
individuals based on gender when the policies are applied equally to both men and women.12 The
Court classifies a program as “gender preference” if its policies contain gender -based criteria that
are applied directly as a preference.13
Notwithstanding the fact that the United States Supreme Court has not ruled on a WBE program,
the consensus among the federal circuit courts of appeals is that WBE programs are subject to
intermediate scrutiny, rather than the more exacting strict scrutiny standard to which race -
conscious programs are subject.14 Intermediate scrutiny requires the governmental entity to
demonstrate that the action taken furthers an “important governmental objective,” employing a
method that bears a fair and substantial relation to the goal.15 The courts have also described the
test as requiring an “exceedingly persuasive justification” f or classifications based on gender.16
The United States Supreme Court acknowledged that in “limited circumstances a gender -based
classification favoring one sex can be justified if it intentionally and directly assists the members
of that sex who are disproportionately burdened.”17
Consistent with the United States Supreme Court’s finding with regard to gender classification,
the Third Circuit in Contractors Association of Eastern Pennsylvania v. City of Philadelphia
(“Philadelphia IV”) ruled in 1993 that the standard of review governing WBE programs is different
10 Brunet v. City of Columbus, 1 F.3d 390, 404 (6th Cir. 1993).
11 Id.
12 Brunet v. City of Columbus, 1 F.3d 390, 404 (6th Cir. 1993) (citing Jacobsen v. Cincinnati Board of Education, 961 F.2d 100, 102 (6th Cir.
1992).
13 Id.
14 See Coral Constr. Co. v. King Cnty., 941 F.2d 910, 930-31 (9th Cir. 1991); Eng’g Constr. Ass’n v. Metro. Dade Cnty. (“Dade County II”), 122
F.3d 895, 907-08 (11th Cir. 1997); see also Concrete Works of Colo. v. City & Cnty. of Denver, 321 F.3d 950, 960 (10th Cir. 2003)(“Concrete
Works IV”); and H.B. Rowe Co. v. N.C. Dep’t of Transp, 615 F.3d 233, 236 (4th Cir. 2010) (“Rowe”).
15 Miss. Univ. for Women v. Hogan , 458 U.S. 718, 726 (1982); see also United States v. Virginia, 518 U.S. 515, 524 (1996) (“Virginia”).
16 Hogan, 458 U.S. at 751; see also Mich. Rd. Builders Ass’n, Inc. v. Milliken, 834 F.2d 583, 595 (6th Cir. 1987).
17 Hogan, 458 U.S. at 728; see also Schlesinger v. Ballard, 419 U.S. 498, 508 (1975) (“Ballard”).
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from the standard imposed upon MBE programs.18 The Third Circuit held that, whereas MBE
programs must be “narrowly tailored” to a “compelling state interest,” WBE programs must be
“substantially related” to “important governmental objectives.”19 In contrast, an MBE program
would survive constitutional scrutiny only by demonstrating a pattern and practice of systemic
racial exclusion or discrimination in which a state or local government was an active or passive
participant.20
The Ninth Circuit in Associated General Contractors of California v. City and County of San
Francisco (“AGCC I”) held that classifications based on gender require an “exceedingly
persuasive justification.”21 The justification is valid only if members of the gender benefited by
the classification actually suffer a disadvantage related to the classification, and the classification
does not reflect or reinforce archaic and stereotyped notions of the roles and ab ilities of women.22
The Eleventh Circuit United States Court of Appeals (Eleventh Circuit) also applied intermediate
scrutiny.23 In its review and affirmation of the district court’s holding, in Engineering Contractors
Association of South Florida v. Metropolitan Dade County (“Dade County II”), the Eleventh
Circuit cited the Third Circuit’s 1993 formulation in Philadelphia IV: “[T]his standard requires
the [County] to present probative evidence in support of its stated rationale for the gender
preference, discrimination against women-owned contractors.”24 Although the Dade County II
appellate court ultimately applied the intermediate scrutiny standard, it queried whether the United
States Supreme Court decision in United States v. Virginia,25 finding the all-male program at
Virginia Military Institute unconstitutional, signaled a heightened level of scrutiny.26 In the case
of United States v. Virginia, the U.S. Supreme Court held that parties who seek to defend gender -
based government action must demonstrate an “exceedingly persuasive justification” for that
action.27 While the Eleventh Circuit United States Court of Appeals echoed that speculation, it
concluded that “[u]nless and until the U.S. Supreme Court tells us otherwise, intermediate scrutiny
remains the applicable constitutional standard in gender discrimination cases, and a gender
preference may be upheld so long as it is substantially related to an important governmental
objective.”28
18 Contractors Ass’n of E. Pa. v. City of Philadelphia (“Philadelphia IV”), 6 F. 3d 990, 1001 (3d Cir. 1993).
19 Philadelphia IV, 6 F.3d at 1009-10.
20 Id. at 1002.
21 Associated Gen. Contractors of Cal. v. City & Cnty. of San Francisco , 813 F.2d 922, 940 (9th Cir. 1987) (“AGCC I”).
22 Ballard, 419 U.S. at 508.
23 Ensley Branch N.A.A .C.P. v. Seibels, 31 F. 3d 1548, 1579-80 (11th Cir. 1994).
24 Dade County II, 122 F.3d at 909 (citing Philadelphia IV, 6 F.3d at 1010; see also Saunders v. White, 191 F. Supp. 2d 95, 134 (D.D.C. 2002)
(stating “[g]iven the gender classifications explained above, the initial evaluation procedure must satisfy intermediate scrutiny to be
constitutional.”).
25 Virginia, 518 U.S. at 534.
26 Dade County II, 122 F.3d at 907-08.
27 Virginia, 518 U.S. at 534.
28 Dade County II, 122 F.3d at 908.
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In Dade County II, the Eleventh Circuit court noted that the Third Circuit in Philadelphia IV was
the only federal appellate court that explicitly attempted to clarify the evidentiary requirement
applicable to WBE programs.29 Dade County II interpreted that standard to mean that “evidence
offered in support of a gender preference must not only be ‛probative’ [but] must also be
‘sufficient.’”30
It also reiterated two principal guidelines of intermediate scrutiny evidentiary
analysis: (1) under this test, a local government must demonstrate some past
discrimination against women, but not necessarily discrimination by the
government itself;31 and (2) the intermediate scrutiny evidentiary review is not to
be directed toward mandating that gender-conscious affirmative action is used only
as a “last resort,”32 but instead ensuring that the affirmative action is “a product of
analysis rather than a stereotyped reaction based on habit.”33
This determination requires “evidence of past discrimination in the economic sphere at which the
affirmative action program is directed.”34 The Court also stated that “a gender-conscious program
need not closely tie its numerical goals to the proportion of qualified women in the market.”35
C. Local Business Enterprise Programs
Local Business Enterprise (LBE) programs are designed to stimulate the local economy by
utilizing businesses on public contracts that are located within a specified geographic boundary.
In AGCC I, a pre-Croson case, the Ninth Circuit Court of Appeals applied the rational basis
standard when evaluating the City and County of San Francisco’s Local Business Enterprise
program, holding that a local government may give a preference to local businesses to address the
economic disadvantages those businesses face in doing business within the City and County of
San Francisco.36
To survive a constitutional challenge under a rational basis review, the government entity need
only demonstrate that the governmental action or program is rationally related to a legitimate
29 Id. at 909.
30 Id. at 910.
31 Id. (quoting Ensley Branch, 31 F.3d at 1580).
32 Id. (quoting Hayes v. N. State Law Enforcement Officers Ass’n., 10 F.3d 207, 217 (4th Cir. 1993) (racial discrimination case).
33 Id. (quoting Philadelphia IV, 6 F.3d at 1010).
34 Id. (quoting Ensley Branch, 31 F.3d at 1581).
35 Id. at 929; cf, Builders Ass’n of Greater Chi. v. Cnty. of Cook , 256 F. 3d 642, 644 (7th Cir. 2001) (questioned why there should be a lesser
standard where the discrimination was against women rather than minorities.).
36 AGCC I, 813 F.2d at 943; Lakeside Roofing Company v. State of Missouri, et al., 2012 WL 709276, 39-41 (E.D.Mo. Mar. 5, 2012) (Note that
federal judges will generally rule the way that a previous court ruled on the same issue following the doctrine of stare decisis – the policy of
courts to abide by or adhere to principles established by decisions in earlier cases; however, a decision reached by a differ ent circuit is not
legally binding on another circuit court, it is merely persuasive and instructional on the issue).
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government interest.37 The Supreme Court cautioned government agencies seeking to meet the
rational basis standard by advising that, if a race and gender -neutral program is subjected to a
constitutional attack, the facts upon which the program is predicated will be subject to judicial
review.38 The rational basis standard of review does not have to be the government’s actual
interest. Rather, if the Court can merely hypothesize a legitimate interest served by the challenged
action, it will withstand the rational basis review.39 The term rational must convince an impartial
lawmaker that the classification would serve a legitimate public purpose that transcends the harm
to the members of the disadvantaged class.40
San Francisco conducted a detailed study of the economic disadvantages faced by San Francisco -
based businesses compared to businesses located in other jurisdictions. The study showed a
competitive disadvantage in public contracting for businesses located within the City compared to
businesses from other jurisdictions.
San Francisco-based businesses incurred higher administrative costs in doing business within the
City. Such costs included higher taxes, rents, wages, insurance rates, and benefits for labo r. In
upholding the LBE Ordinance, the Ninth Circuit held “. . . the city may rationally allocate its own
funds to ameliorate disadvantages suffered by local businesses, particularly where the city itself
creates some of the disadvantages."41
D. Small Business Enterprise Programs
Small Business Enterprise programs are designed to foster business development for small
businesses by maximizing their participation on government contracts. The size standards of the
program vary depending on the government agency’s eligibility requirements. A government
entity may implement a Small Business Enterprise program predicated upon a rational basis to
ensure adequate small business participation in government contracting. Rational basis is the
lowest level of scrutiny and the standard the courts apply to race and gender-neutral public
contracting programs.42
37 Armour v. City of Indianapolis, Ind., 132 S. Ct. 2073, 2080 (2012) (quoting Heller v. Doe, 509 U.S. 312, 319–320 (1993)).
38 Id.
39 Lakeside Roofing, 2012 WL 709276, 38; see KATHLEEN M. SULLIVAN& GERALD GUNTHER, CONS TITUTIONAL LAW
FOUNDATION PRESS Chapter 9 (16th ed. 2007).
40 Croson, 488 U.S. at 515.
41 AGCC I, 813 F.2d at 943.
42 Doe 1 v. Lower Merion Sch. Dist., 689 F. Supp. 2d 742, 748 (E.D. Pa. 2010).
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III. Burden of Proof
The procedural protocol established by Croson imposes an initial burden of proof upon the
government to demonstrate that the challenged MBE program is supported by a strong factual
predicate, i.e., documented evidence of past discrimination. Notwithstanding this requirement, the
plaintiff bears the ultimate burden of proof to persuade the Court that the MBE program is
unconstitutional. The plaintiff may challenge a government’s factual predicate on any of the
following grounds:43
• Disparity exists due to race-neutral reasons.
• Methodology is flawed.
• Data are not statistically significant.
• Controverting data exist.
A. Initial Burden of Proof
Croson requires defendant jurisdictions to produce a “strong basis in evidence” that the objective
of the challenged MBE program is to rectify the effects of past identified discrimination.44 Whether
or not the government has produced a strong basis in evidence is a question of law.45 The defendant
in a constitutional claim against a disparity study has the initial burden of proof to show that there
was past discrimination.46
Once the defendant meets this initial burden, the burden shifts to the plaintiff to prove that the
program is unconstitutional. “[W]hen the proponent of an affirmative action plan produces
sufficient evidence to support an inference of discrimination, the plaintiff must rebut that inference
in order to prevail.47 Because the sufficiency of the factual predicate supporting the MBE program
is at issue, factual determinations relating to the accuracy and validity of the proffered evidence
underlie the initial legal conclusion to be drawn.48
The adequacy of the government’s evidence is “evaluated in the context of the breadth of the
remedial program advanced by the [jurisdiction].”49 The onus is on the jurisdiction to provide a
factual predicate that is sufficient in scope and precision to demonstrate that contemporaneous
discrimination necessitated the adoption of the MBE program.50 When the jurisdiction supplies
43 Contractors Ass'n v. City of Philadelphia, 893 F. Supp. 419, 430, 431, 433, 437 (E.D. Pa.1995) (“Philadelphia V”) (These were the issues on
which the district court in Philadelphia reviewed the disparity study before it).
44 See Croson, 488 U.S. at 510; Philadelphia VI, 91 F.3d at 597 (citing Concrete Works of Colo. v. Denver, 36 F.3d 1513, 1522 (10th Cir. 1994)
(“Concrete Works II”)).
45 Id. (citing Associated Gen. Contractors v. New Haven , 791 F. Supp. 941, 944 (D. Conn. 1992)).
46 Concrete Works II, 36 F.3d at 1521-22 (citing Wygant v. Jackson Bd. of Educ., 476 U.S. 267, 292 (1986)).
47 Engineering Contractors Ass'n of S. Fla. v. Metropolitan Dade Co., 122 F.3d 895, 916 (11th Cir. 1997).
48 Concrete Works II, 36 F.3d at 1522.
49 Id. (citing Croson, 488 U.S. at 498).
50 See Croson, 488 U.S at 488.
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sufficient statistical information to support the inference of discrimination, the plaintiff must prove
that the statistical analysis that was utilized to support the challenged program is flawed.51
Therefore, the ultimate burden of proof is on the plaintiff.
B. Ultimate Burden of Proof
The party challenging an MBE program will bear the ultimate burden of proof throughout the
course of the litigation, despite the government’s obligation to produce a strong factual predicate
to support its program.52 The plaintiff must persuade the Court that the program is constitutionally
flawed, either by challenging the government’s factual predicate for the program or by
demonstrating that the program is overly broad. A plaintiff “cannot meet its burden of proof
through conjecture and unsupported criticism of the evidence.”53
Joining the majority in stating that the ultimate burden rests with the plaintiff, Justice O’Connor
explained the nature of the plaintiff’s burden of proof in her concurring opinion in Wygant v.
Jackson Board of Education (“Wygant”):54
[I]t is incumbent upon the nonminority [plaintiffs] to prove their case; they continue
to bear the ultimate burden of persuading the Court that the [government’s]
evidence did not support an inference of prior discrimination and thus a remedial
purpose, or that the plan instituted on the basis of this evidence was not sufficiently
“narrowly tailored.”55
In Philadelphia VI, the Third Circuit Court of Appeals clarified this allocation of the burden of
proof and the constitutional issue of whether or not facts constitute a “strong basis” in evidence
for race-based remedies.56 That Court wrote that the allocation of the burden of persuasion is
dependent on the plaintiff’s argument against the constitutionality of the program. If the plaintiff’s
theory is that an agency has adopted race-based preferences with a purpose other than remedying
past discrimination, the plaintiff has the burden of convincing the Court that the identified remedial
motivation is a pretext and that the real motivation was something else.57 If, on the other hand, the
plaintiff argues there is no existence of past discrimination within the agency, the plaintiff must
successfully rebut the agency’s evidentiary facts and prove their inaccuracy.58
51 Engineering Contractors Ass'n of S. Fla. v. Metropolitan Dade Co., 943 F. Supp. 1546, 1558-61 (S.D. Fla. 1996).
52 See Wygant, 476 U.S. at 277-78, 293.
53 Concrete Works of Colo., Inc. v. City & Cnty. of Denver , 321 F.3d 950, 989 (10th Cir. 2003).
54 Id. at 293 (O’Connor, S., concurrence).
55 Wygant, 476 U.S. at 277-78.
56 Philadelphia VI, 91 F.3d at 597.
57 Philadelphia VI, 91 F.3d at 597.
58 Id. at 597-598.
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However, the ultimate issue of whether sufficient evidence exists to prove past discrimination is a
question of law. The burden of persuasion in the traditional sense plays no role in the Court’s
resolution of that ultimate issue.59
Concrete Works VI made clear that the plaintiff’s burden is an evidentiary one; it cannot be
discharged simply by argument. The Court cited its opinion in Adarand Constructors Inc. v. Slater,
228 F.3d 1147, 1173 (10th Cir. 2000): “[g]eneral criticism of disparity studies, as opposed to
particular evidence undermining the reliability of the particular disparity study, is of little
persuasive value.”60 The requisite burden of proof needed to establish a factual predicate for race
and gender-conscious goals as set forth by Croson and its progeny is described in Section IV.
The Tenth and Eleventh Circuits present alternative approaches to the legal evidentiary
requirements of the shifting burden of proof in racial classification cases. This split among the
circuits pertains to the allocation of the burden of proof once the initi al burden of persuading the
Court is met—that persisting vestiges of discrimination exist.61
The Tenth Circuit’s opinion in Concrete Works VI states that the burden of proof remains with the
plaintiff to demonstrate that an ordinance is unconstitutional.62 On the other hand, the Eleventh
Circuit in Hershell contends that the government, as the proponent of the classification, bears the
burden of proving that its consideration of race is narrowly tailored to serve a compelling state
interest, and that the government must always maintain a “strong basis in evidence” for
undertaking affirmative action programs.63 Therefore, the proponent of the classification must
meet a substantial burden of proof, a standard largely allocated to the government to prove that
sufficient vestiges of discrimination exist to support the conclusion that remedial action is
necessary. Within the Eleventh Circuit, judicial review of a challenged affirmative action program
focuses primarily on whether or not the government entity can meet the burden of proof.
In practice, the standards prescribed in the Eleventh Circuit for proving the constitutionality of a
proposed M/WBE framework are rooted in Engineering Contractors Ass’n v. Metropolitan Dade
County, the same Eleventh Circuit case that was cited to in the T enth Circuit.64 In Dade County I,
the Court found that a municipality can justify affirmative action by demonstrating “gross
statistical disparities” between the proportion of minorities awarded contracts and the proportion
59 At first glance, the Third Circuit and the Eleventh Circuit positions appear to be inconsistent as to whether the issue at hand is a legal issue or
a factual issue. However, the two courts were examining the issues in different scenarios. For instance, the Third Circuit wa s examining whether
enough facts existed to determine if past discrimination existed, and the Eleventh Circuit was examining whether the remedy the agency utilized
was the appropriate response to the determined past discrimination. Therefore, depending upon the Plaintiff’s arguments, a co urt reviewing an
MBE program is likely to be presented with questions of law and fact.
60 Concrete Works VI, 321 F.3d at 979.
61 Hershell Gill Consulting Eng’rs, Inc. v. Miami-Dade Cnty., 333 F. Supp. 2d 1305, 1325 (S.D. Fla. 2004).
62 Concrete Works VI, 321 F.3d at 959 (quoting Adarand v. Pena, 228 F.3d 1147, 1176 (10th Cir. 2000) (“We reiterate that the ultimate burden
of proof remains with the challenging party to demonstrate the unconstitutionality of an affirmative -action program.”)).
63 Hershell, 333 F. Supp. 2d at 1305 (stating that Concrete Works is not persuasive because it conflicts with the allocation of the burden of
proof stated by Eleventh Circuit precedent in Johnson v. Board of Regents of the University of Georgia, 263 F.3d 1234, 1244 (11th Cir.
2001)).
64 943 F. Supp. 1546 (S.D. Fla. 1996) (“Dade County I”).
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of minorities willing and able to do the work, or by presenting anecdotal evidence, especially if
buttressed by statistical data.65
IV. Croson Evidentiary Framework
Government entities must construct a strong evidentiary framework to stave off legal challenges
and ensure that the adopted MBE program comports with the requirements of the Equal Protection
Clause of the United States Constitution. The framework must comply with the stringent
requirements of the strict scrutiny standard. Accordingly, there must be a strong basis in evidence
that tends to show past discrimination, and the race-conscious remedy must be “narrowly tailored,”
as set forth in Croson.66 A summary of the appropriate types of evidence to satisfy the first element
of the Croson standard follows.
A. Active and Passive Participation
Croson requires that the local entity seeking to adopt an MBE program must have perpetuated the
discrimination to be remedied by the program.67 However, the local entity need not have been an
active perpetrator of such discrimination. Passive participation will satisfy this part of the Court’s
strict scrutiny review.68 An entity will be considered an “active” participant if the evidence shows
that it created barriers that actively exclude MBEs from its contracting opportunities. An entity
will be considered to be a “passive” participant in private sector discriminatory practices if it has
infused tax dollars into that discriminatory industry.69
Until Concrete Works I, the inquiry regarding passive discrimination was limited to the
subcontracting practices of government prime contractors. The Tenth Circuit, in Concrete Works
I, considered a purely private sector definition of passive discrimination, holding that evidence of
a government entity infusing its tax dollars into a discriminatory system can satisfy passive
discrimination.70
In Concrete Works I, the district court granted summary judgment in favor of the City of Denver
in 1993.71 Concrete Works appealed to the Tenth Circuit, in Concrete Works II, in which the
summary judgment in favor of the City of Denver was reversed and the case was remanded to the
district court for trial.72 The case was remanded with specific instructions permitting the parties
65 Id. at 1559-60.
66 Croson, 488 U.S. at 486.
67 Id. at 488.
68 Id. at 492, 509.
69 Id. at 492, accord Coral Constr., 941 F.2d at 916.
70 Concrete Works of Colo., Inc. v. City & Cnty. of Denver, 823 F. Supp. 821, 824 (D. Colo. 1993)(“Concrete Works I”), rev’d, 36 F.3d 1513
(10th Cir. 1994), rev’d, 86 F. Supp. 2d 1042 (D. Colo. 2000), rev’d, 321 F.3d 950 (10th Cir. 2003).
71 Concrete Works I, 823 F. Supp.at 824.
72 Concrete Works II, 36 F.3d at 1530-31.
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“to develop a factual record to support their competing interpretations of the empirical data.”73 On
remand, the district court entered a judgment in favor of the plaintiff, holding that the City’s
ordinances violated the Fourteenth Amendment.74
The district court in Concrete III rejected the four disparity studies the City offered to support the
continuation of Denver's M/WBE program.75 The Court surmised that (1) the methodology
employed in the statistical studies was not “designed to answer the relevant questions,”76 (2) the
collection of data was flawed, (3) important variables were not accounted for in the analyses, and
(4) the conclusions were based on unreasonable assumptions.77 The Court deemed that the “most
fundamental flaw” in the statistical evidence was the lack of “objective criteria [to] define who is
entitled to the benefits of the program and [which groups should be] excluded from those
benefits.”78 The statistical analysis relied upon by the City to support its M/WBE program was
conducted as a result of the ensuing litigation. The statistical evidence proffered by the City to the
Court was not objective because it lacked a correlation to the current M/WBE program goals.
The Tenth Circuit on appeal rejected the district court’s analysis because the district court’s queries
required Denver to prove the existence of discrimination. Moreover, the Tenth Circuit explicitly
held that “passive” participation included private sector discrimination in the marketplace. The
Court found that marketplace discrimination is relevant when the agency’s prime contractors’
practices are discriminatory against their subcontractors:
The Court, however, did set out two conditions that must be met for the
governmental entity to show a compelling interest. “First, the discrimination must
be identified discrimination.” (citation omitted). The City can satisfy this condition
by identifying the discrimination “public or private, with some specificity.”
(internal quotes and citation omitted).79
In Concrete Works IV, the Tenth Circuit held that the governmental entity must also have a “strong
basis in evidence to conclude that remedial action was necessary.”80 The Tenth Circuit further held
that the city was correct in its attempt to show that it “indirectly contributed to private
discrimination by awarding public contracts to firms that, in turn, discriminated against MBE
and/or WBE subcontractors in other private portions of their business.”81 While the Tenth Circuit
73 Id.
74 Concrete Works of Colo., Inc. v. City & Cnty. of Denver , 86 F. Supp. 2d 1042, 1079 (D. Colo. 2000)(“Concrete Works III”).
75 Id. at 1065-68.
76 Id. at 1067, 1071.
77 Id. at 1057-58, 1071.
78 Id. at 1068.
79 Concrete Works IV, 321 F.3d at 975-76.
80 Id. at 976 (quoting Shaw v. Hunt, 517 U.S. 804, 909 (1996)).
81 Id. at 976.
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noted that the record contained “extensive evidence” of private sector discrimination, the question
of the adequacy of private sector discrimination as the factual predicate for a race-based remedy
was not before the Court.82
Ten months after Concrete Works IV, the question of whether or not a particular race-based remedy
is narrowly tailored when it is based solely on business practices within the private sector was at
issue in Builders Association of Greater Chicago v. City of Chicago.83 The plaintiff in Builders
Association of Greater Chicago challenged the City’s construction set-aside program. The Court
considered pre- and post-enactment evidence in support of the six-year-old M/WBE program.84
The challenged program consisted of a 16.9 percent MBE subcontracting goal, a 10-percent MBE
prime contracting goal, a 4.5 percent WBE subcontracting goal, and a 1 percent WBE prime
contracting goal.85
The district court found that private sector business practices offered by the city, which were based
on United States Census data and surveys, constituted discrimination against minorities in the
Chicago market area.86 However, the district court did not find the City’s M/WBE subcontracting
goal to be a narrowly tailored remedy given the factual predicate. The Court found that the study
did not provide a meaningful, individualized review of M/WBEs to formulate remedies “more akin
to a laser beam than a baseball bat.”87 The City was ordered to suspend its M/WBE goals program.
As recently as 2010, the Fourth Circuit in H.B. Rowe Co. v. Tippett ruled that the State of North
Carolina could not rely on private-sector data to demonstrate that prime contractors underutilized
women subcontractors in the general construction industry.88 The Court found that the private
sector data did not test whether the underutilization was statistically significant.89
B. Systemic Discriminatory Exclusion
Croson established that a local government enacting a race-conscious contracting program must
demonstrate identified systemic discriminatory exclusion on the basis of race or any other
illegitimate criteria (arguably gender).90 Thus, it is essential to demonstrate a pattern and practice
82 Id. at 959, 977, 990.
83 Builders Ass’n of Greater Chi. v. City of Chi., 298 F. Supp. 2d 725, 732 (N.D. III. 2003).
84 Id. at 726, 729, 733-34.
85 Id. at 729.
86 Id. at 735-37.
87 Id. at 737-39, 742.
88 Rowe, 615 F.3d at 236.
89 Id. at 255.
90 Croson, 488 U.S. at 492; see Monterey Mech. Co. v. Pete Wilson, 125 F.3d 702, 713 (9th Cir. 1997); see also W.H. Scott Constr. Co. v. City of
Jackson, 199 F.3d 206, 218-20 (1999) (held the City’s MBE program was unconstitutional for construction contracts because minority
participation goals were arbitrarily set and not based on any objective data. Moreover, the Court noted that ha d the City implemented the
recommendations from the disparity study it commissioned, the MBE program may have withstood judicial scrutiny (the City was not satisfied
with the study and chose not to adopt its conclusions)).
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of such discriminatory exclusion in the relevant market area.91 Using appropriate evidence of the
entity’s active or passive participation in the discrimination, as discussed above, past
discriminatory exclusion must be identified for each racial group to which a remedy would apply.92
Mere statistics and broad assertions of purely societal discrimination will not suffice to support a
race or gender-conscious program.
Croson elucidates two ways an entity may establish the requisite factual predicate of
discrimination. First, a significant statistical disparity between the number of qualified minority
contractors willing and able to perform a particular service and the number of such contractors
actually engaged by an entity or by the entity’s prime contractors may support an inference of
discriminatory exclusion.93 In other words, when the relevant statistical pool is used, a showing of
statistically significant underutilization “may constitute prima facie proof of a pattern or practice
of discrimination[.]”94
The Croson Court made clear that both prime contract and subcontracting data were relevant.95
The Court observed that “[w]ithout any information on minority participation in subcontracting, it
is quite simply impossible to evaluate overall minority representation in the city’s construction
expenditures.”96 Subcontracting data are also an important means by which to assess suggested
future remedial actions. Because the decision makers are different for the awarding of prime
contracts and subcontracts, the remedies for discrimination identified at a prime contractor versus
subcontractor level may also be different.
Second, “evidence of a pattern of individual discriminatory acts can, if supported by appropriate
statistical proof, lend support to a local government’s determination that broader remedial relief is
justified.”97 Thus, if a local government has statistical evidence that non-minority contractors are
systematically excluding minority businesses from subcontracting opportunities, it may act to end
the discriminatory exclusion.98 Once an inference of discriminatory exclusion arises, the entity
may act to dismantle the closed business system “by taking appropriate measures against those
who discriminate on the basis of race or other illegitimate criteria.”99 Croson further states, “In the
91 Croson, 488 U.S. at 509.
92 Id. at 506. (The Court stated in Croson, “[t]he random inclusion of racial groups that, as a practical matter, may never have suffered from
discrimination in the construction industry in Richmond suggests that perhaps the city’s purpose was not in fact to remedy past discrimination”);
See N. Shore Concrete & Assoc. v. City of New York, 1998 U.S. Dist. LEXIS 6785 * 55 (E.D.N.Y. April 12, 1998) (rejected the inclusion of
Native Americans and Alaskan Natives in the City’s program).
93 Croson, 488 U.S. at 509.
94 Id. at 501 (citing Hazelwood Sch. Dist. v. United States, 433 U.S. 299, 307-08 (1977)).
95 Id. at 502-03.
96 Id.
97 Croson, 488 U.S. at 509.
98 Id.
99 Id. (emphasis added).
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extreme case, some form of narrowly tailored racial preference might be necessary to break down
patterns of deliberate exclusion.”100
In Coral Construction, the Ninth Circuit Court of Appeals further elaborated upon the type of
evidence needed to establish the factual predicate that justifies a race-conscious remedy.101 The
Court held that both statistical and anecdotal evidence should be used to establish systemic
discriminatory exclusion in the relevant marketplace as the factual predicate for an MBE
program.102
The Court explained that statistical evidence alone often does not account for the complex factors
and motivations guiding contracting decisions, many of which may be entirely race neutral.103
Likewise, anecdotal evidence alone is unlikely to establish a systemic pattern of discrimination.104
Nonetheless, anecdotal evidence is important because the individuals who testify about their
personal experiences bring “the cold numbers convincingly to life.”105
1. Geographic Market
Croson did not speak directly to how the geographic market is to be determined. In Coral
Construction, the Ninth Circuit Court of Appeals held that “an MBE program must limit its
geographical scope to the boundaries of the enacting jurisdiction.”106 Conversely, in Concrete
Works I, the district court specifically approved the Denver Metropolitan Statistical Area (MSA)
as the appropriate market area since 80 percent of the construction contracts were based there.107
Taken together, these cases support a definition of market area that is r easonable rather than
dictated by a specific formula. Because Croson and its progeny did not provide a bright-line rule
for local market area, the determination should be fact based. An entity may include consideration
of evidence of discrimination within its own jurisdiction.108 Extra-jurisdictional evidence may be
permitted, when it is reasonably related to where the jurisdiction contracts.109
100 Id. (emphasis added).
101 Coral Constr., 941 F.2d at 917-18, 920-26.
102 Id. at 919.
103 Id.
104 Id.
105 Id. at 919 (quoting Int’l Bhd. of Teamsters v. United States, 431 U.S. 324, 339 (1977) (“Teamster”)).
106 Coral Constr., 941 F.2d at 925.
107 Concrete Works I, 823 F. Supp. at 835-836 (D. Colo. 1993); rev’d on other grounds, 36 F.3d 1513 (10th Cir. 1994).
108 Cone Corp. v. Hillsborough Cnty., 908 F.2d 908, 915 (11th Cir. 1990); Associated Gen. Contractors v. Coal. for Econ. Equity, 950 F.2d
1401, 1415 (9th Cir. 1991) (“AGCC II”).
109 There is a related question of which firms can participate in a remedial program. In Coral Construction, the Court held that the definition of
“minority business” used in King County’s MBE program was over -inclusive. The Court reasoned that the definition was overbroad because
it included businesses other than those who were discriminated against in the King County business community. The program wou ld have
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2. Current Versus Historical Evidence
In assessing the existence of identified discrimination through demonstration of a disparity
between MBE utilization and availability, the entity should examine disparity data both prior to
and after the entity’s current MBE program is enacted. This is referred to as “pre-program” versus
“post-program” data.
Croson requires that an MBE program be “narrowly tailored” to remedy current evidence of
discrimination.110 Thus, goals must be set according to the evidence of disparity found. For
example, if there is a current disparity between the percentage of an entity’s utilization of Hispanic
construction contractors and the availability of Hispanic construction contractors in that entity’s
marketplace, then that entity can set a goal to bridge that disparity.
It is not mandatory to examine a long history of an entity’s utilization to assess current evidence
of discrimination. In fact, Croson indicates that it may be legally fatal to justify an MBE program
based upon outdated evidence.111 Therefore, the most recent two or three years of an entity’s
utilization data would suffice to determine if a statistical disparity exists between current M/WBE
utilization and availability.112
3. Statistical Evidence
To determine whether or not statistical evidence is adequate to give rise to an inference of
discrimination, courts have looked to the “disparity index,” which consists of the percentage of
minority or women contractor participation in local contracts divided by the percentage of minority
or women contractor availability or composition in the population of available firms in the local
market area.113 Disparity indexes have been found highly probative evidence of discrimination in
which they ensure that the “relevant statistical pool” of minority or women contractors is b eing
considered.114
allowed, for instance, participation by MBEs who had no prior contact with the County. Hence, locatio n within the geographic area is not
enough. An MBE had to have shown that it previously sought business or is currently doing business in the market area.
110 See Croson, 488 U.S. at 509-10.
111 Croson, 488 U.S. at 499 (stating, “[i]t is sheer speculation how many minority firms there would be in Richmond absent past societal
discrimination”).
112 See AGCC II, 950 F.2d at 1414 (consultant study looked at City’s MBE utilization over a one -year period).
113 Although the disparity index is a common category of statistical evidence considered, other types of statistical evidence have been considered.
In addition to looking at Dade County’s contracting and subcontracting statistics, the district court also considered marketp lace data statistics
(which looked at the relationship between the race, ethnicity, and gender of surveyed firm owners and the reported sales and receipts of those
firms), the County’s Wainwright study (which compared construction business ownership rates of M/WBEs to those of non -M/WBEs and
analyzed disparities in personal income between M/WBE and non -M/WBE business owners), and the County’s Brimmer Study (which
focused only on Black-owned construction firms and looked at whether disparities existed when the sales and receipts of Black -owned
construction firms in Dade County were compared with the sales and receipts of all Dade County construction firms).The Court af firmed the
judgment that declared appellant's affirmative action plan for awarding county construction contracts unconstitutional a nd enjoined the plan's
operation because there was no statistical evidence of past discrimination and appellant failed to consider race and ethic -neutral alternatives
to the plan.
114 Rowe, 615 F.3d at 243-44; see Dade County I, 943 F. Supp. at 1546, 1559, aff’d, 122 F.3d 895 (11th Cir. 1997); see also Concrete Works II,
36 F.3d at 1513, 1523.
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The Third Circuit Court of Appeals, in Philadelphia VI, ruled that the “relevant statistical pool”
includes those businesses that not only exist in the marketplace but also are qualified and interested
in performing the public agency’s work. In that case, the Third Circuit rejected a statistical
disparity finding in which the pool of minority businesses used in comparing utilization to
availability was composed of those merely licensed to operate in the City of Philadelphia. A license
to do business with the City, standing alone, does not indicate either willingness or capability to
do work for the City. The Court concluded that this particular statistical disparity did not satisfy
Croson.115
When using a pool of relevant statistical evidence, a disparity between the utilization and
availability of M/WBEs can be shown in more than one way. First, the number of M/WBEs utilized
by an entity can be compared to the number of available M/WBEs. This is a strict Croson
“disparity” formula. A significant statistical disparity between the number of M/WBEs that an
entity utilizes in a given industry and the number of available M/WBEs in the relevant market area
specializing in the specified product/service category would support an inference of discriminatory
exclusion.
Second, M/WBE dollar participation can be compared to M/WBE availability. This comparison
could show a disparity between an entity’s award of contracts to available market area non -
minority male businesses and the award of contracts to M/WBEs. Thus, in AGCC II, an
independent consultant’s study “compared the number of available MBE prime construction
contractors in San Francisco with the amount of contract dollars awarded by the City to San
Francisco-based MBEs” over a one-year period.116 The study found that available MBEs received
far fewer construction contract dollars in proportion to their numbers than their available non -
minority counterparts.117 AGCC II argued to the Ninth Circuit that the preferences given to MBEs
violated the equal protection clause of the Fourteenth Amendment of the United States
Constitution. The district court determined that AGCC II only demonstrated a possibility of
irreparable injury on the grounds that such injury is assumed for which constitutional rights h ave
been alleged to be violated but failed to demonstrate a likelihood of success on the merits. On
appeal, The Ninth Circuit affirmed the district court’s ruling.118
Whether a disparity index supports an inference that there is discrimination in the market area
depends not only on what is being compared, but also on the statistical significance of any such
disparity. In Croson, Justice O’Connor opined, “[w]here the gross statistical disparities can be
shown, they alone, in a proper case, may constitute a prima facie proof of a pattern or practice of
115 Philadelphia VI, 91 F.3d at 601-603. The courts have not spoken to the non-M/WBE component of the disparity index. However, if only as
a matter of logic, the “availability” of non-M/WBEs requires that their willingness to be government contractors be established. The same
measures used to establish the interest of M/WBEs should be applied to non-M/WBEs.
116 AGCC II, 950 F.2d at 1414.
117 Id. at 1414. Specifically, the study found that MBE availability was 49.5 percent for prime construction, but MBE dollar participation was
only 11.1 percent; that MBE availability was 36 percent prime equipment and supplies, but MBE dollar participation was 17 per cent; and that
MBE availability for prime general services was 49 percent, but dollar participation was 6.2 percent.
118 Id. at 1401.
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discrimination.”119 However, the Court has not assessed or attempted to cast bright lines for
determining if a disparity index is sufficient to support an inference of discrimination. In the
absence of such a formula, the Tenth Circuit determined that the analysis of the disparity index
and the findings of its significance are to be judged on a case-by-case basis.120
Following the dictates of Croson, courts may carefully examine whether there are data that show
MBEs are qualified, ready, willing, and able to perform.121 Concrete Works II made the same
point: capacity—i.e., whether the firm is “able to perform”—is a ripe issue when a disparity study
is examined on the merits:
[Plaintiff] has identified a legitimate factual dispute about the accuracy of Denver’s
data and questioned whether Denver’s reliance on the percentage of MBEs and
WBEs available in the marketplace overstates “the ability of MBEs or WBEs to
conduct business relative to the industry as a whole because M/WBEs tend to be
smaller and less experienced than non-minority owned firms.” In other words, a
disparity index calculated on the basis of the absolute number of MBEs in the local
market may show greater underutilization than does data that take into
consideration the size of MBEs and WBEs.122
Notwithstanding that appellate concern, the disparity studies before the district court on remand
did not examine the issue of M/WBE capacity to perform Denver’s public-sector contracts.
The Sixth Circuit Court of Appeals, in Associated General Contractors of Ohio, Inc. v. Drabik
(“Drabik”), concluded that for statistical evidence to meet the legal standard of Croson, it must
consider the issue of capacity.123 The State’s factual predicate study based its statistical evidence
on the percentage of MBE businesses in the population. The statistical evidence “did not take into
account the number of minority businesses that were construction firms, let alone how many were
qualified, willing, and able to perform state contracts.”124 The Court reasoned as follows:
Even statistical comparisons that might be apparently more pertinent, such as with
the percentage of all firms qualified in some minimal sense, to perform the work in
question, would also fail to satisfy the Court’s criteria. If MBEs comprise 10 percent
of the total number of contracting firms in the State, but only get 3 percent of the
dollar value of certain contracts, that does not alone show discrimination or even
disparity. It does not account for the relative size of the firms, either in terms of their
119 Croson, 488 U.S. at 501 (quoting Hazelwood Sch. Dist., 433 U.S. at 307-308).
120 Concrete Works II, 36 F.3d at 1522.
121 The Philadelphia study was vulnerable on this issue.
122 Concrete Works II, 36 F.3d at 1528.
123 Associated Gen. Contractors of Ohio, Inc. v. Drabik , 214 F.3d 730, 734-38 (6th Cir. 2000) (“Drabik”). The Court reviewed Ohio’s 1980,
pre-Croson, program, which the Sixth Circuit found constitutional in Ohio Contractors Ass’n v. Keip, 713 F.2d 167, 176 (6th Cir. 1983),
finding the program unconstitutional under Croson.
124 Drabik, 214 F.3d at 736.
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ability to do particular work or in terms of the number of tasks they have resources
to complete.125
Drabik also pointed out that the State not only relied upon the wrong type of statistical data, but
also that the data sets were more than twenty years old. Therefore, an entity must study current
data that indicate the availability and qualifications of the MBEs.
The opinions in Philadelphia VI126 and Dade County I,127 regarding disparity studies involving
public sector contracting, are particularly instructive in defining availability. In Philadelphia VI,
the earlier of the two decisions, contractors’ associations challenged a city ordinance that created
set-asides for minority subcontractors on city public works contracts. The Third Circuit granted
summary judgment in favor of the contractors.128 The Third Circuit upheld the third appeal,
affirming that there was no firm basis in evidence for finding that race-based discrimination existed
to justify a race-based program and that the program was not narrowly tailored to address past
discrimination by the City.129
The Third Circuit reviewed the evidence of discrimination in prime contracting and stated that
whether or not it is strong enough to infer discrimination is a “close call” that the Court “chose not
to make.”130 It was unnecessary to make this determination because the Court found that even if
there were a strong basis in evidence for the program, a subcontracting program was not narrowly
tailored to remedy prime contracting discrimination.131
When the Court looked at subcontracting, it found that a firm basis in evidence did not exist. The
only subcontracting evidence presented was a review of a random 25 to 30 percent of project
engineer logs on projects valued at more than $30,000.132 The consultant determined that no MBEs
were used during the study period based on recollections of the former general counsel to the
General and Specialty Contractors Association of Philadelphia regarding whether or not the
owners of the utilized firms were MBEs. The Court found this evidence insufficient as a basis for
finding that prime contractors in the market area were discriminating against subcontractors.133
125 Id.
126 Philadelphia VI, 91 F.3d at 604-605.
127 Dade County I, 943 F. Supp. at 1582-83.
128 Philadelphia VI, 91 F.3d at 590.
129 Id. at 609-10.
130 Id. at 605.
131 Philadelphia VI, 91 F.3d at 605.
132 Philadelphia VI, 91 F.3d at 600.
133 Another problem with the program was that the 15 percent goal was not based on data indicating that minority businesses in the market area
were available to perform 15 percent of the City’s contracts. The Court noted, however, that “we do not suggest that the perc entage of the
preferred group in the universe of qualified contractors is necessarily the ceiling for all set-asides.” The Court also found the program flawed
because it did not provide sufficient waivers and exemptions, as well as consideration of race -neutral alternatives.
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The Third Circuit has recognized that consideration of qualifications can be approached at different
levels of specificity and that the practicality of the approach should also be weighed. The Court of
Appeals found that “[i]t would be highly impractical to review the hundreds of contracts awarded
each year and compare them to each and every MBE” and that it was a “reasonable choice” under
the circumstances to use a list of M/WBE-certified contractors as a source for available firms.134
Although, theoretically, it may have been possible to adopt a more refined approach, the Court
found that using the list of certified contractors was a rational approach to identifying qualifie d
firms.135
In order to qualify for certification, the federal certification program required firms to detail their
bonding capacity, size of prior contracts, number of employees, financial integrity, and equipment
owned. According to the Court, “the process by which the firms were certified [suggests that] those
firms were both qualified and willing to participate in public works projects.”136 The Court found
certification to be an adequate process of identifying capable firms, recognizing that the process
may even understate the availability of MBE firms.137 Therefore, the Court was somewhat flexible
in evaluating the appropriate method of determining the availability of MBE firms in the statistical
analysis of a disparity.138
In Dade County I, the district court held that the County had not shown the compelling interest
required to institute a race-conscious program, because the statistically significant disparities upon
which the County relied could be better explained by other factors than discrim ination. Statistical
disparities existed only when disparity was measured between the proportion of minority
businesses and the proportion of contract dollars that the firms received, but statistical disparities
did not exist when presented in the award of contracts to minority business. The Court determined
that the conflicts present in the statistical analysis was likely due to the County’s failure to account
for business size in the availability analysis.139 The Dade County district court accepted the
disparity study’s limiting of “available” prime construction contractors to those that had bid at
least once in the study period. However, it must be noted that relying solely on bidders to identify
available firms may have limitations. If the solicitation of bidders is biased, then the results of the
bidding process will be biased.140 In addition, a comprehensive count of bidders is dependent on
the adequacy of the agency’s record keeping.141
134 Philadelphia VI, 91 F.3d at 603.
135 Philadelphia VI, 91 F.3d at 603-605, 609.
136 Id. at 603.
137 Id.
138 Id.
139 Dade County I, 943 F. Supp. at 1560-64.
140 Cf. League of United Latin Am. Citizens v. Santa Ana, 410 F. Supp. 873, 897 (C.D. Cal. 1976); Reynolds v. Sheet Metal Workers, Local 102,
498 F. Supp. 952, 964 n. 12 (D. D.C. 1980), aff’d, 702 F.2d 221 (D.C. Cir. 1981) (involving the analysis of available applicants in the
employment context).
141 Cf. EEOC v. Am. Nat’l Bank, 652 F.2d 1176, 1196-1197 (4th Cir. 1981), cert. denied, 459 U.S. 923 (1981) (in the employment context, actual
applicant flow data may be rejected where race coding is speculative or nonexistent).
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The appellate court in Dade County did not determine whether the County presented sufficient
evidence to justify the M/WBE program. It merely ascertained that the lower court was not clearly
erroneous in concluding that the County lacked a strong basis in evidence to justify race-conscious
affirmative action.142 The appellate court did not prescribe the district court’s analysis or any other
specific analysis for future cases.
C. Anecdotal Evidence
In Croson, Justice O’Connor opined that “evidence of a pattern of individual discriminatory acts
can, if supported by appropriate statistical proof, lend support to a local government’s
determination that broader remedial relief is justified.”143 Anecdotal evidence should be gathered
to determine if minority contractors are systematically being excluded from contracting
opportunities in the relevant market area. Remedial measures fall along a sliding scale determined
by their intrusiveness on non-targeted groups. At one end of the spectrum are race-neutral
measures and policies, such as outreach to all segments of the business community regardless of
race. They are not intrusive and, in fact, require no evidence of discrimination before
implementation. Conversely, race-conscious measures, such as set-asides, fall at the other end of
the spectrum and require a greater amount of evidence.144
As discussed below, anecdotal evidence alone is insufficient to establish the requisite predicate for
a race-conscious program. Its value lies in pointing to remedies that are “narrowly tailored,” the
second prong of a Croson study. The following types of anecdotal evidence have been presented
to and relied on by the Ninth Circuit in both Coral Construction and AGCC II, to justify the
existence of an M/WBE program:
• M/WBEs denied contracts despite being the low bidders—Philadelphia145
• Prime contractors showing MBE bids to non-minority subcontractors to find a non-
minority firm to underbid the MBEs—Cone Corporation v. Hillsborough County146
• M/WBEs’ inability to obtain contracts for private sector work—Coral Construction147
• M/WBEs told that they were not qualified, although they were later found to be qualified
when evaluated by outside parties—AGCC II148
142 Dade County I, 943 F. Supp. at 1557; Dade County II, 122 F.3d at 904.
143 Croson, 488 U.S. at 509; see Teamsters, 431 U.S. at 338.
144 Cf. AGCC II, 950 F.2d at 1417-18 (in finding that an ordinance providing for bid preferences was narrowly tailored, the Ninth Circuit stated
that the program encompassed the required flexibility and stated that “the burdens of the bid preferences on those not entitled to them appear
relatively light and well distributed. In addition, in contrast to remedial measures struck down in other cases, those biddin g have no settled
expectation of receiving a contract. [Citations omitted.]”).
145 Philadelphia, 6 F.3d at 994-5.
146 Cone Corp., 908 F.2d at 916.
147 For instance, where a small percentage of an MBE or WBE’s business comes from private contracts and most of its business come s from race
or gender-based set-asides, this would demonstrate exclusion in the private industry. Coral Constr., 941 F.2d at 933 (WBE’s affidavit indicated
that less than 7 percent of the firm’s business came from private contracts and that most of its business resulted from gende r-based set-asides).
148 AGCC II, 950 F.2d at 1415.
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• Attempts to circumvent M/WBE project goals—Concrete Works II149
• Harassment of M/WBEs by an entity’s personnel to discourage them from bidding on an
entity’s contracts—AGCC II150
Courts must assess the extent to which relief measures disrupt settled “rights and expectations”
when determining the appropriate corrective measures.151 Presumably, courts would look more
favorably upon anecdotal evidence in support of a less intrusive program than they would in
support of a more intrusive one. For example, if anecdotal accounts relate experiences of
discrimination in obtaining bonds, they may be sufficient evidence to support a bonding program
that assists M/WBEs.152 However, these accounts would not be evidence of a statistical availability
that would justify a racially-limited program such as a set-aside.
As noted above, the Croson Court found that the City of Richmond’s MBE program was
unconstitutional because the City failed to provide a factual basis to support its MBE program.
However, the Court opined that “evidence of a pattern of individual discriminatory acts can, if
supported by appropriate statistical proof, lend support to a local government’s determination that
broader remedial relief is justified.”153
In part, it was the absence of statistical evidence that proved fatal to the program. The Supreme
Court stated that “[t]here was no direct evidence of race discrimination on the part of the city in
letting contracts or any evidence that the city’s prime contractors had discriminated against
minority-owned subcontractors.”154
This was not the situation confronting the Ninth Circuit in Coral Construction. There, the 700-
plus page appellate records contained the affidavits of “at least 57 minority or women contractors,
each of whom complain in varying degree of specificity about discrimination within the local
construction industry. . . These affidavits certainly suggest that ongoing discrimination m ay be
occurring in much of the King County business community.”155
Nonetheless, this anecdotal evidence alone was insufficient to justify King County’s MBE
program since “[n]otably absent from the record, however, is any statistical data in support of the
County’s MBE program.”156 After noting the Supreme Court’s reliance on statistical data in Title
149 Concrete Works II, 36 F.3d at 1530.
150 AGCC II, 950 F.2d at 1415.
151 Wygant, 476 U.S. at 283.
152 Teamsters, 431 U.S. at 339; Coral Constr., 941 F.2d at 919.
153 Croson, 488 U.S. at 509 (citing Teamsters, 431 U.S. at 338).
154 Croson, 488 U.S. at 480.
155 Coral Constr., 941 F.2d at 917-18.
156 Id. at 918 (emphasis added) (additional statistical evidence gathered after the program had been implemented was also considered by the
Court and the case was remanded to the lower court for an examination of the factual predicate).
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VII employment discrimination cases and cautioning that statistical data must be carefully used,
the Court elaborated on its mistrust of purely anecdotal evidence:
Unlike the cases resting exclusively upon statistical deviations to prove an equal
protection violation, the record here contains a plethora of anecdotal evidence.
However, anecdotal evidence, standing alone, suffers the same flaws as statistical
evidence. Indeed, anecdotal evidence may even be less probative than statistical
evidence in the context of proving discriminatory patterns or practices.157
The Court concluded its discourse on the potency of anecdotal evidence in the absence of a
statistical showing of disparity by observing that “rarely, if ever, can such evidence show a
systemic pattern of discrimination necessary for the adoption of an affirmative action plan.”158
Two other circuit courts also suggested that anecdotal evidence might be dispositive in rare and
exceptional cases, if ever, while rejecting it in the specific case before them. For example, in
Philadelphia IV, the Third Circuit Court of Appeals noted that the Philadelphia City Council had
“received testimony from at least fourteen minority contractors who recounted personal
experiences with racial discrimination,” which the district court had “discounted” because it
deemed this evidence to be “impermissible” for consideration under Croson.159 The Third Circuit
Court disapproved of the district court’s actions because, in its view, the Court’s rejection of this
evidence betrayed the Court’s role in disposing of a motion for summary judgment.160 The Court
stated:
Given Croson’s emphasis on statistical evidence, even had the district court
credited the City’s anecdotal evidence, we do not believe this amount of anecdotal
evidence is sufficient to satisfy strict scrutiny [quoting Coral, supra]. Although
anecdotal evidence alone may, in an exceptional case, be so dominant or pervasive
that it passes muster under Croson, it is insufficient here.161
The District of Columbia Circuit Court echoed the Ninth Circuit’s acknowledgment of the rare
case in which anecdotal evidence is singularly potent in O’Donnell Construction v. District of
Columbia.162 The Court found that, in the face of conflicting statistical evidence, the anecdotal
evidence there was not sufficient:
It is true that in addition to statistical information, the Committee received
testimony from several witnesses attesting to problems they faced as minority
157 Coral Constr., 941 F.2d at 919.
158 Id.
159 Philadelphia IV, 6 F.3d at 1002.
160 Philadelphia IV, 6 F.3d at 1003.
161 Philadelphia IV, 6 F.3d at 1003.
162 963 F. 2d 420, 427 (D.C. Cir. 1992).
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contractors. Much of the testimony related to bonding requirements and other
structural impediments any firm would have to overcome, no matter what the race
of its owners. (internal citation omitted.) The more specific testimony about
discrimination by white firms could not, in itself, support an industry-wide remedy
(internal quotes and citation omitted). Anecdotal evidence is most useful as a
supplement to strong statistical evidence—which the Council did not produce in
this case.163
The Eleventh Circuit in Dade County II is also in accord. In applying the “clearly erroneous”
standard to its review of the district court’s decision in Dade County II, it commented that “[t]he
picture painted by the anecdotal evidence is not a good one.”164 However, it held that this was not
the “exceptional case” in which, unreinforced by statistics, the anecdotal evidence was enough.165
In Concrete Works II, the Tenth Circuit Court of Appeals described the anecdotal evidence that is
most compelling as evidence within a statistical context. In approving of the anecdotal evidence
marshaled by the City of Denver in the proceedings below, the Court recognized that “[w]hile a
fact finder should accord less weight to personal accounts of discrimination that reflect isolated
incidents, anecdotal evidence of a municipality’s institutional practices carries more weight due to
the systemic impact that such institutional practices have on market conditions.”166 The Court
noted that the City had provided such systemic evidence.
The Ninth Circuit Court of Appeals has articulated what it deems to be permissible anecdotal
evidence in AGCC II.167 There, the Court approved a “vast number of individual accounts of
discrimination,” which included (1) numerous reports of MBEs denied contracts despite being the
low bidder, (2) MBEs told that they were not qualified, although they were later found to be
qualified when evaluated by outside parties, (3) MBEs refused work even after they were awarded
the contracts as low bidder, and (4) MBEs being harassed by city personnel to discourage them
from bidding on city contracts. On appeal, the City pointed to numerous individual accounts of
discrimination to substantiate its findings that discrimination exists in the city’s procurement
processes, an “old boy’s network” still exists, and racial discrimination is still prevalent within the
San Francisco construction industry.168 Based on AGCC II, it would appear that the Ninth Circuit’s
standard for acceptable anecdotal evidence is more lenient than other Circuits that have considered
the issue.
Taken together, these statements constitute a taxonomy of appropriate anecdotal evidence.
Anecdotal evidence alone may, in exceptional cases, show a systemic pattern of discrimination
163 O’Donnell, 963 F.2d at 427.
164 Dade County II, 122 F.3d at 925.
165 Id. at 926.
166 Concrete Works II, 36 F.3d at 1530.
167 AGCC II, 950 F.2d at 1401.
168 AGCC II, 950 F.2d at 1415.
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necessary for the adoption of an affirmative action plan, but it must be so dominant and pervasive
that it passes muster under the Croson standards.169
Pursuant to Croson and its progeny, case law suggests that, to be optimally persuasive, anecdotal
evidence collectively should satisfy six particular requirements. These requirements are that the
accounts:
• Are gathered from minority contractors, preferably those that are “qualified”170
• Concern specific, verifiable instances of discrimination171
• Involve the actions of governmental officials172
• Involve events within the relevant jurisdiction’s market area173
• Discuss the harm that the improper conduct has inflicted on the businesses in question174
• Collectively reveal that discriminatory exclusion and impaired contracting opportunities
are systemic rather than isolated or sporadic.175
Given that neither Croson nor its progeny identify the circumstances under which anecdotal
evidence alone will carry the day, it is not surprising that none of these cases explicate bright -line
rules specifying the quantity of anecdotal evidence needed to support an MBE program. However,
the foregoing cases provide some guidance by implication. Philadelphia IV makes clear that 14
anecdotal accounts standing alone will not suffice.176 The Court then turned to the statistical
data.177 While the matter is not free of countervailing considerations, 57 accounts, many of which
appeared to be of the type referenced above, were insufficient without statistical data to justify the
program in Coral Construction. Therefore, no court has provided rules on the number of pieces of
anecdotal evidence that is needed in conjunction with statistical evidence to pass constitutional
muster.
The quantum of anecdotal evidence that a court would likely find acceptable will depend on the
proposed remedy. The remedies that are least burdensome to non-targeted groups would likely
require a lesser degree of evidence. Those remedies that are more burdensome on the non-targeted
groups would require a stronger factual basis likely extending to verification.
169 Philadelphia IV, 6 F.3d at 1003. The anecdotal evidence must be “dominant or pervasive.”
170 Philadelphia VI, 91 F.3d at 603.
171 Coral Constr., 941 F.2d at 917-18; but see Concrete Works IV, 321 F.3d at 989 (“There is no merit to [plaintiff’s] argument that the witnesses’
accounts must be verified to provide support for Denver’s burden.”).
172 Croson, 488 U.S. at 509.
173 Coral Constr., 941 F.2d at 925.
174 O’Donnell, 963 F.2d at 427.
175 Coral Constr., 941 F.2d at 919.
176 Philadelphia IV, 6 F.3d. at 1002-03.
177 Philadelphia IV, 6 F.3d. at 1002-03.
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D. Remedial Statutory Scheme
H.B. Rowe Company v. Tippett (“Rowe”) decided in 2010, challenged the constitutionality of the
North Carolina General Assembly’s Statute 136-28.4 (Statute), promulgated in 1983.178 The
Statute set forth a general policy to promote the use of small, minority, physically handicapped,
and women contractors in non-federally funded State construction projects.179 The 1983 Statute
directed North Carolina Department of Transportation (NCDOT) to encourage and promote the
policy.180 Seven years later, in 1990, the Statute was amended to include specific participation
goals on state funded transportation construction contracts for minority- and women-owned
businesses.181
As a result of the amendment, NCDOT created a Minority Business Enterprise and Women
Business Enterprise Program (M/WBE Program) f or non-federally funded highway and bridge
construction contracts.182 In 1991, the constitutionality of the Statute was challenged.183 The Court
ruled in favor of the plaintiff, stating that, in order to implement race-conscious measures to
remedy discrimination, the governmental entity must identify with “some specificity” the racial
discrimination it seeks to remedy.184 As a result of the challenge, NCDOT suspended its M/WBE
program in 1991.185
In 1993, NCDOT commissioned a disparity study on state-funded transportation construction
contracts.186 The study determined that minority and women subcontractors were underutilized at
a statistically significant level and the M/WBE Program was re-implemented.187 In 1998, the North
Carolina General Assembly again commissioned an update to the 1993 study.188 The 1998 update
study concluded that minority- and women-owned businesses continued to be underutilized in
state-funded road construction contracts.189
In 2002, H.B. Rowe Company was denied a NCDOT contract because the company’s bid included
6.6 percent women subcontractor participation and no minority subcontractor participation.190
178 Rowe, 615 F.3d at 236.
179 Rowe, 615 F.3d at 236.
180 Id.
181 Id.
182 Id.
183 Id. at 237; see Dickerson Carolina, Inc. v. Harrelson , 114 N.C. App. 693 (1994).
184 Rowe, 615 F.3d at 237 (citing Croson, 488 U.S. at 504).
185 Id.
186 Id.
187 Rowe, 615 F.3d at 237.
188 Id.
189 Id.
190 Id.
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NCDOT claimed that H.B. Rowe Company failed to meet the good faith effort requirements of
the M/WBE program.191 A third study was commissioned in 2004 to again study minority and
women contractor participation in the State’s highway construction industry.192 In 2006, relying
on the 2004 study, the North Carolina General Assembly amended Statute 136-28.4.193 The
principal modifications were:
• Remedial action should be taken only when there is a strong basis in evidence of ongoing
effects of past or present discrimination that prevent or limit disadvantaged minority- and
women-owned businesses from participating as subcontractors in State-funded projects.
• The minority/women classification was limited to those groups that suffered
discrimination.
• A disparity study should be performed every five years to respond to changing conditions.
• Inclusion of a sunset provision.194
First, the Court considered if the statutory scheme as it relates to minorities survives the strict
scrutiny standard. The Fourth Circuit Court of Appeals reviewed the statistical evidence detailed
in the 2004 disparity study to determine if the statutory scheme was based on strong statistical
evidence to implement race-conscious subcontractor goals.195
The statistical evidence was also examined to determine if the statute’s definition of minorities
was over-inclusive by including minority groups that did not suffer discrimination pursuant to the
statistical results of the 2004 disparity study.196
The Court did not consider if the statistical methodology employed in the 2004 disparity study was
sufficient to support a compelling state interest. Rather, the Court accepted the disparity index as
the measure by which to determine the statistical significance of the underutilization of minorities
in the State’s subcontracts.197 The methodology used in the 2004 disparity study calculated a
disparity at 0.05 confidence level.198 A statistical calculation is significant at the 0.05 confidence
level because the probability of that result occurring by chance is 5 percent or less.199 The 0.05
191 Id.
192 Id. At 238.
193 Rowe, 615 F.3d at 238.
194 Id. at 238-39.
195 Rowe, 615 F.3d at 239.
196 Rowe, 615 F.3d at 239.
197 Id. at 243-44.
198 Id. at 244.
199 Id. at 261 n. (citing SHERRI L. JACKSON, RESEARCH METHODS AND STATISTICS: A CRITICAL THINKING APPROACH 168 -
69 (3d ed. 2006) (noting that the .05 confidence level is generally used in the social sciences as indication that the result was produced as a
consequence of an external influence)).
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confidence level is used in social and other sciences as a marker of when a result is a product of
some external influence, rather than ordinary variation or sampling error.200
While the circuit court found that “the study itself sets out the standard by which one could
confidently conclude that discrimination was at work[,]” the standard was not followed in the
State’s statutory scheme.201 The statistical evidence in the 2004 disparity study demonstrated that
African American and Native American subcontractors were underutilized at a disparity index of
less than 80 and that Hispanic American and Asian American subcontractors also were
underutilized, but not at a 0.05 confidence level.202 The 2004 Study determined that the
underutilization of Hispanic American and Asian American contractors was not statistically
significant.
Therefore, the only statutory scheme ruled narrowly tailored to achieve the State’s compelling
interest was the one related to African American and Native American subcontractors. The
statutory scheme pertaining to Hispanic American and Asian American subcontractors was
deemed unconstitutional.203 Thus, the State only provided a strong basis in evidence for the
minority subcontractor participation goals pertaining to African American and Native American
subcontractors.
Second, the Court considered if the statutory scheme as it relates to women survives the
intermediate scrutiny standard. The evidence demonstrated that the State’s prime contractors
“substantially over-utilized” women-owned businesses on public road construction projects.204
The 2004 disparity study calculated the overutilization of women subcontractors as statistically
significant at a 0.05 confidence level, which the Court alternatively described as the 95%
confidence level.205 The circuit court further noted that the private sector evidence was insufficient
to overcome the strong evidence of overutilization.206 Consequently, the circuit court determined
that the evidence in the 2004 disparity study did not provide “exceedingly persuasive justification”
to include women-owned businesses in gender-based remedies.207
In light of the Rowe decision, caution should be exercised when determining which minority or
gender group is appropriate for race-conscious or gender-conscious remedies. For an MBE
program to be narrowly tailored there must be a statistical finding of underutilization of minority
subcontractors. When the underutilization of a minority group is not found to be statistically
significant, the minority group should not be included in race-conscious remedies.
200 Rowe, 615 F.3d at 261 n. 12 (citing EARL BABBIE, THE PRACTICE OF SOCIAL RESEARCH 483 (11th ed. 2007)).
201 Id. at 261.
202 Id. at 245.
203 Id. at 254.
204 Rowe, 615 F.3d at254.
205 Id. at 254-55.
206 Id. at 255.
207 Id.
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The intermediate scrutiny standard for gender classifications can be met with statistical evidence
of underutilization that is not statistically significant. However, this does not apply when there is
demonstrated overutilization. Women-owned businesses should be considered for gender-based
remedies when the statistical evidence demonstrates that the overutilization is not statistically
significant.
V. Consideration of Race-Neutral Options
A remedial program must address the source of the disadvantage faced by minority businesses. If
it is found that race discrimination places MBEs at a competitive disadvantage, an MBE program
may seek to counteract the situation by providing MBEs with a counterbalancing advantage.208 An
MBE program cannot stand if the sole barrier to M/WBE participation is a barrier that is faced by
all new businesses, regardless of ownership.209 If the evidence demonstrates that the sole barrier
to M/WBE participation is that M/WBEs disproportionately lack capital or cannot meet bonding
requirements, then only a race-neutral program of financing for all small firms would be
justified.210 In other words, if the barriers to minority participation are race-neutral, then the
program must be race-neutral.
The requirement that race-neutral measures be considered does not mean that they must be
exhausted before race-conscious remedies can be employed. The Supreme Court explained that
although “narrow tailoring does not require exhaustion of every conceivable race-neutral
alternative,” it “does require serious, good faith consideration of workable race-neutral alternatives
that will achieve ... diversity[.]”211
If the barriers appear race related but are not systemic, then the remedy should be aimed at the
specific arena in which exclusion or disparate impact has been found as detailed above in Section
IV. If the evidence shows that in addition to capital and bonding requirements, which are race-
neutral, MBEs also face race discrimination in the awarding of contracts, then a race-conscious
program will stand, as long as it also includes race-neutral measures to address the capital and
bonding barriers.212
The Ninth Circuit Court of Appeals in Coral Construction ruled that there is no requirement that
an entity exhaust every possible race-neutral alternative.213 Instead, an entity must make a serious,
good faith consideration of race-neutral measures in enacting an MBE program. Thus, in assessing
MBE utilization, it is imperative to examine barriers to MBE participation that go beyond “small
208 AGCC II, 950 F.2d at 1417.
209 Croson, 488 U.S. at 508.
210 Id. at 507.
211 Grutter v. Bollinger, 539 U.S. 306, 339 (2003).
212 Croson, 488 U.S. at 507 (upholding MBE program where it operated in conjunction with race -neutral measures aimed at assisting all small
businesses).
213 Coral Constr., 941 F.2d at 923.
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business problems.” The impact on the distribution of contract programs that have been
implemented to improve MBE utilization should also be measured.214
VI. Conclusion
The decision of the United States Supreme Court in the Croson case changed the legal landscape
for local governments’ race and gender-conscious public contracting programs. In Croson, the
United States Supreme Court modified the authority of a local government to use local funds to
institute remedial race-conscious public contracting programs. This chapter has examined what
Croson and its progeny require for MSD to institute a constitutional race or gender -conscious
public contracting program.
Consistent with the case law, the race and gender-conscious recommendations for MSD’s MWBE
Program presented in this Update Disparity Study are based on a constitutionally sound factual
predicate.
The disparity findings of MSD’s utilization of available MWBEs are presented in Chapter 6:
Prime Contract Disparity Analysis and Chapter 7: Subcontract Disparity Analysis.
214 Dade County II, 122 F.3d at 927. At the same time, the Eleventh Circuit’s caveat in Dade County should be kept in mind: “Supreme Court
decisions teach that a race-conscious remedy is not merely one of many equally acceptable medications that a government may use to treat
race-based problems. Instead, it is the strongest of medicines, with many potentially harmful side-effects, and must be reserved to those severe
cases that are highly resistant to conventional treatment.” For additional guidance, see supra section II, Standard of Review for the discussion
of narrow tailoring in Concrete Works IV, Adarand, County of Cook, and City of Chicago.
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VII. List of Authorities
Cases Pages
Adarand Constructors, Inc. v. Slater,
228 F.3d 1147 (10th Cir. 2000) ……………………………………….…………………15
Armour v. City of Indianapolis, Ind.,
132 S. Ct. 2073 (2012) ……………………………………………...………………...…12
Associated Gen. Contractors of Cal .v. City & Cnty. of San Francisco (“AGCC I”),
813 F.2d 922 (9th Cir. 1987) .…..………………………………………………...11, 12, 13
Associated Gen. Contractors of America v. Cal. Dep’t of Transp. (AGC I), Hearing
Transcript (Hr’g Tr.) 1:1-58:2 (March 23, 2011)…………………….…………………… 35
Associated Gen. Contractors v. Coal. for Econ. Equity (“AGCC II”),
950 F.2d 1401 (9th Cir. 1991) ……………………………………………………….passim
Associated Gen. Contractors of Ohio, Inc. v. Drabik (“Drabik”),
214 F.3d 730 (6th Cir. 2000) ………………………………………………………..3, 5, 24
Associated Gen. Contractors v. New Haven,
791 F. Supp. 941 (D. Conn. 1992) ………………………………………………………..14
Brunet v. City of Columbus,
1 F.3d 390 (6th Cir. 1993) ………………………………………………………………..10
Builders Ass’n of Greater Chi. v. City of Chi.,
298 F. Supp. 2d 725 (N.D. Ill. 2003) ……………………………………………………..18
Builders Ass’n of Greater Chicago v. Cnty. of Cook,
256 F.3d 642 (7th Cir. 2001) ……………………………………………………………..12
City of Richmond v. J.A. Croson Co. (“Croson”),
488 U.S. 469 (1989) …………………………………………………………………passim
Concrete Works of Colo., Inc. v. City & Cnty. of Denver (“Concrete Works I”),
823 F. Supp. 821 (D. Colo. 1993) …………………………………………………….17, 21
Concrete Works of Colo., Inc. v. City & Cnty. of Denver (“Concrete Works II”),
36 F.3d 1513 (10th Cir. 1994) ……………………………………………………….passim
Concrete Works of Colo., Inc. v. City & Cnty. of Denver (“Concrete W orks III”),
86 F. Supp. 2d 1042 (D. Colo. 2000) …………………………………………………….17
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Concrete Works of Colo., Inc. v. City & Cnty. of Denver (“Concrete Works IV”),
321 F.3d 950 (10th Cir. 2003) ……………………………………………………….passim
Cone Corp. v. Hillsborough Cnty.,
908 F.2d 908 (11th Cir. 1990) ………………………………………………………..21, 27
Contractors Ass’n of E. Pa. v. City of Philadelphia (“Philadelphia IV”),
6 F.3d 990 (3d Cir. 1993) ……………………………………………………………passim
Contractors Ass’n of E. Pa. v. City of Philadelphia (“Philadelphia V”),
893 F. Supp. 419 (E.D. Pa.1995) …………………………………………………………13
Contractors Ass’n of E. Pa v. City of Philadelphia (“Philadelphia VI”),
91 F.3d 586 (3rd Cir. 1996) …………………………………………………………passim
Coral Constr. Co. v. King Cnty.,
941 F.2d 910 (9th Cir. 1991) ………………………………………………………..passim
Dickerson Carolina, Inc. v. Harrelson,
114 N.C. App. 693 (1994) ………………………………………………………………..31
Doe 1 v. Lower Merion Sch. Dist.,
689 F. Supp. 2d 742 (E.D. Pa. 2010) …………………………………………………….13
EEOC v. Am. Nat’l Bank,
652 F.2d 1176 (4th Cir. 1981) ……………………………………………………………26
Eng’g Contractors Ass’n v. Metro. Dade Cnty. (“Dade County I”),
943 F. Supp. 1546 (S.D. Fla. 1996) ………………………………………………….passim
Eng’g Contractors Ass’n v. Metro. Dade Cnty. (“Dade County II”),
122 F.3d 895 (11th Cir. 1997) ………………………………………………………passim
Ensley Branch N.A.A.C.P. v. Seibels,
31 F.3d 1548 (11th Cir. 1994) ………………………………………………………..11, 12
Grutter v. Bollinger,
539 U.S. 306 (2003) ……………………………………………………………………...35
Hayes v. N. State Law Enforcement Officers Ass’n,
10 F.3d 207 (4th Cir. 1993) ………………………………………………………………12
Hazelwood Sch. Dist. v. United States,
433 U.S. 299 (1977) ………………………………………………………………….20, 23
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H.B. Rowe Co. v. N.C. Dep’t of Transp. (“Rowe”),
615 F.3d 233 (4th Cir. 2010) ………………………………………………………..passim
Hershell Gill Consulting Eng’rs, Inc. v. Miami-Dade Cnty.,
333 F. Supp. 2d 1305 (S.D. Fla. 2004) …………………………………………………...16
Int’l Bhd. of Teamsters v. United States (“Teamsters”),
431 U.S. 324 (1977) …………………………………………………………………passim
Johnson v. Board of Regents of the University of Georgia,
263 F.3d 1234, 1244 (11th Cir. 2001) ……………………………………………………16
Lakeside Roofing Company v. State of Missouri, et al.,
2012 WL 709276 (E.D.Mo. Mar. 5, 2012) …………………………………………..12, 13
League of United Latin Am. Citizens v. Santa Ana,
410 F. Supp. 873 (C.D. Cal. 1976) ……………………………………………………….26
Mich. Rd. Builders Ass’n v. Milliken,
834 F.2d 583 (6th Cir. 1987) …………………………………………………………….10
Midwest Fence Corp. v. U.S. Dep't of Transportation,
84 F. Supp. 3d 705 (N.D. Ill. 2015)…………………………………………………………….38
Miss. Univ. for Women v. Hogan,
458 U.S. 718 (1982) ……………………………………………………………………...10
Monterey Mech. Co. v. Pete Wilson et al.,
125 F.3d 702 (9th Cir. 1997) …………………………………………………………….19
Northern Contracting, Inc. v. Illinois Department of Transportation,
473 F.3d 715 (7th Cir. 2007)……………………………………………………………………………..33
N. Shore Concrete &Ass’n v. City of N.Y.,
1998 U.S. Dist. LEXIS 6785 (EDNY 1998) ………………………………………….…19
O’Donnell Constr. Co. v. D.C.,
963 F.2d 420 (D.C. Cir. 1992) ……………………………………………………….29, 30
Ohio Contractors Ass’n v. Keip,
1983 U.S. App. LEXIS 24185 (6th Cir. 1983) ………………………………………….5, 24
Reynolds v. Sheet Metal Workers, Local 102,
498 F. Supp. 952 (D. D.C. 1980) ………………………………………………………..26
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Schlesinger v. Ballard,
419 U.S. 498 (1975) …………………………………………………………………….....4
Shaw v. Hunt,
517 U.S. 899 (1996) ……………………………………………………………………...11
United States v. Virginia,
518 U.S. 515 (1996) ………………………………………………………………….10, 11
W. States Paving Co. v. Washington State Dep’t of Transp.,
407 F.3d 983 (9th Cir. 2005)…………………………………………………………………… 33
W.H. Scott Constr. Co. v. City of Jackson,
199 F.3d 206 (1999) ……………………………………………………………………..19
Wygant v. Jackson Bd. of Educ.,
476 U.S. 267 (1986) ……………………………………………………………....14, 15 27
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CHAPTER 2: Prime Contractor Utilization
Analysis
I. Introduction
This chapter documents the Metropolitan St. Louis Sewer District’s (MSD) utilization of Minority
and Woman-owned Business Enterprise (MWBE) and non-minority male-owned business
enterprise (non-MWBE) prime contractors by ethnicity, gender, and industry during the study
period of January 1, 2013 to December 31, 2017. MSD’s contracts examined were classified into
four industries that are described below—building construction, non-building construction,
engineering professional services, and purchases and other services.
• Building Construction: erection, alteration, or improvement of public structures and
buildings (vertical construction) that include multiple trades. Routine maintenance of
existing structures, buildings, or real property is not included. 215
• Non-Building Construction: demolition, below ground sewer construction (horizontal
construction), and major repair. 216
• Engineering Professional Services: services rendered by an independent consultant with
professional knowledge in a profession or vocation that is founded on prolonged and
specialized intellectual training that enables an individual to provide advice, opinions,
and/or recommendations.
• Purchases and Other Services: supplies, materials, equipment, and contractual services.
Table 2.1 lists the eight race and gender groups in which the prime contractors are classified.
215 MSD Purchasing Policy 3-2018, p. 6.
216 MSD Purchasing Policy 3-2018, p. 8.
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Table 2.1: Business Ethnic and Gender Groups
Ethnicity and Gender Category Definition
African Americans Businesses owned by male and female African
Americans
Asian Americans Businesses owned by male and female Asian
Americans
Hispanic Americans Businesses owned by male and female Hispanic
Americans
Native Americans Businesses owned by male and female Native
Americans
Caucasian Females Businesses owned by Caucasian females
Non-minority Male-owned Businesses
Businesses owned by Caucasian males, and
businesses that could not be identified as minority
or female-owned217
Minority-owned Businesses
Businesses owned by male and female African
Americans, Asian Americans, Hispanic
Americans, and Native Americans
Woman-owned Businesses Businesses owned by females
II. Prime Contract Data Sources
The prime contract data consist of contract records extracted from MSD’s Oracle financial
management system. The contract payments were issued from January 1, 2013 to December 31,
2017. The prime contract data were normalized to create a unique prime contract dataset for MSD’s
contracts. The prime dataset was normalized to: (1) define each field in the dataset and (2)
determine the relationship between the fields. The normalized prime dataset was scrubbed to
remove duplicates, contracts awarded outside the study period, claims/reimbursements, payments
to government entities, non-profits, and utility companies. Each unique record was defined by
either a project number, contract number, PN number, or purchase order number.
Purchases of proprietary commodities, as well as the maintenance and service of the proprietary
commodities, were also excluded. Each prime contract was classified into one of the four
industries—building construction, non-building construction, engineering professional services,
and purchases and other services. The assignment of industry classifications was reviewed and
approved by MSD.
A number of steps were taken to determine the ethnicity and gender of each prime contractor. The
initial step determined whether the contractor was certified by a local certifying agency. When
217 See Section II: Prime Contract Data Sources for the methodology employed to identify the ethnicity and gender of MSD’s utilized prime
contractors.
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available, the ethnicity and gender of the certified firm’s business owner was derived from the
certification record. Additional sources were used to determine the ethnicity and gend er of the
utilized, non-certified contractors. These included chambers of commerce directories, trade
organization membership lists, internet research, and contractor surveys. Internet research was
conducted to examine the business’ website, social media, digital media, and business listings to
determine the business owner’s ethnicity and gender. A contractor survey solicited ethnicity and
gender information directly from the businesses. Prime contractors whose owner’s ethnicity and
gender could not be verified as minority or female-owned were classified as non-MWBE. The
non-MWBE category also included publicly-traded corporations, employee-owned businesses,
and fifty-fifty partnerships in which neither partner was a minority nor a woman.
III. Thresholds for Analysis
MSD’s prime contracts awarded in each industry are analyzed at three size thresholds: (1) all prime
contracts, (2) informal prime contracts, as defined by MSD Purchasing Policy 3-2018 as under
$25,000, and (3) formal prime contracts valued at $500,000 and under.
A. Informal Threshold
The threshold for the analysis of MSD’s informal prime contracts is defined by industry, pursuant
to MSD’s Purchasing Policy 3-2018. The informal thresholds listed in Table 2.2 apply to the non-
building construction, engineering professional services, and purchases and other services.
Table 2.2: Informal Contract Thresholds by Industry
Industry Informal Contract Threshold
Non-Building Construction Under $25,000
Engineering Professional Services Under $25,000
Purchases and Other Services Under $25,000
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B. Formal Contract Threshold
The formal contract threshold, as defined in MSD’s purchasing policy, is $25,000 and greater.
However, to ensure that the disparity analysis was not distorted by the presence of prime contracts
that required significant capacity to perform, the formal contract size threshold was set at $500,000
and the large prime contracts were removed.
During the study period, 90.14% of MSD’s contract awards were less than $500,000. These
contracts were received by non-minority females, non-minority males, minority females, and
minority males. Only 3.06% of MSD’s prime contracts were valued $3,000,000 and greater. No
minority females and 0.07% of minority males received contracts valued $3,000,000 and over.
Table 2.3 lists the formal prime contract threshold for each of the four industries analyzed.
Table 2.3: Formal Contract Threshold by Industry
Industry Formal Contract Threshold
Building Construction218 From $25,000 to $8,270,000
Non-Building Construction From $25,000 to $500,000
Engineering Professional Services From $25,000 to $500,000
Purchases and Other Services From $25,000 to $500,000
IV. Prime Contractor Utilization
A. All Prime Contractors
As shown in Table 2.4, MSD issued 2,749 prime contracts from January 1, 2013 to December 31,
2017. The total prime contracts awarded included seven for building construction, 890 for non-
building construction, 299 for engineering professional services, and 1,553 for purchasing and
other services. The payments made by MSD during the study period totaled $1,238,982,577 for all
2,749 prime contracts. Payments included $30,684,903 for building construction, $917,808,132
for non-building construction, $279,103,076 for engineering professional services, and
$11,386,466 for purchases and other services.
218 MSD did not award any building construction contracts valued under $500,000.
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Table 2.4: Total Prime Contracts and Dollars Expended
All Industries, January 1, 2013 to December 31, 2017
Industry Total Number
of Contracts
Total
Dollars Expended
Building Construction219 7 $30,684,903
Non-Building Construction 890 $917,808,132
Engineering Professional Services 299 $279,103,076
Purchases and Other Services 1,553 $11,386,466
Total Expenditures 2,749 $1,238,982,577
B. Distribution of Prime Contract Dollars
While the disparity analysis will not include contracts greater than $500,000, all prime contracts,
including the large contracts removed from the disparity analysis, are counted in the highly used
data presented in this section. MSD awarded a significant number of its prime contract dollars to
a few vendors. The “highly used” analysis shows the businesses that received approximately 70%
of the total contract dollars awarded in each industry. The “most highly used” analysis shows a
subset of the “highly used” businesses that received approximately 50% of the total contract dollars
in each industry. The most highly used businesses received the largest percentage of the contract
dollars in their industry. The percent of the prime contract dol lars awarded to the highly used
contractors illustrates the fact that the award of most of MSD’s subcontracts was controlled by a
few businesses.
C. Highly Used Building Construction Prime Contractors
MSD awarded a total of seven building construction prime contracts during the study period. As
listed in Table 2.5, seven building construction prime contracts were received by five businesses
for a total of $30,584,903.
Table 2.5: Building Construction Prime Contracts
Total Prime Contracts 7
Total Utilized Businesses 5
Total Expenditures $30,684,903
219 There were too few contracts to analyze the highly used contractors in the building construction industry.
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Table 2.6 lists the ethnicity and gender of the most highly used building construction prime
contractor, who received the most building construction prime contract dollars. The one contractor
received $26,596,550, or 86.68%, of the total building construction prime contract dollars. The
most highly used prime contractor was a non-minority male-owned business. The contracts
received by this business ranged from $3,272,855 to $19,087,150.
Table 2.6: Most Highly Used Building Construction Prime Contractor
Ethnicity/
Gender
Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
Non-minority Male $26,596,550 86.68% 3 42.86%
D. Highly Used Non-Building Construction Prime Contractors
MSD awarded a total of 890 non-building construction prime contracts during the study period.
As listed in Table 2.7, 890 non-building construction prime contracts were received by 102
businesses.
Table 2.7: Non-Building Construction Prime Contracts
Total Prime Contracts 890
Total Utilized Businesses 102
Total Expenditures $917,808,132
Table 2.8 lists the distribution of non-building construction prime contracts by the number of
businesses. Five of the 102 businesses received $637,575,775, or 69.47%, of the total non-building
construction prime contract dollars. The findings show that a small group of prime contractors
received a majority of non-building construction prime contract dollars spent by MSD.
Table 2.8: Non-Building Construction Prime Contracts
Distributed by Number of Businesses
Businesses Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
5 Highly Used Businesses $637,575,775 69.47% 179 20.11%
97 Businesses $280,232,357 30.53% 711 79.89%
102 Total Businesses $917,808,132 100.00% 890 100.00%
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Table 2.9 lists the ethnicity and gender of the most highly used non-building construction prime
contractors, who received approximately 50% of non-building construction prime contract dollars.
The two most highly used prime contractors were non-minority male-owned businesses. The
contracts received by these two businesses ranged from $3,750 to $123,350,000.
Table 2.9: Top Two Most Highly Used Non-Building Construction Prime Contractors
Ethnicity/
Gender
Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
Non-minority Males $439,386,018 47.87% 81 9.10%
E. Highly Used Engineering Professional Services Prime
Contractors
MSD awarded a total of 299 engineering professional services prime contracts during the study
period. As listed in Table 3.10, 299 engineering professional services prime contracts were
received by 55 businesses.
Table 2.10: Engineering Professional Services Prime Contracts
Total Prime Contracts 299
Total Utilized Businesses 55
Total Expenditures $279,103,076
Table 2.11 lists the distribution of MSD engineering professional services prime contracts by the
number of businesses. Five of the 55 businesses received $195,845,510, approximately 70% of the
total engineering professional services prime contract dollars. The findings show that a small group
of prime contractors received a majority of the engineering professional services prime contract
dollars spent by MSD.
Table 2.11: Engineering Professional Services Prime Contracts Distributed by
Number of Businesses
Businesses Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
5 Highly Used Businesses $195,845,510 70.17% 13 4.35%
50 Businesses $83,257,566 29.83% 286 95.65%
55 Total Businesses $279,103,076 100.00% 299 100.00%
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Table 2.12 lists the ethnicity and gender of the most highly used engineering professional services
prime contractors, who received approximately 50% of the engineering professional services
prime contract dollars. The three most highly used prime contractors were non-minority male-
owned businesses. The contracts received by these three businesses ranged from $500,000 to
$56,859,170.
Table 2.12: Top Three Most Highly Used Engineering Professional Services
Prime Contractors
Ethnicity/
Gender
Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
Non-minority Males $148,007,027 53.03% 6 2.01%
F. Highly Used Purchases and Other Services Prime Contractors
MSD awarded a total of 1,553 purchases and other services prime contracts during the study
period. As listed in Table 2.13, MSD’s 1,553 purchases and other services prime contracts were
received by 52 businesses.
Table 2.13: Purchases and Other Services Prime Contracts
Total Prime Contracts 1,553
Total Utilized Businesses 52
Total Expenditures $11,386,466
Table 2.14 lists the distribution of MSD purchases and other services prime contracts by the
number of businesses. Seven of the 52 businesses received $7,955,651, approximately 70% of the
total purchases and other services prime contract dollars. The findings show that a small group of
prime contractors received a majority of MSD’s purchases and other services prime contract
dollars.
Table 2.14: Purchases and Other Services Prime Contracts Distributed by
Number of Businesses
Businesses Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
7 Highly Used Businesses $7,955,651 69.87% 693 44.62%
45 Businesses $3,430,815 30.13% 860 55.38%
52 Total Businesses $11,386,466 100.00% 1,553 100.00%
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Table 2.15 lists the ethnicity and gender of the four most highly used purchases and other services
prime contractors, who received approximately 50% of the purchases and other services prime
contract dollars. The four most highly used prime contractors were African American, Caucasian
female, and non-minority male-owned businesses. The contracts received by these four businesses
ranged from $52 to $1,255,624.
Table 2.15: Top Four Highly Used Purchases and Other Services Prime Contractors
Ethnicity/
Gender
Total
Dollars
Percent
of Dollars
Number of
Contracts
Percent of
Contracts
African Americans $1,772,039 29.65% 20 2.97%
Caucasian Females $2,172,217 36.35% 651 96.73%
Non-Minority Males $2,032,040 34.00% 2 0.30%
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G. All Prime Contracts by Industry
1. Building Construction Prime Contract Utilization: All Contracts
Table 2.16 summarizes all prime contract dollars expended by MSD on building construction
prime contracts. Minority Business Enterprises (MBEs) received 1.68% of the building
construction prime contract dollars; Woman Business Enterprises (WBEs) received none; and non-
minority male-owned businesses (non-MWBEs) received 98.32%.
African Americans received 1, or 14.29%, of the building construction prime contracts awarded
during the study period, representing $515,449, or 1.68%, of the building construction prime
contract dollars.
Asian Americans received none of the building construction prime contracts during the study
period.
Hispanic Americans received none of the building construction prime contracts during the study
period.
Native Americans received none of the building construction prime contracts during the study
period.
Caucasian Females received none of the building construction prime contracts during the study
period.
Non-minority Males received 6, or 85.71%, of the building construction prime contracts awarded
during the study period, representing $30,169,453, or 98.32%, of the building construction prime
contract dollars.
Minority-owned Businesses received 1, or 14.29%, of the building construction prime contracts
awarded during the study period, representing $515,449, or 1.68%, of the building construction
prime contract dollars.
Woman-owned Businesses received none of the building construction prime contracts during the
study period.
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Table 2.16: Building Construction Prime Contract Utilization
All Contracts, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 1 14.29%$515,449 1.68%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 0 0.00%$0 0.00%
Non-minority Males 6 85.71%$30,169,453 98.32%
TOTAL 7 100.00%$30,684,903 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 0 0.00%$0 0.00%
African American Males 1 14.29%$515,449 1.68%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 0 0.00%$0 0.00%
Non-minority Males 6 85.71%$30,169,453 98.32%
TOTAL 7 100.00%$30,684,903 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 1 14.29%$515,449 1.68%
Woman Business Enterprises 0 0.00%$0 0.00%
Minority and Women
Ethnicity
Ethnicity and Gender
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2. Non-Building Construction Prime Contract Utilization: All Contracts
Table 2.17 summarizes all prime contract dollars expended by MSD on non-building construction
prime contracts. MBEs received 2.88% of the non-building construction prime contract dollars;
WBEs received 3.90%; and non-MWBEs received 93.75%.
African Americans received 131, or 14.72%, of the non-building construction prime contracts
awarded during the study period, representing $14,788,708 or 1.61%, of the non-building
construction prime contract dollars.
Asian Americans received none of the non-building construction prime contracts awarded during
the study period.
Hispanic Americans received 16, or 1.80%, of the non-building construction prime contracts
awarded during the study period, representing $11,056,917, or 1.20%, of the non-building
construction prime contract dollars.
Native Americans received 4, or 0.45%, of the non-building construction prime contracts awarded
during the study period, representing $600,616, or 0.07%, of the non-building construction prime
contract dollars.
Caucasian Females received 68, or 7.64%, of the non-building construction prime contracts
awarded during the study period, representing $30,931,337, or 3.37%, of the non-building
construction prime contract dollars.
Non-minority Males received 671, or 75.39%, of the non-building construction prime contracts
awarded during the study period, representing $860,430,552, or 93.75%, of the non-building
construction prime contract dollars.
Minority-owned Businesses received 151, or 16.97%, of the non-building construction prime
contracts awarded during the study period, representing $26,446,242, or 2.88%, of the non-
building construction prime contract dollars.
Woman-owned Businesses received 105, or 11.80%, of the non-building construction prime
contracts awarded during the study period, representing $35,818,051, or 3.90%, of the non-
building construction prime contract dollars.
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Table 2.17: Non-Building Construction Prime Contract Utilization
All Contracts, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 131 14.72%$14,788,708 1.61%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 16 1.80%$11,056,917 1.20%
Native Americans 4 0.45%$600,616 0.07%
Caucasian Females 68 7.64%$30,931,337 3.37%
Non-minority Males 671 75.39%$860,430,552 93.75%
TOTAL 890 100.00%$917,808,132 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 37 4.16%$4,886,714 0.53%
African American Males 94 10.56%$9,901,995 1.08%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 16 1.80%$11,056,917 1.20%
Native American Females 0 0.00%$0 0.00%
Native American Males 4 0.45%$600,616 0.07%
Caucasian Females 68 7.64%$30,931,337 3.37%
Non-minority Males 671 75.39%$860,430,552 93.75%
TOTAL 890 100.00%$917,808,132 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 151 16.97%$26,446,242 2.88%
Woman Business Enterprises 105 11.80%$35,818,051 3.90%
Minority and Women
Ethnicity
Ethnicity and Gender
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3. Engineering Professional Services Prime Contract Utilization: All
Contracts
Table 2.18 summarizes all contract dollars expended by MSD on engineering professional services
prime contracts. MBEs received 9.15% of the engineering professional services prime contract
dollars; WBEs received 1.89%; and non-MWBEs received 89.75%.
African Americans received 206, or 68.90%, of the engineering professional services prime
contracts awarded during the study period, representing $25,401,551, or 9.10%, of the engineering
professional services prime contract dollars.
Asian Americans received none of the engineering professional services prime contracts awarded
during the study period.
Hispanic Americans received 1, or 0.33%, of the engineering professional services prime
contracts awarded during the study period, representing $125,000, or 0.04%, of the engineering
professional services prime contract dollars.
Native Americans received none of the engineering professional services prime contracts awarded
during the study period.
Caucasian Females received 11, or 3.68%, of the engineering professional services prime
contracts awarded during the study period, representing $3,088,866, or 1.11%, of the engineering
professional services prime contract dollars.
Non-minority Males received 81, or 27.09%, of the engineering professional services prime
contracts awarded during the study period, representing $250,487,660, or 89.75%, of the
engineering professional services prime contract dollars.
Minority-owned Businesses received 207, or 69.23%, of the engineering professional services
prime contracts awarded during the study period, representing $25,526,551, or 9.15%, of the
engineering professional services prime contract dollars.
Woman-owned Businesses received 206, or 68.90%, of the engineering professional services
prime contracts awarded during the study period, representing $5,272,002, or 1.89%, of the
engineering professional services prime contract dollars.
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Table 2.18: Engineering Professional Services Prime Contract Utilization
All Contracts, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 206 68.90%$25,401,551 9.10%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 1 0.33%$125,000 0.04%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 11 3.68%$3,088,866 1.11%
Non-minority Males 81 27.09%$250,487,660 89.75%
TOTAL 299 100.00%$279,103,076 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 195 65.22%$2,183,137 0.78%
African American Males 11 3.68%$23,218,414 8.32%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 1 0.33%$125,000 0.04%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 11 3.68%$3,088,866 1.11%
Non-minority Males 81 27.09%$250,487,660 89.75%
TOTAL 299 100.00%$279,103,076 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 207 69.23%$25,526,551 9.15%
Woman Business Enterprises 206 68.90%$5,272,002 1.89%
Minority and Women
Ethnicity
Ethnicity and Gender
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Prime Contractor Utilization Analysis
4. Purchases and Other Services Prime Contract Utilization: All
Contracts
Table 2.19 summarizes all contract dollars expended by MSD on purchases and other services
prime contracts. MBEs received 20.24% of the purchases and other services prime contract dollars;
WBEs received 29.16%; and non-MWBEs received 50.59%.
African Americans received 26, or 1.67%, of the purchases and other services prime contracts
awarded during the study period, representing $2,095,456, or 18.40%, of the purchases and other
services prime contract dollars.
Asian Americans received 3, or 0.19%, of the purchases and other services prime contracts
awarded during the study period, representing $209,650, or 1.84%, of the purchases and other
services prime contract dollars.
Hispanic Americans received none of the purchases and other services prime contracts awarded
during the study period.
Native Americans received none of the purchases and other services prime contracts awarded
during the study period.
Caucasian Females received 1,057, or 68.06%, of the purchases and other services prime
contracts awarded during the study period, representing $3,320,576, or 29.16%, of the purchases
and other services prime contract dollars.
Non-minority Males received 467, or 30.07%, of the purchases and other services prime contracts
awarded during the study period, representing $5,760,784, or 50.59%, of the purchases and other
services prime contract dollars.
Minority-owned Businesses received 29, or 1.87%, of the purchases and other services prime
contracts awarded during the study period, representing $2,305,106, or 20.24%, of the purchases
and other services prime contract dollars.
Woman-owned Businesses received 1,057, or 68.06%, of the purchases and other services prime
contracts awarded during the study period, representing $3,320,576, or 29.16%, of the purchases
and other services prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.19: Purchases and Other Services Prime Contract Utilization
All Contracts, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 26 1.67%$2,095,456 18.40%
Asian Americans 3 0.19%$209,650 1.84%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 1,057 68.06%$3,320,576 29.16%
Non-minority Males 467 30.07%$5,760,784 50.59%
TOTAL 1,553 100.00%$11,386,466 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 0 0.00%$0 0.00%
African American Males 26 1.67%$2,095,456 18.40%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 3 0.19%$209,650 1.84%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 1,057 68.06%$3,320,576 29.16%
Non-minority Males 467 30.07%$5,760,784 50.59%
TOTAL 1,553 100.00%$11,386,466 100.00%
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 29 1.87%$2,305,106 20.24%
Woman Business Enterprises 1,057 68.06%$3,320,576 29.16%
Minority and Women
Ethnicity
Ethnicity and Gender
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Prime Contractor Utilization Analysis
H. Informal Prime Contracts by Industry
1. Non-Building Construction Prime Contract Utilization: Contracts
Valued under $25,000
Table 2.20 summarizes all contract dollars expended by MSD on non-building construction prime
contracts valued under $25,000. MBEs received 22.68% of the non-building construction prime
contract dollars; WBEs received 13.57%; and non-MWBEs received 66.76%.
African Americans received 52, or 19.92%, of the non-building construction prime contracts
valued under $25,000 awarded during the study period, representing $587,640, or 21.38%, of the
non-building construction prime contract dollars.
Asian Americans received none of the non-building construction prime contracts valued under
$25,000 awarded during the study period.
Hispanic Americans received 2, or 0.77%, of the non-building construction prime contracts valued
under $25,000 awarded during the study period, representing $18,968, or 0.69%, of the non-
building construction prime contract dollars.
Native Americans received 1, or 0.38%, of the non-building construction prime contracts valued
under $25,000 awarded during the study period, representing $16,850, or 0.61%, of the non-
building construction prime contract dollars.
Caucasian Females received 25, or 9.58%, of the non-building construction prime contracts
valued under $25,000 awarded during the study period, representing $290,345, or 10.56%, of the
non-building construction prime contract dollars.
Non-minority Males received 181, or 69.35%, of the non-building construction prime contracts
valued under $25,000 awarded during the study period, representing $1,834,900, or 66.76%, of
the non-building construction prime contract dollars.
Minority-owned Businesses received 55, or 21.07%, of the non-building construction prime
contracts valued under $25,000 awarded during the study period, representing $623,458, or
22.68%, of the non-building construction prime contract dollars.
Woman-owned Businesses received 32, or 12.26%, of the non-building construction prime
contracts valued under $25,000 awarded during the study period, representing $373,073, or
13.57%, of the non-building construction prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.20: Non-Building Construction Prime Contract Utilization
Contracts Valued under $25,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 52 19.92%$587,640 21.38%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 2 0.77%$18,968 0.69%
Native Americans 1 0.38%$16,850 0.61%
Caucasian Females 25 9.58%$290,345 10.56%
Non-minority Males 181 69.35%$1,834,900 66.76%
TOTAL 261 100.00%$2,748,702 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 7 2.68%$82,729 3.01%
African American Males 45 17.24%$504,911 18.37%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 2 0.77%$18,968 0.69%
Native American Females 0 0.00%$0 0.00%
Native American Males 1 0.38%$16,850 0.61%
Caucasian Females 25 9.58%$290,345 10.56%
Non-minority Males 181 69.35%$1,834,900 66.76%
TOTAL 261 100.00%$2,748,702 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 55 21.07%$623,458 22.68%
Woman Business Enterprises 32 12.26%$373,073 13.57%
Minority and Women
Ethnicity
Ethnicity and Gender
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Prime Contractor Utilization Analysis
2. Engineering Professional Services Prime Contract Utilization:
Contracts Valued under $25,000
Table 2.21 summarizes all contract dollars expended by MSD on engineering professional services
prime contracts valued under $25,000. MBEs received 73.49% of the engineering professional
services prime contract dollars; WBEs received 79.38%; and non-MWBEs received 20.62%.
African Americans received 191, or 95.98%, of the engineering professional services prime
contracts valued under $25,000 awarded during the study period, representing $263,868, or
73.49%, of the engineering professional services prime contract dollars.
Asian Americans received none of the engineering professional services prime contracts valued
under $25,000 awarded during the study period.
Hispanic Americans received none of the engineering professional services prime contracts
valued under $25,000 awarded during the study period.
Native Americans received none of the engineering professional services prime contracts valued
under $25,000 awarded during the study period.
Caucasian Females received 2, or 1.01%, of the engineering professional services prime contracts
valued under $25,000 awarded during the study period, representing $21,169, or 5.90%, of the
engineering professional services prime contract dollars.
Non-minority Males received 6, or 3.02%, of the engineering professional services prime contracts
valued under $25,000 awarded during the study period, representing $74,028, or 20.62%, of the
engineering professional services prime contract dollars.
Minority-owned Businesses received 191, or 95.98%, of the engineering professional services
prime contracts valued under $25,000 awarded during the study period, representing $263,868, or
73.49%, of the engineering professional services prime contract dollars.
Woman-owned Businesses received 193, or 96.98%, of the engineering professional services
prime contracts valued under $25,000 awarded during the study period, representing $285,037, or
79.38%, of the engineering professional services prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.21: Engineering Professional Services Prime Contract Utilization
Contracts Valued under $25,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 191 95.98%$263,868 73.49%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 2 1.01%$21,169 5.90%
Non-minority Males 6 3.02%$74,028 20.62%
TOTAL 199 100.00%$359,065 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 191 95.98%$263,868 73.49%
African American Males 0 0.00%$0 0.00%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 2 1.01%$21,169 5.90%
Non-minority Males 6 3.02%$74,028 20.62%
TOTAL 199 100.00%$359,065 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 191 95.98%$263,868 73.49%
Woman Business Enterprises 193 96.98%$285,037 79.38%
Minority and Women
Ethnicity
Ethnicity and Gender
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Prime Contractor Utilization Analysis
3. Purchases and Other Services Prime Contract Utilization: Contracts
Valued under $25,000
Table 2.22 summarizes all contract dollars expended by MSD on purchases and other services
prime contracts valued under $25,000. MBEs received 4.03% of the purchases and other services
prime contract dollars; WBEs received 74.32%; and non-MWBEs received 21.64%.
African Americans received 14, or 0.93%, of the purchases and other services prime contracts
valued under $25,000 awarded during the study period, representing $126,602, or 3.88%, of the
purchases and other services prime contract dollars.
Asian Americans received 1, or 0.07%, of the purchases and other services prime contracts valued
under $25,000 awarded during the study period, representing $5,100, or 0.16%, of the purchases
and other services prime contract dollars.
Hispanic Americans received none of the purchases and other services prime contracts valued
under $25,000 awarded during the study period.
Native Americans received none of the purchases and other services prime contracts valued under
$25,000 awarded during the study period.
Caucasian Females received 1,049, or 69.42%, of the purchases and other services prime
contracts valued under $25,000 awarded during the study period, representing $2,425,912, or
74.32%, of the purchases and other services prime contract dollars.
Non-minority Males received 447, or 29.58%, of the purchases and other services prime contracts
valued under $25,000 awarded during the study period, representing $706,416, or 21.64%, of the
purchases and other services prime contract dollars.
Minority-owned Businesses received 15, or 0.99%, of the purchases and other services prime
contracts valued under $25,000 awarded during the study period, representing $131,702, or 4.03%,
of the purchases and other services prime contract dollars.
Woman-owned Businesses received 1,049, or 69.42%, of the purchases and other services prime
contracts valued under $25,000 awarded during the study period, representing $2,425,912, or
74.32%, of the purchases and other services prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.22: Purchases and Other Services Prime Contract Utilization
Contracts Valued under $25,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 14 0.93%$126,602 3.88%
Asian Americans 1 0.07%$5,100 0.16%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 1,049 69.42%$2,425,912 74.32%
Non-minority Males 447 29.58%$706,416 21.64%
TOTAL 1,511 100.00%$3,264,031 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 0 0.00%$0 0.00%
African American Males 14 0.93%$126,602 3.88%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 1 0.07%$5,100 0.16%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 1,049 69.42%$2,425,912 74.32%
Non-minority Males 447 29.58%$706,416 21.64%
TOTAL 1,511 100.00%$3,264,031 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 15 0.99%$131,702 4.03%
Woman Business Enterprises 1,049 69.42%$2,425,912 74.32%
Minority and Women
Ethnicity
Ethnicity and Gender
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Prime Contractor Utilization Analysis
I. Formal Prime Contracts by Industry
1. Building Construction Prime Contract Utilization: Contracts Valued
from $25,000 to $8,270,000
Table 2.23 summarizes all contract dollars expended by MSD on building construction prime
contracts valued from $25,000 to $8,270,000. MBEs received 4.44% of the building construction
prime contract dollars; WBEs received none; and non-MWBEs received 95.56%.
African Americans received 1, or 16.67%, of the building construction prime contracts valued
from $25,000 to $8,270,000 awarded during the study period, representing $515,449, or 4.44% of
the building construction prime contract dollars.
Asian Americans received none of the building construction prime contracts valued from $25,000
to $8,270,000 awarded during the study period.
Hispanic Americans received none of the building construction prime contracts valued from
$25,000 to $8,270,000 awarded during the study period.
Native Americans received none of the building construction prime contracts valued from $25,000
to $8,270,000 awarded during the study period.
Caucasian Females received none of the building construction prime contracts valued from
$25,000 to $8,270,000 awarded during the study period.
Non-minority Males received 5, or 83.33%, of the building construction prime contracts valued
from $25,000 to $8,270,000 awarded during the study period, representing $11,082,304 or
95.56%, of the building construction prime contract dollars.
Minority-owned Businesses received 1, or 16.67%, of the building construction prime contracts
valued from $25,000 to $8,270,000 awarded during the study period, representing $515,449 or
4.44%, of the building construction prime contract dollars.
Woman-owned Businesses received none of the building construction prime contracts valued from
$25,000 to $8,270,000 awarded during the study period.
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Prime Contractor Utilization Analysis
Table 2.23: Building Construction Prime Contract Utilization
Contracts Valued From $25,000 to $8,270,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 1 16.67%$515,449 4.44%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 0 0.00%$0 0.00%
Non-minority Males 5 83.33%$11,082,304 95.56%
TOTAL 6 100.00%$11,597,753 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 0 0.00%$0 0.00%
African American Males 1 16.67%$515,449 4.44%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 0 0.00%$0 0.00%
Non-minority Males 5 83.33%$11,082,304 95.56%
TOTAL 6 100.00%$11,597,753 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 1 16.67%$515,449 4.44%
Woman Business Enterprises 0 0.00%$0 0.00%
Minority and Women
Ethnicity
Ethnicity and Gender
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Metropolitan St. Louis Sewer District Update Disparity Study
Prime Contractor Utilization Analysis
2. Non-Building Construction Prime Contract Utilization: Contracts
Valued from $25,000 to $500,000
Table 2.24 summarizes all contract dollars expended by MSD on non-building construction prime
contracts valued from $25,000 to $500,000. MBEs received 16.69% of the non-building
construction prime contract dollars; WBEs received 15.31%; and non-MWBEs received 73.50%.
African Americans received 74, or 17.79%, of the non-building construction prime contracts
valued from $25,000 to $500,000, awarded during the study period, representing $8,974,483 or
14.15%, of the non-building construction prime contract dollars.
Asian Americans received none of the non-building construction prime contracts valued from
$25,000 to $500,000 awarded during the study period.
Hispanic Americans received 8, or 1.92%, of the non-building construction prime contracts valued
from $25,000 to $500,000 awarded during the study period, representing $1,030,594 or 1.62%, of
the non-building construction prime contract dollars.
Native Americans received 3, or 0.72%, of the non-building construction prime contracts valued
from $25,000 to $500,000 awarded during the study period, representing $583,766 or 0.92%, of
the non-building construction prime contract dollars.
Caucasian Females received 35, or 8.41%, of the non-building construction prime contracts
valued from $25,000 to $500,000 awarded during the study period, representing $6,219,064, or
9.80%, of the non-building construction prime contract dollars.
Non-minority Males received 296, or 71.15%, of the non-building construction prime contracts
valued from $25,000 to $500,000 awarded during the study period, representing $46,626,134, or
73.50%, of the non-building construction prime contract dollars.
Minority-owned Businesses received 85, or 20.43%, of the non-building construction prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$10,588,843, or 16.69%, of the non-building construction prime contract dollars.
Woman-owned Businesses received 63, or 15.14%, of the non-building construction prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$9,710,251, or 15.31%, of the non-building construction prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.24: Non-Building Construction Prime Contract Utilization
Contracts Valued from $25,000 to $500,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 74 17.79%$8,974,483 14.15%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 8 1.92%$1,030,594 1.62%
Native Americans 3 0.72%$583,766 0.92%
Caucasian Females 35 8.41%$6,219,064 9.80%
Non-minority Males 296 71.15%$46,626,134 73.50%
TOTAL 416 100.00%$63,434,041 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 28 6.73%$3,491,186 5.50%
African American Males 46 11.06%$5,483,296 8.64%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 8 1.92%$1,030,594 1.62%
Native American Females 0 0.00%$0 0.00%
Native American Males 3 0.72%$583,766 0.92%
Caucasian Females 35 8.41%$6,219,064 9.80%
Non-minority Males 296 71.15%$46,626,134 73.50%
TOTAL 416 100.00%$63,434,041 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 85 20.43%$10,588,843 16.69%
Woman Business Enterprises 63 15.14%$9,710,251 15.31%
Minority and Women
Ethnicity
Ethnicity and Gender
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Metropolitan St. Louis Sewer District Update Disparity Study
Prime Contractor Utilization Analysis
3. Engineering Professional Services Prime Contract Utilization:
Contracts Valued from $25,000 to $500,000
Table 2.25 summarizes all contract dollars expended by MSD on engineering professional services
prime contracts valued from $25,000 to $500,000. MBEs received 18.01% of the engineering
professional services prime contract dollars; WBEs received 12.30%; and non-MWBEs received
70.96%.
African Americans received 11, or 20.37%, of the engineering professional services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$1,529,963, or 16.65%, of the engineering professional services prime contract dollars.
Asian Americans received none of the engineering professional services prime contracts valued
from $25,000 to $500,000 awarded during the study period.
Hispanic Americans received 1, or 1.85%, of the engineering professional services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$125,000, or 1.36%, of the engineering professional services prime contract dollars.
Native Americans received none of the engineering professional services prime contracts valued
from $25,000 to $500,000 awarded during the study period.
Caucasian Females received 7, or 12.96%, of the engineering professional services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$1,013,793, or 11.03%, of the engineering professional services prime contract dollars.
Non-minority Males received 35, or 64.81%, of the engineering professional services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$6,520,876, or 70.96%, of the engineering professional services prime contract dollars.
Minority-owned Businesses received 12, or 22.22%, of the engineering professional services
prime contracts valued from $25,000 to $500,000 awarded during the study period, representing
$1,654,963, or 18.01%, of the engineering professional services prime contract dollars.
Woman-owned Businesses received 9, or 16.67%, of the engineering professional services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$1,130,105, or 12.30%, of the engineering professional services prime contract dollars.
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Prime Contractor Utilization Analysis
Table 2.25: Engineering Professional Services Prime Contract Utilization
Contracts Valued from $25,000 to $500,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 11 20.37%$1,529,963 16.65%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 1 1.85%$125,000 1.36%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 7 12.96%$1,013,793 11.03%
Non-minority Males 35 64.81%$6,520,876 70.96%
TOTAL 54 100.00%$9,189,632 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 2 3.70%$116,312 1.27%
African American Males 9 16.67%$1,413,651 15.38%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 1 1.85%$125,000 1.36%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 7 12.96%$1,013,793 11.03%
Non-minority Males 35 64.81%$6,520,876 70.96%
TOTAL 54 100.00%$9,189,632 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 12 22.22%$1,654,963 18.01%
Woman Business Enterprises 9 16.67%$1,130,105 12.30%
Minority and Women
Ethnicity
Ethnicity and Gender
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Metropolitan St. Louis Sewer District Update Disparity Study
Prime Contractor Utilization Analysis
4. Purchases and Other Services Prime Contract Utilization: Contracts
Valued from $25,000 to $500,000
Table 2.26 summarizes all contract dollars expended by MSD on purchases and other services
prime contracts valued from $25,000 to $500,000. MBEs received 39.60% of the purchases and
other services prime contract dollars; WBEs received 16.30%; and non-MWBEs received 44.10%.
African Americans received 12, or 30.77%, of the purchases and other services prime contracts
valued from $25,000 to $500,000 awarded during the study period, representing $1,968,854, or
35.87%, of the purchases and other services prime contract dollars.
Asian Americans received 2, or 5.13%, of the purchases and other services prime contracts valued
from $25,000 to $500,000 awarded during the study period, representing $204,550, or 3.73%, of
the purchases and other services prime contract dollars.
Hispanic Americans received none of the purchases and other services prime contracts valued
from $25,000 to $500,000 awarded during the study period.
Native Americans received none of the purchases and other services prime contracts valued from
$25,000 to $500,000 awarded during the study period.
Caucasian Females received 8, or 20.51%, of the purchases and other services prime contracts
valued from $25,000 to $500,000 awarded during the study period, representing $894,664, or
16.30%, of the purchases and other services prime contract dollars.
Non-minority Males received 17, or 43.59%, of the purchases and other services prime contracts
valued from $25,000 to $500,000 awarded during the study period, representing $2,420,491, or
44.10%, of the purchases and other services prime contract dollars.
Minority-owned Businesses received 14, or 35.90%, of the purchases and other services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$2,173,404, or 39.60%, of the purchases and other services prime contract dollars.
Woman-owned Businesses received 8, or 20.51%, of the purchases and other services prime
contracts valued from $25,000 to $500,000 awarded during the study period, representing
$894,664, or 16.30%, of the purchases and other services prime contract dollars.
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Table 2.26: Purchases and Other Services Prime Contract Utilization
Contracts Valued from $25,000 to $500,000, January 1, 2013 to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 12 30.77%$1,968,854 35.87%
Asian Americans 2 5.13%$204,550 3.73%
Hispanic Americans 0 0.00%$0 0.00%
Native Americans 0 0.00%$0 0.00%
Caucasian Females 8 20.51%$894,664 16.30%
Non-minority Males 17 43.59%$2,420,491 44.10%
TOTAL 39 100.00%$5,488,559 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 0 0.00%$0 0.00%
African American Males 12 30.77%$1,968,854 35.87%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 2 5.13%$204,550 3.73%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 0 0.00%$0 0.00%
Native American Females 0 0.00%$0 0.00%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 8 20.51%$894,664 16.30%
Non-minority Males 17 43.59%$2,420,491 44.10%
TOTAL 39 100.00%$5,488,559 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 14 35.90%$2,173,404 39.60%
Woman Business Enterprises 8 20.51%$894,664 16.30%
Minority and Women
Ethnicity
Ethnicity and Gender
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V. Summary
The prime contract utilization analysis examined prime contracts valued at $1,238,982,577
awarded by MSD during the study period of January 1, 2013 to December 31, 2017. The
$1,238,982,577 expended included $30,684,903 for building construction, $917,808,132 for non-
building construction, $279,103,076 for engineering professional services, and $11,386,466 for
purchases and other services. A total of 2,749 prime contracts were analyzed, which included seven
for building construction, 890 for non-building construction, 299 for engineering professional
services, and 1,553 for purchases and other services.
The utilization analysis was performed for prime contracts in the four industries at three-dollar
thresholds: (1) all prime contracts regardless of award amount, (2) all informal prime contracts
valued under $25,000 for non-building construction, engineering professional services, and
purchases and other services, as defined by MSD’s purchasing policy, and (3) formal prime
contracts valued from $25,000 to $8,270,000 for building construction and from $25,000 to
$500,000 for non-building construction, engineering professional services, and purchases and
other services.
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CHAPTER 3: Subcontractor Utilization
Analysis
I. Introduction
A disparity study, as required by Croson, must document the local government’s utilization of
available Minority and Woman-owned Business Enterprises (MWBE), and non-minority male-
owned businesses (non-MWBE) as prime contractors and subcontractors. This chapter presents
the utilization of building construction, non-building construction, and engineering professional
services subcontractors by ethnicity, gender, and industry. The analysis examined the subcontracts
Metropolitan St. Louis Sewer District’s (MSD) prime contractors awarded during the January 1,
2013 to December 31, 2017 study period.
II. Data Sources
Subcontract records were collected in order to analyze expenditures by industry, race, and gender.
Table 4.1 lists the sources used to compile the subcontract dataset. MSD’s online Diversity
Reporting (MDR) system was the primary repository of subcontract records for the study period.
The system, implemented in response to recommendations made in the 2012 Disparity Study,
tracks award and payment data for CIRP construction and engineering professional services
contracts. Additional sources, as noted in Table 4.1, were used to compile subcontract data.
Since some records were found in more than one source, the sources were ranked, and the data
analyzed was retrieved from the highest ranked source. It is clear from the reconstructed data that
the Diversity Reporting (MDR) system effectively captured most of the subcontracts awarded
during the study period.
Table 3.1: Prime Contracts and Unique Subcontracts by Source
Source Number of Prime
Contracts
Number of Unique
Subcontracts
MDR Electronic Subcontract Records 663 1,253
Form C PDF Subcontract Records 139 1,233
Contract Administrator Records 19 41
Total 821 2,527
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A. Data Collection Process
The subcontract data collection was collected from three sources. Initially, the subcontract awards
and payments were extracted from the MDR system. Subsequently, Form C, Vendor utilization,
was collected and reviewed for subcontracts listed during the project close-out. For subcontract
data that could not be secured from MDR or Form C, Mason Tillman worked in collaboration with
contract administrators to secure subcontract records from their project files for the remainder of
the prime contracts. A total of 2,527 unique subcontracts were secured using this process.
1. MDR Electronic Subcontract Records
Prime contractors are required to submit monthly reports in the MDR system, even when no
subcontractor payments are made during the month. At the time the prime enters the subcontract
data an automated email is sent to the subcontractor to verify the payment amount.
MSD extracted the subcontract data from the MDR online system and provided an electronic file
containing subcontract award and payment records for1,253 unique subcontracts.
2. Form C PDF Subcontract Records
Form C was submitted to MSD during the contract close out prior to release of the final payment.
Form C were PDF files from which the data was data was extracted manually and entered into an
Excel file. There were 1,233 unique subcontracts retrieved from the Form Cs.
3. Contract Administrator Records
For the prime contracts that were not identified in the MDR system or from a Form C, MSD’s
contract administrators were also asked to review their files to locate the prime contracts. The
contract administrators identified 19 of the outstanding prime contracts and 41 subcontracts.
B. Subcontract Data Analysis
The subcontract records were appended to the relational database and cleaned to remove duplicate
contracts. The ethnicity and gender of each subcontractor was verified using certification
directories and Internet research. Once the data were cleaned, the subcontractor utilization tables
identifying the dollars and number of subcontracts awarded to each ethnic and gender group in the
three industries were prepared. Subcontractor utilization by ethnicity, gender, and industry is
presented below.
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III. Subcontractor Utilization
A. All Subcontracts
Table 4.2 lists the 2,527 reconstructed subcontracts in the analysis. The 2,527 subcontracts include
101 building construction, 2,173 non-building construction, and 253 engineering professional
services.
A total of $388,761,711 subcontract dollars were analyzed. There were $16,587,434 for building
construction, $279,266,674 for non-building construction, and $92,907,603 for engineering
professional services.
Table 3.1: Subcontracts Awarded and Dollars Expended by Industry,
January 1, 2013, to December 31, 2017
Industry Total Number of
Subcontracts
Total Amount
Expended
Building Construction 101 $16,587,434
Non-building Construction 2,173 $279,266,674
Engineering Professional services 253 $92,907,603
Total 2,527 $388,761,711
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B. Subcontracts by Industry
1. Building Construction Subcontracts
Table 4.3 lists the analyzed building construction subcontracts awarded by MSD’s prime
contractors during the study period. Minority-owned businesses (MBE) received 22.57%; woman-
owned businesses220 (WBE) received 7.51%; and non-minority male-owned businesses (non-
MWBE) received 70.94% of the building construction subcontract dollars.
African Americans received 23 or 22.77% of MSD’s building construction subcontracts,
representing $3,426,554 or 20.66% of the building construction subcontract dollars.
Asian Americans received none of MSD’s building construction subcontracts.
Hispanic Americans received 1 or 0.99% of MSD’s building construction subcontracts,
representing $83,979 or 0.51% of the building construction subcontract dollars.
Native Americans received 1 or 0.99% of MSD’s building construction subcontracts, representing
$233,872 or 1.41% of the building construction subcontract dollars.
Caucasian Females received 12 or 11.88% of MSD’s building construction subcontracts,
representing $1,076,138 or 6.49% of the building construction subcontract dollars.
Non-minority Males received 64 or 63.37% of MSD’s building construction subcontracts,
representing $11,766,892 or 70.94% of the building construction subcontract dollars.
Minority-owned Businesses received 25 or 24.75% of MSD’s building construction subcontracts
during the study period, representing $3,744,405 or 22.57% of the building construction
subcontract dollars.
Woman-owned Businesses received 19 or 18.81% of MSD’s building construction subcontracts
during the study period, representing $1,244,991 or 7.51% of the building construction subcontract
dollars.
220 Ethnic and gender categories have been described in Table 2.1 in Chapter 2: Prime Contractor Utilization Analysis.
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Table 3.2: Building Construction Subcontractor Utilization,
January 1, 2013, to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 23 22.77%$3,426,554 20.66%
Asian Americans 0 0.00%$0 0.00%
Hispanic Americans 1 0.99%$83,979 0.51%
Native Americans 1 0.99%$233,872 1.41%
Caucasian Females 12 11.88%$1,076,138 6.49%
Non-minority Males 64 63.37%$11,766,892 70.94%
TOTAL 101 100.00%$16,587,434 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 7 6.93%$168,853 1.02%
African American Males 16 15.84%$3,257,701 19.64%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 0 0.00%$0 0.00%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 1 0.99%$83,979 0.51%
Native American Females 0 0.00%$0 0.00%
Native American Males 1 0.99%$233,872 1.41%
Caucasian Females 12 11.88%$1,076,138 6.49%
Non-minority Males 64 63.37%$11,766,892 70.94%
TOTAL 101 100.00%$16,587,434 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 25 24.75%$3,744,405 22.57%
Woman Business Enterprises 19 18.81%$1,244,991 7.51%
Minority and Women
Ethnicity
Ethnicity and Gender
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2. Non-building Construction Subcontracts
Table 4.4 lists the non-building construction subcontracts issued by MSD’s prime contractors
during the study period. MBEs received 53.32%; WBEs received 18.19%; and non-MWBEs
received 38.75% of the non-building construction subcontract dollars.
African Americans received 831 or 38.24% of MSD’s non-building construction subcontracts,
representing $146,358,711 or 52.41% of the non-building construction subcontract dollars.
Asian-Americans received 1 or 0.05% of MSD’s non-building construction subcontracts,
representing $23,581 or 0.01% of the non-building construction subcontract dollars.
Hispanic Americans received 30 or 1.38% of MSD’s non-building construction subcontracts,
representing $2,276,874 or 0.82% of the non-building construction subcontract dollars.
Native Americans received 2 or 0.09% of MSD’s non-building construction subcontracts,
representing $253,572 or 0.09% of the non-building construction subcontract dollars.
Caucasian Females received 239 or 11.00% of MSD’s non-building construction subcontracts,
representing $22,125,499 or 7.92% of the non-building construction subcontract dollars.
Non-minority Males received 1,070 or 49.24% of MSD’s non-building construction subcontracts,
representing $108,228,437 or 38.75% of non-building construction subcontract dollars.
Minority-owned Businesses received 864 or 39.76% of MSD’s non-building construction
subcontracts during the study period, representing $148,912,738 or 53.32% of the non-building
construction subcontract dollars.
Woman-owned Businesses received 458 or 21.08% of MSD’s non-building construction
subcontracts during the study period, representing $50,790,166 or 18.19% of the non -building
construction subcontract dollars.
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Table 3.3: Non-building Construction Subcontractor Utilization,
January 1, 2013, to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 831 38.24%$146,358,711 52.41%
Asian Americans 1 0.05%$23,581 0.01%
Hispanic Americans 30 1.38%$2,276,874 0.82%
Native Americans 2 0.09%$253,572 0.09%
Caucasian Females 239 11.00%$22,125,499 7.92%
Non-minority Males 1,070 49.24%$108,228,437 38.75%
TOTAL 2,173 100.00%$279,266,674 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 201 9.25%$28,166,932 10.09%
African American Males 630 28.99%$118,191,779 42.32%
Asian American Females 0 0.00%$0 0.00%
Asian American Males 1 0.05%$23,581 0.01%
Hispanic American Females 18 0.83%$497,735 0.18%
Hispanic American Males 12 0.55%$1,779,140 0.64%
Native American Females 0 0.00%$0 0.00%
Native American Males 2 0.09%$253,572 0.09%
Caucasian Females 239 11.00%$22,125,499 7.92%
Non-minority Males 1,070 49.24%$108,228,437 38.75%
TOTAL 2,173 100.00%$279,266,674 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 864 39.76%$148,912,738 53.32%
Woman Business Enterprises 458 21.08%$50,790,166 18.19%
Minority and Women
Ethnicity
Ethnicity and Gender
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3. Engineering Professional Services Subcontracts
Table 4.5 lists the engineering professional services subcontracts issued by MSD’s prime
contractors during the study period. MBEs received 37.40%; WBEs received 33.11%; and non-
MWBEs received 40.52% of the professional services subcontract dollars.
African Americans received 69 or 27.27% of MSD’s engineering professional services
subcontracts, representing $21,075,815 or 22.68% of the engineering professional services
subcontract dollars.
Asian Americans received 12 or 4.74% of MSD’s engineering professional services subcontracts,
representing $5,284,725 or 5.69% of the engineering professional services subcontract dollars.
Hispanic Americans received 16 or 6.32% of MSD’s engineering professional services
subcontracts, representing $8,370,222 or 9.01% of the engineering professional services
subcontract dollars.
Native Americans received 1 or 0.40% of MSD’s engineering professional services subcontracts,
representing $15,303 or 0.02% of the engineering professional services subcontract dollars.
Caucasian Females received 75 or 29.64% of MSD’s engineering professional services
subcontracts, representing $20,515,023 or 22.08% of the engineering professional services
subcontract dollars.
Non-minority Males received 80 or 31.62% of MSD’s engineering professional services
subcontracts, representing $37,646,515 or 40.52% of the engineering professional services
subcontract dollars.
Minority-owned Businesses received 98 or 38.74% of MSD’s engineering professional services
subcontracts during the study period, representing $34,746,065 or 37.40% of the engineering
professional services subcontract dollars.
Woman-owned Businesses received 114 or 45.06% of MSD’s engineering professional services
subcontracts during the study period, representing $30,765,363 or 33.11% of the engineering
professional services subcontract dollars.
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Table 3.4: Engineering Professional Services Subcontractor Utilization,
January 1, 2013, to December 31, 2017
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African Americans 69 27.27%$21,075,815 22.68%
Asian Americans 12 4.74%$5,284,725 5.69%
Hispanic Americans 16 6.32%$8,370,222 9.01%
Native Americans 1 0.40%$15,303 0.02%
Caucasian Females 75 29.64%$20,515,023 22.08%
Non-minority Males 80 31.62%$37,646,515 40.52%
TOTAL 253 100.00%$92,907,603 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
African American Females 37 14.62%$10,177,991 10.95%
African American Males 32 12.65%$10,897,824 11.73%
Asian American Females 1 0.40%$57,045 0.06%
Asian American Males 11 4.35%$5,227,680 5.63%
Hispanic American Females 0 0.00%$0 0.00%
Hispanic American Males 16 6.32%$8,370,222 9.01%
Native American Females 1 0.40%$15,303 0.02%
Native American Males 0 0.00%$0 0.00%
Caucasian Females 75 29.64%$20,515,023 22.08%
Non-minority Males 80 31.62%$37,646,515 40.52%
TOTAL 253 100.00%$92,907,603 100.00%
Number Percent Amount Percent
of Contracts of Contracts of Dollars of Dollars
Minority Business Enterprises 98 38.74%$34,746,065 37.40%
Woman Business Enterprises 114 45.06%$30,765,363 33.11%
Minority and Women
Ethnicity
Ethnicity and Gender
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IV. Summary
The subcontract records were compiled using a process involving three sources. The primary
source from which the majority of the subcontracts were secured was the MDR system.
Subcontract records were also extracted from Form C and project files. A total of 2,527
subcontracts were identified, including 101 for building construction, 2,173 for non-building
construction, and 253 for engineering professional services. The building construction, non-
building construction, and engineering professional services subcontract records compiled and
analyzed were valued at $102,644,758. The $102,644,758 included $16,587,434 for building
construction, $279,266,674 for non-building construction, and $92,907,603 for engineering
professional services.
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CHAPTER 4: Market Area Analysis
I. Introduction
A. Legal Criteria for Geographic Market Area
The Supreme Court’s decision in City of Richmond v. J.A. Croson Co.221 (Croson) held that
programs established by local governments to set goals for the participation of Minority-owned
Business Enterprises (MBEs) must be supported by evidence of past discrimination in the award
of their contracts. Prior to the Croson decision, local governments could implement race-conscious
programs without developing a detailed public record to document the underutilization of MBEs
in their award of contracts. Instead, they relied on widely recognized societal patterns of
discrimination.222
Croson established that a local government could not rely on society-wide discrimination as the
basis for a race-based contracting program. Instead, a local government was required to identify
discrimination within its own contracting jurisdiction.223 In Croson, the United States Supreme
Court found the City of Richmond, Virginia’s MBE construction program to be unconstitutional
because there was insufficient evidence of discrimination in the local construction market.
Croson was explicit in saying that the local construction market was the appropriate geographical
framework within which to perform statistical comparisons of business availability to business
utilization. Therefore, the identification of the local market area is particularly important because
it establishes the parameters within which to conduct a disparity study.
B. Application of the Croson Standard
While Croson emphasized the importance of the local market area, it provided little assistance in
defining its parameters. However, it is informative to review the Court’s definition of the City of
Richmond, Virginia’s market area. In discussing the geographic parameters of the constitutional
violation that must be investigated, the Court interchangeably used the terms “relevant market,”
“Richmond construction industry,”224 and “city’s construction industry.”225 These terms were used
to define the proper scope for examining the existence of discrimination within the City. This
interchangeable use of terms lends support to a definition of market area that coincides with the
boundaries of a contracting jurisdiction.
221 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
222 United Steelworkers v. Weber, 433 U.S. 193, 198, n. 1 (1979).
223 Croson, 488 U.S. at 497.
224 Id. at 500.
225 Id. at 470.
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An analysis of the cases following Croson provides additional guidance for defining the market
area. The body of cases examining the reasonable market area definition is fact-based—rather
than dictated by a specific formula.226 In Cone Corporation v. Hillsborough County,227 the United
States Eleventh Circuit Court of Appeals considered a disparity study in support of Hillsborough
County, Florida’s MBE Program. The MBE program used minority contractors located in
Hillsborough County as the measure of available firms. The program was found to be
constitutional under the compelling governmental interest element of the strict scrutiny standard.
Hillsborough County’s program was based on statistics indicating that specific discrimination
existed in the construction contracts awarded by Hillsborough County, not in the construction
industry in general. Hillsborough County extracted data from within its own jurisdictional
boundaries and assessed the percentage of minority businesses available in Hillsborough County.
The Court stated that the disparity study was properly conducted within the “local construction
industry.”228
Similarly, in Associated General Contractors v. Coalition for Economic Equity (AGCCII),229 the
United States Ninth Circuit Court of Appeals found the City and County of San Francisco,
California’s MBE Program to have the factual predicate necessary to survive strict scrutiny. The
San Francisco MBE Program was supported by a disparity study that assessed the number of
available MBE contractors within the City and County of San Francisco, California. The Court
found it appropriate to use the City and County as the relevant market area within which to conduct
a disparity study.230
In Coral Construction v. King County, the United States Ninth Circuit Court of Appeals held that
“a set-aside program is valid only if actual, identifiable discrimination has occurred within the
local industry affected by the program.”231 In support of its MBE program, King County,
Washington offered studies compiled by other jurisdictions, including entities completely within
the County, others coterminous with the boundaries of the County, as well as a jurisdiction
significantly distant from King County. The plaintiffs contended that Croson required King
County, Washington, to compile its own data and cited Croson as prohibiting data sharing.
The Court found that data sharing could potentially lead to the improper use of societal
discrimination data as the factual basis for a local MBE program and that innocent third parties
could be unnecessarily burdened if an MBE program were based on data outside the government’s
jurisdictional boundaries. However, the Court also found that the data from entities within King
226 See e.g., Concrete Works of Colorado v. City of Denver, Colorado , 36 F.3d 1513, 1528 (10th Cir. 1994) (“Concrete Works”).
227 Cone Corporation v. Hillsborough County, 908 F.2d 908 (11th Cir. 1990).
228 Id. at 915.
229 Associated General Contractors of California v. Coalition for Economic Equity and City and County of San Francisco , 950 F.2d 1401 (9th
Cir. 1991).
230 AGCCII, 950 F.2d at 1415.
231 Coral Construction Co. v. King County, 941 F.2d 910 (9th Cir. 1991).
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County and from coterminous jurisdictions were relevant to discrimination in the County. They
also found that the data posed no risk of unfairly burdening innocent third parties.
The Court concluded that data gathered by a neighboring county could not be used to support King
County’s MBE program. The Court noted, “It is vital that a race-conscious program align itself as
closely to the scope of the problem sought to be rectified by the governmental entity. To prevent
overbreadth, the enacting jurisdiction should limit its factual inquiry to the presence of
discrimination within its own boundaries.”232 However, the Court did note that the “world of
contracting does not conform itself neatly to jurisdictional boundaries.”233
There are other situations where courts have approved a market area definition that extended
beyond a jurisdiction’s geographic boundaries. In Concrete Works v. City and County of Denver
(Concrete Works),234 the United States Tenth Circuit Court of Appeals directly addressed the issue
of whether extra-jurisdictional evidence of discrimination can be used to determine the “local
market area” for a disparity study. In Concrete Works, the defendant relied on evidence of
discrimination in the six-county Denver, Colorado Metropolitan Statistical Area (Denver MSA) to
support its MBE program. Plaintiffs argued that the federal constitution prohibited consideration
of evidence beyond jurisdictional boundaries. The Court of Appeals disagreed.
Critical to the Court’s acceptance of the Denver MSA as the relevant local market was the finding
that more than 80% of construction and design contracts awarded by the City and County of
Denver were awarded to contractors within the Denver MSA. Another consideration was that the
City and County of Denver’s analysis was based on United States Census data, which was available
for the Denver MSA but not for the City of Denver itself. There was no undue burden placed on
nonculpable parties, as the City and County of Denver had expended a majority of its construction
contract dollars within the area defined as the local market. Citing AGCCII,235 the Court noted
“that any plan that extends race-conscious remedies beyond territorial boundaries must be based
on very specific findings that actions the city has taken in the past have visited racial discrimination
on such individuals.”236
Similarly, New York State conducted a disparity study in which the geographic market consisted
of New York State and eight counties in northern New Jersey. The geographic market was defined
as the area encompassing the location of businesses that received more than 90% of the dollar
value of all contracts awarded by the agency.237
State and local governments must pay special attention to the geographical scope of their disparity
studies. Croson determined that the statistical analysis should focus on the number of qualified
232 Coral, 941 F.2d at 917.
233 Id.
234 Concrete Works, 36 F.3d at 1528.
235 AGCC II, 950 F.2d at 1401.
236 Concrete Works, 36 F.3d at 1528.
237 Opportunity Denied! New York State’s Study, 26 Urban Lawyer No. 3, Summer 1994.
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minority business owners in the government’s marketplace.238 The text of Croson itself suggests
that the geographical boundaries of the government entity comprise an appropriate market area
and other courts have agreed with this finding.
It follows then that an entity may limit consideration of evidence of discri mination to
discrimination occurring within its own jurisdiction.
II. Market Area Analysis
Although Croson and its progeny do not provide a bright line rule for the delineation of the local
market area, taken collectively, the case law supports a definition of the market area as the
geographical boundaries of the government entity. Given Metropolitan St. Louis Sewer District’s
(MSD) jurisdiction, the Study’s market area is determined to be the geographical boundaries of
the City of St. Louis, and St. Louis County.
A. Summary of the Distribution of All Prime Contracts Awarded
MSD awarded 2,749 prime contracts valued at $1,238,982,577 from January 1, 2013 to December
31, 2017. The distribution of all prime contracts awarded and dollars received by all firms
domiciled inside and outside of the market area is depicted in Table 4.1.
Table 4.1: Distribution of All Contracts Awarded
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
St. Charles County 372 13.53% $481,115,041 38.83%
St. Louis County 1,690 61.48% $439,576,873 35.48%
St. Louis City 457 16.62% $192,259,333 15.52%
Franklin County 88 3.20% $28,090,725 2.27%
Lincoln County 23 0.84% $18,548,267 1.50%
Jefferson County 63 2.29% $10,452,892 0.84%
St. Francois County 17 0.62% $2,613,799 0.21%
Warren County 4 0.15% $461,186 0.04%
Clay County 3 0.11% $64,956 0.01%
Out of State 32 1.16% $65,799,504 5.31%
Total 2,749 100.00% $1,238,982,577 100.00%
238 Croson, 488 U.S. at 501.
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Market Area Analysis
B. Distribution of Building Construction Prime Contracts
MSD awarded 7 building construction prime contracts valued at $30,684,903 during the study
period. Businesses located in the market area received 57.14% of the building construction prime
contracts and 13.32% of the dollars. The distribution of the building construction prime contracts
awarded and dollars received by all firms domiciled inside and outside of the market area is
depicted in Table 4.2.
Table 4.2: Distribution of Building Construction Prime Contracts
III. Distribution of Non-building Construction Prime Contracts
MSD awarded 890 non-building construction prime contracts valued at $917,808,132 during the
study period. Businesses located in the market area received 64.16% of the non-building
construction prime contracts and 37.29% of the dollars. The distribution of the non-building
construction prime contracts awarded and dollars received by all firms domiciled inside and
outside of the market area is depicted in Table 4.3.
Table 4.3: Distribution of Non-building Construction Prime Contracts
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
St. Charles County 109 12.25% $479,138,380 52.20%
St. Louis County 361 40.56% $259,509,538 28.27%
St. Louis City 210 23.60% $82,738,061 9.01%
Franklin County 87 9.78% $28,075,322 3.06%
Lincoln County 23 2.58% $18,548,267 2.02%
Jefferson County 63 7.08% $10,452,892 1.14%
St. Francois County 17 1.91% $2,613,799 0.28%
Warren County 4 0.45% $461,186 0.05%
Clay County 1 0.11% $2,564 0.00%
Out Of State 15 1.69% $36,268,122 3.95%
Total 890 100.00% $917,808,132 100.00%
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
St. Louis County 4 57.14%$4,088,353 13.32%
Out Of State 3 42.86%$26,596,550 86.68%
Total 7 100.00%$30,684,903 100.00%
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Market Area Analysis
A. Distribution of Engineering Professional Services Prime
Contracts
MSD awarded 299 engineering professional services prime contracts valued at $279,103,076
during the study period. Businesses located in the market area received 99.67% of the engineering
professional services prime contracts and 99.96% of the dollars. The distribution of the engineering
professional services prime contracts awarded and dollars received by all firms domiciled inside
and outside of the market area is depicted in Table 4.4.
Table 4.4: Distribution of Engineering Professional Services Prime Contracts
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
St. Louis County 60 20.07% $169,897,530 60.87%
St. Louis City 238 79.60% $109,105,547 39.09%
Out of State 1 0.33% $100,000 0.04%
Total 299 100.00% $279,103,076 100.00%
B. Distribution of Purchases and Other Services Prime Contracts
MSD awarded 1,553 purchases and other services prime contracts valued at $11,386,466 during
the study period. Businesses located in the market area received 82.03% of the purchases and other
services prime contracts and 57.06% of the dollars. The distribution of the purchases and other
services prime contracts awarded and dollars received by all firms domiciled inside and outside of
the market area is depicted in Table 4.5.
Table 4.5: Distribution of Purchases and Other Services Prime Contracts
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
St. Louis County 1,265 81.46% $6,081,453 53.41%
St. Charles County 263 16.93% $1,976,661 17.36%
St. Louis City 9 0.58% $415,725 3.65%
Clay County 2 0.13% $62,392 0.55%
Franklin County 1 0.06% $15,403 0.14%
Out of State 13 0.84% $2,834,832 24.90%
Total 1,553 100.00% $11,386,466 100.00%
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Market Area Analysis
IV. Summary
During the study period, MSD awarded 2,749 building construction, non-building construction,
engineering professional services, and purchases and other services prime contracts valued at
$1,238,982,577. The MSD awarded 2,147 of prime contracts and $631,836,206 of dollars to
businesses domiciled within the market area.
Table 5.5 depicts an overview of the number of building construction, non-building construction,
engineering professional services, and purchases and other services prime contracts MSD awarded
and the dollars spent in the market area.
Building Construction Prime Contracts: 4 or 57.14% of building construction prime contracts
were awarded to market area businesses. Building construction prime contracts in the market area
accounted for $4,088,353 or 13.32% of the total building construction prime contract dollars.
Non-Building Construction Prime Contracts: 571 or 64.16% of non-building construction prime
contracts were awarded to market area businesses. Non-building construction prime contracts in
the market area accounted for $342,247,599 or 37.29% of the total non-building construction
prime contract dollars.
Engineering Professional Services Prime Contracts: 298 or 99.67% of engineering professional
services prime contracts were awarded to market area businesses. Engineering professional
services prime contracts in the market area accounted for $279,003,076 or 99.96% of the total
engineering professional services prime contract dollars.
Purchases and Other Services Prime Contracts: 1,274 or 82.03% of purchases and other services
prime contracts were awarded to market area businesses. Purchases and other services prime
contracts in the market area accounted for $6,497,178 or 57.06% of the total purchases and other
services prime contract dollars.
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Market Area Analysis
Table 4.6: Distribution of MSD Contracts
Geographic
Area
Number of
Contracts
Percent of
Contracts
Total
Dollars
Percent of
Dollars
Market Area 2,147 78.10%$631,836,206 51.00%
Outside Market Area 602 21.90%$607,146,371 49.00%
TOTAL 2,749 100.00%$1,238,982,577 100.00%
Market Area 4 57.14%$4,088,353 13.32%
Outside Market Area 3 42.86%$26,596,550 86.68%
TOTAL 7 100.00%$30,684,903 100.00%
Market Area 571 64.16%$342,247,599 37.29%
Outside Market Area 319 35.84%$575,560,533 62.71%
TOTAL 890 100.00%$917,808,132 100.00%
Market Area 298 99.67%$279,003,076 99.96%
Outside Market Area 1 0.33%$100,000 0.04%
TOTAL 299 100.00%$279,103,076 100.00%
Market Area 1,274 82.03%$6,497,178 57.06%
Outside Market Area 279 17.97%$4,889,288 42.94%
TOTAL 1,553 100.00%$11,386,466 100.00%
Non-Building Construction Including Federally Funded
Engineering Professional Services
Purchases and Other Services
Combined Industries
Building Construction
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Prime Contractor and Subcontractor Availability Analysis
CHAPTER 5: Prime Contractor and
Subcontractor Availability
Analysis
I. Introduction
According to City of Richmond v. J.A. Croson Co. (Croson), availability is defined as the number
of businesses in the local government’s market area that are ready, willing, and able to provide the
goods or services procured by the entity.239 To determine the availability of Minority and Woman-
owned Business Enterprises240 (MWBEs) and non-minority male-owned businesses domiciled
within the market area, the available businesses must first be enumerated. As set forth in Chapter
4: Market Area Analysis, the market area is defined as the City and County of St. Louis.
When considering sources to determine the number of available MWBEs and non-minority male-
owned businesses in the market area, the selection must be based on whether two aspects about
the population in question can be gauged from the availability sources. One consideration is a
business’ interest in contracting with the government, as implied by the term “willing.” The other
is the business’ ability or capacity to provide a service or good, as implied by the term “able.” The
available businesses met these criteria.
II. Prime Contractor Availability Data Sources
A. Identification of Willing Businesses Within the Mar ket Area
To identify willing and able businesses in the MSD’s market area that provide the building
construction, non-building construction, engineering professional services, and purchases and
other services that the Metropolitan St. Louis Sewer District (MSD) pro cures, four sources of
information were used. The four sources were 1) MSD’s utilized businesses, bidders, and vendor
list; 2) government certification directories; 3) business owners who attended MSD’s Disparity
Study business community meetings; and 4) business association, trade organizations and chamber
of commerce membership lists.
Any business listed in more than one source was only counted once in the relevant industry. If a
business was willing and able to provide goods or services in more than one industry it was listed
in each relevant industry. The four sources were ranked according to their reliability in determining
a business’ willingness to contract with MSD. The highest ranking was assigned to the businesses
received from MSD. Government certification lists were ranked second; community meeting
attendees third; and business association membership lists fourth. Businesses culled from all
sources except the business association membership lists were deemed to be willing. The unique
239 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
240 Hereinafter referred to as Minority and Caucasian female-owned businesses in the statistical tables.
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businesses culled from the business association lists were surveyed for affirmation of their
willingness to contract with MSD.
The first source used to build the availability database was MSD’s utilized businesses, bidders and
listed vendors. Businesses identified from federal and local government certification agencies were
thereafter appended. The certification lists included small, local, minority, woman-owned, and
disadvantaged-owned businesses. The registration list from the business community meetings
were appended to the availability list because the willingness of a business to attend community
meeting was an affirmation of the business’ willingness to contract with MSD. Businesses
identified from trade associations, business organizations and chamber of comm erce membership
lists that affirmed their willingness through the survey were also appended.
B. Prime Contractor Sources
Extensive targeted outreach was undertaken in the market area to identify and secure certification
lists, trade association and business organization membership lists. Table 5.1 lists MSD sources,
certification directories, and business lists used to identify market area businesses.
Table 5.1: Prime Contractor Availability Data Sources
Source Name Type of Information
Metropolitan St. Louis Sewer District Records
Small Contractor Program - 11705 DS MWBE and Non-minority Male
Small Contractor Program - 11771 DS MWBE and Non-minority Male
Small Contractor Program - 11772 DS MWBE and Non-minority Male
Small Contractor Program - 11773 DS MWBE and Non-minority Male
Small Contractor Program - 12007 DS MWBE and Non-minority Male
Small Contractor Program - 12008 DS MWBE and Non-minority Male
Small Contractor Program - STORM_Clean MWBE and Non-minority Male
Total Spend - 2013 thru 2017 - Capital Program Only -2nd Data Set MWBE and Non-minority Male
Small Contractor Program – Contractor list, Contractors tab MWBE and Non-minority Male
Small Contractor Program – Contractor list, Potential tab MWBE and Non-minority Male
Government Certification Directories
Missouri Department of Transportation, Missouri Regional Certification
Committee DBE Directory MWBE and Non-minority Male
Missouri Office of Equal Opportunity, Minority and Woman Owned
Businesses MWBE and Non-minority Male
St. Louis Lambert International Airport Business Diversity
Development MWBE
U.S. Small Business Administration, St. Louis District Office of the
HubZone Program MWBE and Non-minority Male
U.S. Small Business Administration, St. Louis District Office of
Veterans Business Development MWBE and Non-minority Male
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Prime Contractor and Subcontractor Availability Analysis
U.S. Small Business Administration, St. Louis District Office, Small
Disadvantaged Businesses MWBE and Non-minority Male
U.S. Small Business Administration, St. Louis District Office, Office of
Women's Business Development MWBE
U.S. Small Business Administration, St. Louis District Office, 8(a)
Business Development Program MWBE
Business Association Membership Lists
American Concrete Pumping Association MWBE and Non-minority Male
American Council of Engineering Companies of Missouri MWBE and Non-minority Male
American Subcontractors Association - Midwest Council MWBE and Non-minority Male
Associated General Contractors of Missouri MWBE and Non-minority Male
Bi-State Development DBEs St. Louis MSD MWBE and Non-minority Male
Cement Mason Union Local 527 MWBE and Non-minority Male
Concrete Council of St. Louis MWBE and Non-minority Male
Electrical Apparatus Service Association, Inc MWBE and Non-minority Male
Hispanic Chamber of Commerce of Metropolitan St. Louis HCC-STL MWBE and Non-minority Male
Irrigation Association - STL MSD MWBE and Non-minority Male
Landscape and Nursery Association of Greater St. Louis MWBE and Non-minority Male
Lemay Chamber of Commerce MWBE and Non-minority Male
Mason Contractors Association of St. Louis MWBE and Non-minority Male
Mechanical Contractors Association of Eastern Missouri MWBE and Non-minority Male
Missouri Association of Plumbing, Heating and Cooling Contractors MWBE and Non-minority Male
Missouri Concrete Association St. Louis Only MWBE and Non-minority Male
Missouri Green Industry Alliance MWBE and Non-minority Male
Missouri Society of Professional Surveyors, St. Louis Chapter MWBE and Non-minority Male
National Association of Pipe Fabricators MWBE and Non-minority Male
National Concrete Masonry Association MWBE and Non-minority Male
National Precast Concrete Association MWBE and Non-minority Male
National Ready Mixed Concrete Association MWBE and Non-minority Male
Northwest Chamber of Commerce MWBE and Non-minority Male
O’Fallon Chamber of Commerce MWBE and Non-minority Male
Plumbers and Pipefitters 562 MWBE and Non-minority Male
Plumbing Industry Council MWBE and Non-minority Male
Roofing & Siding Contractors Alliance MWBE and Non-minority Male
Sealant and Waterproofing and Restoration Institute MWBE and Non-minority Male
Sheet Metal Workers Local 36 MWBE and Non-minority Male
St Louis Minority Business Council MWBE
St. Louis Fire Sprinkler Alliance MWBE and Non-minority Male
St. Louis Regional Chamber and Growth Association MWBE and Non-minority Male
The American Institute of Architects MWBE and Non-minority Male
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Prime Contractor and Subcontractor Availability Analysis
C. Determination of Willingness
There were 1,447 unique market area businesses identified from the availability sources that
provide goods or services in one or more of the four industries. The enumeration of the willing
businesses derived from each source and added to the availability database, is listed below.
1. MSD Records
A total of 861 unique market area businesses were identified from MSD’s records.
2. Government Certification Lists
A total of 472 unique market area businesses were identified from government certification lists.
3. Business Community Meetings
A total of seven unique market area businesses were identified from the business community
meetings.
4. Business Association Membership Lists
A total of 699 unique businesses, identified from the business association membership lists, were
surveyed to determine their willingness to contract with MSD. From the 699 surveyed businesses,
46 refused to participate, 116 did not respond when contacted, 23 telephone numbers were
disconnected, and 514 businesses completed the survey. Of the 514 businesses that completed the
survey, 149 were willing and provided the goods or services procured by MSD. The 149 were
added to the availability database.
D. Distribution of Available Prime Contractors by Source,
Ethnicity, and Gender
Table 5.2 to Table 5.5 present the distribution of willing prime contractors by source and industry.
As noted in Table 5.2, 71.97% of the building construction businesses identified were derived from
MSD’s records including pre-qualification lists, utilized businesses, bidders and listed vendors and
government certification directories. Companies identified from the community meeting attendee
lists and the business association membership lists represent 27.07% of the willing businesses.
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Prime Contractor and Subcontractor Availability Analysis
Table 5.2: Distribution of Prime Contractor Availability Data Sources,
Building Construction
*The percentages may not total 100% due to rounding.
Table 5.3 lists the data sources for the available non-building construction prime contractors. As
noted, 91.97% of the non-building construction prime contractors identified were derived from
MSD’s records, and government certification directories. Companies identified through the
business association membership lists represent 8.03% of the willing prime contractors.
Table 5.3: Distribution of Prime Contractor Availability Data Sources,
Non-Building Construction
*The percentages may not total 100% due to rounding.
Table 5. 4 lists the data sources for the engineering professional services prime contractors. As
noted, 86.61% of the engineering professional services businesses identified were derived from
the MSD’s records, and government certification directories. Willing companies identified through
the survey of the business association membership lists represent 13.39% of the willing prime
contractors.
Sources MWBEs
Percentage
Non-MWBEs
Percentage
Source
Percentage
Prime Contractor Utilization 4.22%20.27%11.78%
Vendors Lists 5.42%3.38%4.46%
Certification Lists 76.51%11.49%45.86%
Pre-Qualified Firms 3.01%17.57%9.87%
Subtotal 89.16%52.70%71.97%
Community Meeting Attendees 0.60%0.00%0.32%
Willingness Survey 9.64%46.62%27.07%
Business Survey 0.60%0.68%0.64%
Subtotal 10.84%47.30%28.03%
Grand Total*100.00%100.00%100.00%
Sources MWBEs
Percentage
Non-MWBEs
Percentage
Source
Percentage
Prime Contractor Utilization 29.69%63.01%47.45%
Vendors Lists 9.38%0.00%4.38%
Certification Lists 53.13%6.85%28.47%
Pre-Qualified Firms 4.69%17.81%11.68%
Subtotal 96.88%87.67%91.97%
Willingness Survey 1.56%12.33%7.30%
Business Survey 1.56%0.00%0.73%
Subtotal 3.13%12.33%8.03%
Grand Total*100.00%100.00%100.00%
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Prime Contractor and Subcontractor Availability Analysis
Table 5.4: Distribution of Prime Contractor Availability Data Sources,
Engineering Professional Services
*The percentages may not total 100% due to rounding.
Table 5.5 lists the data sources for the available purchases and other services prime contractors.
As noted, 89.94% of the purchases and other services available businesses identified were derived
from the MSD’s records. Willing businesses identified through the survey of the membership lists
represent 10.06% of the willing prime contractors.
Table 5.5: Distribution of Prime Contractor Availability Data Sources,
Purchases and Other Services
*The percentages may not total 100% due to rounding.
III. Capacity
The second component of the availability analysis requirement set forth in Croson is to assess the
capacity or ability of a business to perform the contracts awarded by the government entity.241
Capacity requirements are not delineated in Croson, but capacity has been considered in
subsequent cases. Among the first circuit courts to address capacity was the Third Circuit, which
held certification to be a valid method of defining availability.242 In 1996, Contractors Association
of Eastern Pennsylvania v. City of Philadelphia (Philadelphia), the court held that utilizing a list
241 Croson, 488 U.S. 469.
242 Contractors Ass’n of E. Pa. v. City of Philadelphia (“Philadelphia VI”), 91 F.3d 586, at 603 (3d Cir. 1996).
Sources MWBEs
Percentage
Non-MWBEs
Percentage
Source
Percentage
Prime Contractor Utilization 14.18%39.80%24.69%
Vendors Lists 0.71%0.00%0.42%
Certification Lists 80.85%17.35%54.81%
Pre-Qualified Firms 2.84%12.24%6.69%
Subtotal 98.58%69.39%86.61%
Willingness Survey 0.71%29.59%12.55%
Business Survey 0.71%1.02%0.84%
Subtotal 1.42%30.61%13.39%
Grand Total*100.00%100.00%100.00%
Sources MWBEs
Percentage
Non-MWBEs
Percentage
Source
Percentage
Prime Contractor Utilization 8.33%49.04%22.08%
Vendors Lists 2.94%0.96%2.27%
Certification Lists 83.33%30.77%65.58%
Subtotal 94.61%80.77%89.94%
Willingness Survey 4.41%18.27%9.09%
Business Survey 0.98%0.96%0.97%
Subtotal 5.39%19.23%10.06%
Grand Total*100.00%100.00%100.00%
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Prime Contractor and Subcontractor Availability Analysis
of certified contractors was a rational approach to identify qualified, willing firms.243 The court
stated “[a]n analysis is not devoid of probative value simply because it may theoretically be
possible to adopt a more refined approach [of qualification].”244 As noted in Philadelphia, “[t]he
issue of qualifications can be approached at different levels of specificity[.]”245
Researchers have also attempted to define capacity using US Census data to profile the age of the
business, education of the business owner, business revenue, number of employees, and bonding
limits . Although these conventional socio-economic indices are themselves impacted by race and
gender-based discrimination they also have been considered in analyzing the capacity of the
willing businesses.
Three methods were used to define the capacity of MWBEs as compared to similarly situated non-
minority male-owned businesses:
• A review of the distribution of contracts to determine the size of the contracts that MSD
awarded to MWBEs and non-minority male-owned businesses.
• The identification of the largest contracts awarded to MWBEs.
• An assessment of capacity -related economic factors of MWBEs and non-minority male-
owned businesses using the results of the capacity eSurvey.
In a further effort to address capacity, large contracts that required considerable capacity to
perform were removed from the statistical analysis of disparity. Limiting the range of the formal
prime contracts analyzed ensured that the disparity analysis was not distorted by the presence of
outliers or prime contracts that required a significant capacity to perform.
A. Prime Contract Size Distribution
All of MSD’s prime contracts were ordered by award amount to determine the distribution of the
awarded contacts. The purpose of this distribution was to gauge the capacity required to perform
MSD’s contracts. In Table 5.6, contract awards in the four industries were grouped into nine ranges
and are presented by non-minority females, non-minority males, minority females, and minority
males.
243 Id.
244 Id. at 603; see also, Concrete Works IV, 321 F.3d at 966 (noting a less sophisticated method to calculate availability does not render a disparity
study flawed.)
245 Contractors Ass’n of E. Pa., 91 F.3d at 610.
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Prime Contractor and Subcontractor Availability Analysis
The table indicates that 79.81% of the prime contracts awarded by MSD were valued at less than
$100,000. Additionally, 86.50% were less than $250,000; 90.14% were less than $500,000;
92.76% were less than $1,000,000; and 96.94% were less than $3,000,000. Only 3.06% of the
awarded prime contracts were valued at $3,000,000 and greater.
Table 5.6: All Industry Contracts by Size
January 1, 2013, to December 31, 2017
Chart 5.1: All Industry Contracts by Size
January 1, 2013, to December 31, 2017
Non-minority Minority
Females Males Females Males
Freq Percent Freq Percent Freq Percent Freq Percent Freq Percent
$0 - $4,999 908 33.03%464 16.88%190 6.91%12 0.44%1,574 57.26%
$5,000 - $24,999 168 6.11%170 6.18%8 0.29%51 1.86%397 14.44%
$25,000 - $49,999 13 0.47%68 2.47%7 0.25%19 0.69%107 3.89%
$50,000 - $99,999 10 0.36%77 2.80%9 0.33%20 0.73%116 4.22%
$100,000 - $249,999 16 0.58%126 4.58%11 0.40%31 1.13%184 6.69%
$250,000 - $499,999 11 0.40%76 2.76%3 0.11%10 0.36%100 3.64%
$500,000 - $999,999 3 0.11%62 2.26%3 0.11%4 0.15%72 2.62%
$1,000,000 - $2,999,999 5 0.18%102 3.71%1 0.04%7 0.25%115 4.18%
$3,000,000 and greater 2 0.07%80 2.91%0 0.00%2 0.07%84 3.06%
Total 1,136 41.32%1,225 44.56%232 8.44%156 5.67%2,749 100.00%
Size Total
0.00%
10.00%
20.00%
30.00%
40.00%
$0 - $4,999 $5,000 -
$24,999
$25,000 -
$49,999
$50,000 -
$99,999
$100,000 -
$249,999
$250,000 -
$499,999
$500,000 -
$999,999
$1,000,000 -
$2,999,999
$3,000,000
and greater
Caucasian Females
Non-minority Males
Minority Females
Minority Males
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Prime Contractor and Subcontractor Availability Analysis
The size of MSD’s prime contracts is a determinant of the capacity that a willing business needs
to be competitive at the prime contract level. The fact that more than 79.81% of MSD’s contracts
are valued at less than $100,000 illustrates that the capacity needed to perform a significant number
of MSD’s contracts is not considerable.
B. Largest MWBE Prime Contracts Awarded by Industry
The size of the largest prime contracts that MSD awarded to MWBEs illustrates that MWBEs have
the capacity to perform substantial formal contracts. Table 5.7 indicates that MWBEs
demonstrated the capacity to perform contracts as large as $515,449 in building construction,
$10,408,339 in non-building construction, $20,449,983 in engineering professional services, and
$415,785 in purchases and other services.
Table 5.7: Largest Prime Contracts Awarded by MSD to MWBEs
Ethnicity and
Gender Group
Building
Construction
Non-Building
Construction
Engineering
Professional
Services
Purchases and
Other Services
African American Female ---- $708,999 $1,203,158 ----
African American Male $515,449 $2,056,247 $20,449,983 $415,785
Asian American Female ---- ---- ---- ----
Asian American Male ---- ---- ---- $178,200
Hispanic American Female ---- ---- ---- ----
Hispanic American Male ---- $3,027,792 $125,000 ----
Native American Female ---- ---- ---- ----
Native American Male ---- $391,960 ---- ----
Caucasian Female ---- $10,408,339 $1,156,423 $395,000
Largest Dollar Amounts MBEs $515,449 $3,027,792 $20,449,983 $415,785
Largest Dollar Amounts WBEs $0 $10,408,339 $1,203,158 $395,000
(----) Denotes a group that was not awarded any contracts within the respective industry
C. Formal Contract Threshold Analysis
As a further measure to ensure that the available businesses have the capacity to perform the
contracts analyzed in the disparity analysis, prime contracts subject to the statistical analysis was
limited. As discussed in Chapter 2: Prime Contractor Utilization Analysis, the analysis of formal
contracts was limited to the awarded contracts with a dollar value of $500,000 and under. The
decision to limit the dollar threshold was made to ensure that the disparity analysis was not
distorted by the presence of large prime contracts that required significant capacity to perform.
Therefore, the large contracts were removed from the statistical analysis of prime contract
disparity.
1. Profile of Respondents
Table 5.8 lists the ethnicity and gender of survey respondents. The business capacity survey
respondents were diverse: 37.84% were African American; 3.60% were Asian American; 6.31%
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were Hispanic American; 1.80% were Native American; and 50.45% were Caucasian American.
Of the surveys completed, 46.85% were completed by females of all ethnicities and 53.15% were
completed by males of all ethnicities.
Table 5.8: Ethnicity and Gender of Business Owners
The ethnic groups were combined and analyzed as “minority males” and “minority females.”
Table 5.9 indicates that 16.22% of businesses provided building construction services; 9.91% of
businesses provided non-building construction services; 25.23% of businesses provided
engineering professional services; and 48.65% of businesses provided purchases and other
services.
Table 5.9: Primary Industry of Business
Industry Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
Building Construction 2.70% 6.31% 3.60% 3.60% 16.22%
Non-building Construction 1.80% 3.60% 1.80% 2.70% 9.91%
Engineering Professional
Services 2.70% 10.81% 7.21% 4.50% 25.23%
Purchases and Other
Services 11.71% 9.91% 15.32% 11.71% 48.65%
Total 18.92% 30.63% 27.93% 22.52% 100.00%
2. Capacity Assessment Findings
Table 5.10 lists business annual gross revenue according to nine levels. It shows that 40.74% of
businesses earned $500,000 and under; 14.81% of businesses earned $500,001 to $1,000,000;
12.96% of businesses earned $1,000,001 to $3,000,000; 8.33% of businesses earned $3,000,001
to $5,000,000; 9.26% of businesses earned $5,000,001 to $10,000,000; and 13.89% of businesses
earned over $10 million.
Response African
American
Asian
American
Hispanic
American
Native
American Caucasian Total
Female 17.12%0.90%0.90%0.00%27.93%46.85%
Male 20.72%2.70%5.41%1.80%22.52%53.15%
Total 37.84%3.60%6.31%1.80%50.45%100.00%
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Table 5.10: Annual Gross Revenue
Chart 5.2 illustrates more than half or 55.56%, of businesses earn less than $1,000,000 a year. This
finding indicates that the majority of businesses are small, regardless of the ethnicity or gender of
the owner.
Chart 5.2: Annual Gross Revenue
Revenue Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
Less than $50,000 4.63%4.63%1.85%0.93%12.04%
$50,000 to $100,000 1.85%1.85%1.85%0.00%5.56%
$100,001 to $300,000 5.56%4.63%3.70%2.78%16.67%
$300,001 to $500,000 0.93%2.78%1.85%0.93%6.48%
$500,001 to $1,000,000 0.93%4.63%6.48%2.78%14.81%
$1,000,001 to $3,000,000 2.78%3.70%4.63%1.85%12.96%
$3,000,001 to $5,000,000 0.00%2.78%4.63%0.93%8.33%
$5,000,001 to $10,000,000 0.00%2.78%1.85%4.63%9.26%
More than $10,000,000 0.93%2.78%1.85%8.33%13.89%
Total 17.59%30.56%28.70%23.15%100.00%
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Table 5.11 lists the number of employees at each business within the four groups: minority
females, minority males, Caucasian females, and non-minority males. The findings reveal that
38.83% of business had 0 to 5 employees;246 19.42% had 6 to 10 employees; 8.74% had 11 to 20
employees; 7.77% had 21 to 30 employees; 6.80% had 31 to 50 employees; and 18.45% had more
than 50 employees.
Table 5.11: Number of Employees
Chart 5.3 illustrates that most businesses have fewer than five employees, regardless of the
ethnicity or gender of the owner. Of all businesses, 66.99% are small, employing 20 or fewer
employees. Although the surveyed businesses are small, they are similar to the average St. Louis,
MO-IL metropolitan statistical area (MSA) business, as reported by ReferenceUSA (April 2020).
ReferenceUSA’s data illustrates that 88.32% of businesses in the St. Louis MSA, regardless of
ethnicity and gender, employ 20 or fewer employees.
246 Business owners are not counted as employees.
Number of
Employees
Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
0-5 employees 11.65%13.59%10.68%2.91%38.83%
6-10 employees 1.94%5.83%6.80%4.85%19.42%
11-20 employees 3.88%0.97%1.94%1.94%8.74%
21-30 employees 0.00%2.91%3.88%0.97%7.77%
31-50 employees 1.94%1.94%0.00%2.91%6.80%
Over 50 employees 0.97%4.85%2.91%9.71%18.45%
Total 20.39%30.10%26.21%23.30%100.00%
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Chart 5.3: Number of Employees
One consideration of capacity as discussed in the case law, is a contractor’s ability to bid and
perform multiple contracts.247 This factor relates to the human and capital resources available for
a business to perform multiple contracts, concurrently. Table 5.12 indicates that businesses can
perform multiple concurrent contracts within a calendar year. More than half, or 64.29%, of
businesses responded that they have completed more than five contracts in a calendar year.
Table 5.12: Number of Annual Contracts
247 See Rothe Development Corporation v. U.S. Department of Defense , 262 F.3d 1306 (Fed. Cir. 2001); see also Rothe Development Corporation
v. U.S. Department of Defense, 545 F.3d 1023 (Fed. Cir. 2008).
Annual
Contracts
Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
1 to 5 Contracts 9.52%15.48%5.95%4.76%35.71%
6 to 10 Contracts 2.38%2.38%2.38%1.19%8.33%
11 to 20 Contacts 4.76%3.57%5.95%0.00%14.29%
More than 20 Contracts 2.38%9.52%11.90%17.86%41.67%
Total 19.05%30.95%26.19%23.81%100.00%
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Chart 5.4 illustrates that more than half of the businesses performed multiple contracts within the
previous calendar year. This finding illustrates that the businesses, without regard to ethnicity or
gender, have successfully performed multiple contracts, concurrently.
Chart 5.4: Number of Annual Contracts
Table 5.13 lists the length of time businesses have been in operation. More than half or 51.35%,
of minority-owned, woman-owned, and non-minority male-owned businesses have been in
business from 11 to 50 years, which illustrates that mature businesses comprise the majority of the
available businesses.
Table 5.13: Years in Business
Years in Business Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
Less than 5 years 5.41% 4.50% 3.60% 0.90% 14.41%
6 - 10 years 6.31% 4.50% 6.31% 2.70% 19.82%
11 - 20 years 5.41% 11.71% 7.21% 1.80% 26.13%
21 - 30 years 0.90% 5.41% 6.31% 3.60% 16.22%
31 - 50 years 0.00% 2.70% 2.70% 3.60% 9.01%
More than 50 years 0.90% 1.80% 1.80% 9.91% 14.41%
Total 18.92% 30.63% 27.93% 22.52% 100.00%
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Chart 5.5 illustrates that minority and woman-owned businesses are a growing segment of the
contracting market in comparison to Caucasian males. More businesses less than 20 years old are
minority and woman owned. In contrast businesses 31 or more years are non-minority male owned.
It is important to note, however, that the availability pool includes mature minority and woman -
owned businesses with extensive experience in their respective fields.
Chart 5.5: Years in Business
Table 5.14 lists the educational attainment of business owners. The data indicates that 28.44%
business owners have a bachelor’s degree and minority male business owners earned graduate
level degrees at a higher rate than similarly situated non-minority males.
Table 5.14: Education Level of Business Owners
Education Level Minority
Females
Minority
Males
Caucasian
Females
Non-minority
Males Total
High School Degree or
Equivalent 1.83% 1.83% 5.50% 4.59% 13.76%
Trade/Technical Certificate or
Degree 0.00% 3.67% 1.83% 0.92% 6.42%
Associate Degree 2.75% 0.92% 3.67% 0.92% 8.26%
Bachelor’s degree 3.67% 7.34% 9.17% 8.26% 28.44%
Graduate Degree 10.09% 13.76% 3.67% 3.67% 31.19%
Professional Degree 0.92% 2.75% 4.59% 3.67% 11.93%
Total 19.27% 30.28% 28.44% 22.02% 100.00%
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Chart 5.6 illustrates that the most common degree among business owners is a graduate degree.
This finding indicates that most business owners, regardless of ethnicity and gender, are highly
educated.
Chart 5.6: Educational Attainment
D. Conclusion
The analysis illustrates that among similarly situated minority and woman-owned businesses and
non-minority male-owned businesses, the relative capacity of firms is comparable. Most
businesses enumerated in the availability analysis have the following profile:
• Employ 10 or fewer employees.
• Have gross revenue of $1,000,000 or less.
• Performed multiple public and private contracts concurrently.
• Operated their business for less than 50 years.
• Have a bachelor’s or graduate degree.
The result of the capacity eSurvey is evidence that willing minority and woman-owned businesses
have demonstrated capacity comparable to similarly situated willing non-minority male-owned
businesses. Despite similar educational attainment, years in business, and number of employees,
non-minority male-owned businesses still received most of MSD’s contracts as detailed in Chapter
2: Prime Contractor Utilization Analysis. The capacity analysis indicates that non-minority males
are not awarded more contracts because of any single socioeconomic factor or combination of
factors. Considering the capacity evidence and the finding that non-minority males are awarded
the majority of MSDs large and small contracts, the facts indicate that there is also discrimination
in the private sector.
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IV. Prime Contractor Availability Analysis
The prime contractor availability analysis is based on the 1,278 willing market area businesses
enumerated from the four availability sources described above. T he availability of willing market
area businesses are presented by ethnicity, gender, and industry in the sections below.
A. Building Construction Prime Contractor Availability
The distribution of available building construction prime contractors is summarized in Table 5.15
below.
African Americans account for 29.28% of the building construction prime contractors in MSD’s
market area.
Asian Americans account for 1.59% of the building construction prime contractors in MSD’s
market area.
Hispanic Americans account for 4.78% of the building construction prime contractors in MSD’s
market area.
Native Americans account for 1.27% of the building construction prime contractors in MSD’s
market area.
Caucasian Females account for 16.24% of the building construction prime contractors in MSD’s
market area.
Non-minority Males account for 47.13% of the building construction prime contractors in MSD’s
market area.
Minority-owned Businesses account for 36.62% of the building construction prime contractors in
MSD’s market area.
Woman-owned Businesses248 account for 21.97% of the building construction prime contractors
in MSD’s market area.
248 Ethnic and gender categories have been described in Table 2.1 in Chapter 2: Prime Contractor Utilization Analysis.
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Table 5.15: Available Building Construction Prime Contractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 28.98%
Asian Americans 1.59%
Hispanic Americans 4.78%
Native Americans 1.27%
Caucasian Females 16.24%
Non-minority Males 47.13%
TOTAL 100.00%
Percent
of Businesses
African American Females 4.46%
African American Males 24.52%
Asian American Females 0.32%
Asian American Males 1.27%
Hispanic American Females 0.64%
Hispanic American Males 4.14%
Native American Females 0.32%
Native American Males 0.96%
Caucasian Females 16.24%
Non-minority Males 47.13%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 36.62%
Woman Business Enterprises 21.97%
Minority and Females
Ethnicity
Ethnicity and Gender
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B. Non-Building Construction Prime Contractor Availability
The distribution of available non-building construction prime contractors is summarized in Table
5.16 below.
African Americans account for 27.01% of the non-building construction prime contractors in
MSD’s market area.
Asian Americans account for 0.73% of the non-building construction prime contractors in MSD’s
market area.
Hispanic Americans account for 2.92% of the non-building construction prime contractors in
MSD’s market area.
Native Americans account for 0.73% of the non-building construction prime contractors in MSD’s
market area.
Caucasian Females account for 15.33% of the non-building construction prime contractors in
MSD’s market area.
Non-minority Males account for 53.28% of the non-building construction prime contractors in
MSD’s market area.
Minority-owned Businesses account for 31.39% of the non-building construction prime
contractors in MSD’s market area.
Woman-owned Businesses account for 19.71% of the non-building construction prime contractors
in MSD’s market area.
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Table 5.16: Available Non-Building Construction Prime Contractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 27.01%
Asian Americans 0.73%
Hispanic Americans 2.92%
Native Americans 0.73%
Caucasian Females 15.33%
Non-minority Males 53.28%
TOTAL 100.00%
Percent
of Businesses
African American Females 4.38%
African American Males 22.63%
Asian American Females 0.00%
Asian American Males 0.73%
Hispanic American Females 0.00%
Hispanic American Males 2.92%
Native American Females 0.00%
Native American Males 0.73%
Caucasian Females 15.33%
Non-minority Males 53.28%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 31.39%
Woman Business Enterprises 19.71%
Minority and Females
Ethnicity
Ethnicity and Gender
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C. Engineering Professional Services Prime Contractor
Availability
The distribution of available engineering professional services prime contractors is summarized in
Table 5.17 below.
African Americans account for 20.92% of the engineering professional services prime contractors
in MSD’s market area.
Asian Americans account for 6.69% of the engineering professional services prime contractors in
MSD’s market area.
Hispanic Americans account for 5.86% of the engineering professional services prime contractors
in MSD’s market area.
Native Americans account for 2.09% of the engineering professional services prime contractors
in MSD’s market area.
Caucasian Females account for 23.43% of the engineering professional services prime contractors
in MSD’s market area.
Non-minority Males account for 41.00% of the engineering professional services prime
contractors in MSD’s market area.
Minority-owned Businesses account for 35.56% of the engineering professional services prime
contractors in MSD’s market area.
Woman-owned Businesses account for 33.47% of the engineering professional services prime
contractors in MSD’s market area.
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Table 5.17: Available Engineering Professional Services Prime Contractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 20.92%
Asian Americans 6.69%
Hispanic Americans 5.86%
Native Americans 2.09%
Caucasian Females 23.43%
Non-minority Males 41.00%
TOTAL 100.00%
Percent
of Businesses
African American Females 5.44%
African American Males 15.48%
Asian American Females 2.51%
Asian American Males 4.18%
Hispanic American Females 1.26%
Hispanic American Males 4.60%
Native American Females 0.84%
Native American Males 1.26%
Caucasian Females 23.43%
Non-minority Males 41.00%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 35.56%
Woman Business Enterprises 33.47%
TOTAL 100.00%
Minority and Females
Ethnicity
Ethnicity and Gender
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D. Purchases and Other Services Prime Contractor Availability
The distribution of available purchases and other services prime contractors is summarized in
Table 5.18 below.
African Americans account for 31.82% of the purchases and other services prime contractors in
MSD’s market area.
Asian Americans account for 3.57% of the purchases and other services prime contractors in
MSD’s market area.
Hispanic Americans account for 4.22% of the purchases and other services prime contractors in
MSD’s market area.
Native Americans account for 1.95% of the purchases and other services prime contractors in
MSD’s market area.
Caucasian Females account for 24.68% of the purchases and other services prime contractors in
MSD’s market area.
Non-minority Males account for 33.77% of the purchases and other services prime contractors in
MSD’s market area.
Minority-owned Businesses account for 41.56% of the purchases and other services prime
contractors in MSD’s market area.
Woman-owned Businesses account for 38.31% of the purchases and other services prime
contractors in MSD’s market area.
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Table 5.18: Available Purchases and Other Services Prime Contractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 31.82%
Asian Americans 3.57%
Hispanic Americans 4.22%
Native Americans 1.95%
Caucasian Females 24.68%
Non-minority Males 33.77%
TOTAL 100.00%
Percent
of Businesses
African American Females 10.39%
African American Males 21.43%
Asian American Females 0.97%
Asian American Males 2.60%
Hispanic American Females 0.97%
Hispanic American Males 3.25%
Native American Females 1.30%
Native American Males 0.65%
Caucasian Females 24.68%
Non-minority Males 33.77%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 41.56%
Woman Business Enterprises 38.31%
Minority and Females
Ethnicity
Ethnicity and Gender
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V. Subcontractor Availability Analysis
A. Source of Willing and Able Subcontractors
Subcontractor availability was comprised of the utilized subcontractors and the businesses in the
prime availability dataset that provided services similar to the subcontract services included in the
subcontractor utilization analysis.
B. Building Construction Subcontractor Availability
The distribution of available building construction subcontractors is summarized in Table 5.20
below.
African Americans account for 35.77% of the building construction subcontractors in the MSD’s
market area.
Asian Americans account for 3.16% of the building construction subcontractors in the MSD’s
market area.
Hispanic Americans account for 4.62% of the building construction subcontractors in the MSD’s
market area.
Native Americans account for 1.09% of the building construction subcontractors in the MSD’s
market area.
Caucasian Females account for 19.22% of the building construction subcontractors in the MSD’s
market area.
Non-minority Males account for 36.13% of the building construction subcontractors in the MSD’s
market area.
Minority-owned Businesses account for 44.65% of the building construction subcontractors in the
MSD’s market area.
Woman-owned Businesses account for 29.93% of the building construction subcontractors in the
MSD’s market area.
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Table 5.19: Available Building Construction Subcontractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 35.77%
Asian Americans 3.16%
Hispanic Americans 4.62%
Native Americans 1.09%
Caucasian Females 19.22%
Non-minority Males 36.13%
TOTAL 100.00%
Percent
of Businesses
African American Females 8.27%
African American Males 27.49%
Asian American Females 0.85%
Asian American Males 2.31%
Hispanic American Females 0.97%
Hispanic American Males 3.65%
Native American Females 0.61%
Native American Males 0.49%
Caucasian Females 19.22%
Non-minority Males 36.13%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 44.65%
Woman Business Enterprises 29.93%
Minority and Females
Ethnicity
Ethnicity and Gender
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C. Non-Building Construction Subcontractor Availability
The distribution of available non-building construction subcontractors is summarized in Table 5.21
below.
African Americans account for 31.20% of the non-building construction subcontractors in the
MSD’s market area.
Asian Americans account for 3.11% of the non-building construction subcontractors in the MSD’s
market area.
Hispanic Americans account for 3.91% of the non-building construction subcontractors in the
MSD’s market area.
Native Americans account for 0.98% of the non-building construction subcontractors in the
MSD’s market area.
Caucasian Females account for 17.69% of the non-building construction subcontractors in the
MSD’s market area.
Non-minority Males account for 43.11% of the non-building construction subcontractors in the
MSD’s market area.
Minority-owned Businesses account for 39.20% of the non-building construction subcontractors
in the MSD’s market area.
Woman-owned Businesses account for 27.82% of the non-building construction subcontractors in
the MSD’s market area.
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Table 5.20: Available Non-building Construction Subcontractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 31.20%
Asian Americans 3.11%
Hispanic Americans 3.91%
Native Americans 0.98%
Caucasian Females 17.69%
Non-minority Males 43.11%
TOTAL 100.00%
Percent
of Businesses
African American Females 7.73%
African American Males 23.47%
Asian American Females 0.98%
Asian American Males 2.13%
Hispanic American Females 0.89%
Hispanic American Males 3.02%
Native American Females 0.53%
Native American Males 0.44%
Caucasian Females 17.69%
Non-minority Males 43.11%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 39.20%
Woman Business Enterprises 27.82%
Minority and Females
Ethnicity
Ethnicity and Gender
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D. Engineering Professional Services Subcontractor Availability
The distribution of available engineering professional services subcontractors is summarized in
Table 5.22 below.
African Americans account for 36.39% of the engineering professional services subcontractors in
the MSD’s market area.
Asian Americans account for 4.99% of the engineering professional services subcontractors in the
MSD’s market area.
Hispanic Americans account for 5.31% of the engineering professional services subcontractors in
the MSD’s market area.
Native Americans account for 1.45% of the engineering professional services subcontractors in
the MSD’s market area.
Caucasian Females account for 26.73% of the engineering professional services subcontractors
in the MSD’s market area.
Non-minority Males account for 25.12% of the engineering professional services subcontractors
in the MSD’s market area.
Minority-owned Businesses account for 48.15% of the engineering professional services
subcontractors in the MSD’s market area.
Woman-owned Businesses account for 42.35% of the engineering professional services
subcontractors in the MSD’s market area.
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Table 5.21: Available Engineering Professional Services Subcontractors
January 1, 2013, to December 31, 2017
Percent
of Businesses
African Americans 36.39%
Asian Americans 4.99%
Hispanic Americans 5.31%
Native Americans 1.45%
Caucasian Females 26.73%
Non-minority Males 25.12%
TOTAL 100.00%
Percent
of Businesses
African American Females 11.92%
African American Males 24.48%
Asian American Females 1.93%
Asian American Males 3.06%
Hispanic American Females 0.97%
Hispanic American Males 4.35%
Native American Females 0.81%
Native American Males 0.64%
Caucasian Females 26.73%
Non-minority Males 25.12%
TOTAL 100.00%
Percent
of Businesses
Minority Business Enterprises 48.15%
Woman Business Enterprises 42.35%
Minority and Females
Ethnicity
Ethnicity and Gender
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VI. Summary
This chapter presented the enumeration of willing and able market area businesses by ethnicity,
gender, and industry. The capacity of the enumerated businesses was assessed using four methods:
(1) A review of the MSD’s contract size distribution, to identify the capacity needed to perform
most MSD contracts; (2) A determination of the largest contracts MSD awarded to MWBEs to
illustrate the capacity within the dataset of available businesses; (3) A threshold analysis that
defined the formal contracts with a dollar value $500,000 and under to ensure that the disparity
analysis was not distorted by the presence of prime contracts that required significant capacity to
perform; and (4) A business capacity analysis that assessed relevant socioeconomic factors that
defined the socioeconomic profile of MWBEs and similarly situated non-minority males.
The findings from these analyses illustrate that most of MSD’s prime contracts were relatively
small. Furthermore, the findings demonstrate the available MWBEs have a socioeconomic profile
comparable to similarly situated non-minority male-owned businesses and demonstrated capacity
to perform large MSD contracts. In the availability dataset minority-owned businesses account for
39.37% of building construction, non-building construction, engineering professional services,
and purchases and other services prime contractors. Caucasian female-owned businesses account
for 21.25% and non-minority male-owned business account for 39.37%.
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CHAPTER 6: Prime Contract Disparity
Analysis
I. Introduction
The objective of this chapter is to determine if available Minority and Woman-owned Business
Enterprise (MWBE) contractors were underutilized on Metropolitan St. Louis Sewer District
(MSD) prime contracts during the January 1, 2013, to December 31, 2017 study period. Under a
fair and equitable system of awarding prime contracts, the proportion of prime contract dollars
awarded to MWBEs should be relatively close to the corresponding proportion of available
MWBEs249 in the relevant market area. If the ratio of utilized MWBE prime contractors compared
to available MWBE prime contractors is less than one, a statistical test is conducted to calculate
the probability of observing the empirical disparity ratio. This analysis assumes a fair and equitable
system.250 City of Richmond v. J.A. Croson Co. (Croson)251 states that an inference of discrimination
can be made if the disparity is statistically significant. Under the Croson standard, non-minority
male-owned businesses (non-minority males) are not subjected to a statistical test of
underutilization.
The first step in conducting the statistical test is to calculate the contract dollars that each ethnic
and gender group is expected to receive. This value is based on each group’s availability in the
market area and shall be referred to as the expected contract amount. The next step is to compute
the difference between each ethnic and gender group’s expected contract amount and the actual
contract amount received by each group. The disparity ratio is then calculated by dividing the
actual contract amount by the expected contract amount.
For parametric and non-parametric analyses, the p-value considers the number of contracts,
amount of contract dollars, and variation in contract dollars. If the difference between the actual
and expected number of contracts and total contract dollars has a p-value equal to or less than 0.05,
the difference is statistically significant.252
In the simulation analysis, the p-value considers a combination of the distribution formulated
from the empirical data and the contract dollar amounts. If the actual contract dollar amount, or
actual contract rank, falls below the fifth percentile of the distribution, it denotes a p -value less
than 0.05.
249 Availability is defined as the number of ready, willing, and able firms. The methodology for determining willing and able firms is detailed in
Chapter 5: Prime Contractor and Subcontractor Availability Analysis.
250 When conducting statistical tests, a confidence level must be established as a gauge for the level of certainty t hat an observed occurrence is not
due to chance. It is important to note that a 100% confidence level, or a level of absolute certainty, can never be obtained in statistics. A 95%
confidence level is the statistical standard used in physical and social sciences, and is thus used in the present report to determine if an inference
of discrimination can be made.
251 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
252 This study does not statistically test the overutilization of minority or gender groups or the underutilization of non-minority males.
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Our statistical model employs all three steps simultaneously to each industry. Findings from one
of the three methods are reported. If the p-value from any one of the three methods is less than
0.05, the finding is reported in the disparity tables as statistically significant. If the p-value is
greater than 0.05, the finding is reported as not statistically significant.
II. Disparity Analysis
A prime contract disparity analysis was performed on contracts awarded in the building
construction, non-building construction, engineering professional services, and purchases and
other services industries during the January 1, 2013, to December 31, 2017 study period. The
informal thresholds were defined according to the MSD’s procurement policies. MSD did not
award any building construction contracts valued under $25,000 during the study period. The
informal thresholds for each industry are listed in Table 6.1.
Table 6.1: Informal Thresholds for Analysis by Industry
Industry Informal Contract Threshold
Non-Building Construction Under $25,000
Engineering Professional Services Under $25,000
Purchases and Other Services Under $25,000
The formal contract threshold, as defined in MSD’s purchasing policy, is $25,000 and greater.
However, to ensure that the disparity analysis was not distorted by the presence of prime contracts
that required significant capacity to perform, the formal contract size threshold was set at $500,000
and under. Since MSD did not award any building construction contracts valued at $500,000 and
under during the study period, the threshold for that industry is $25,000 to $8,270,000. The
statistical analysis performed to define the formal contract thresholds analyzed is discussed in
Chapter 2: Prime Contractor Utilization Analysis. The formal contract thresholds for each industry
are listed in Table 6.2.
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Table 6.2: Formal Contract Thresholds for Analysis by Industry
Industry Formal Contract Threshold
Building Construction $25,000 to $8,270,000
Non-Building Construction $25,000 to $500,000
Engineering Professional Services $25,000 to $500,000
Purchases and Other Services $25,000 to $500,000
The findings from the methods employed to calculate statistical significance, as discussed on page
6-1, are presented in the subsequent sections. The outcomes of the statistical analyses are presented
in the “p-value” column of the tables. A description of these statistical outcomes, as shown in the
disparity tables, is presented below in Table 6.3.
Table 6.3: Statistical Outcome Descriptions
P-Value Outcome Definition of P-Value Outcome
< 0.05 * This underutilization is statistically significant.
not significant
• MWBEs: This underutilization is not statistically significant.
• Non-minority males: This overutilization is not statistically
significant.
< 0.05 † This overutilization is statistically significant.
---- While this group was underutilized, there were too few available firms
to determine statistical significance.
** This study does not statistically test the overutilization of minority or
gender groups or the underutilization of non-minority males.
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A. Disparity Analysis: Informal Prime Contracts by Industry
MSD’s disparity analysis for informal prime contracts is presented below.
1. Non-Building Construction Prime Contracts Valued under $25,000
The disparity analysis of non-building construction prime contracts valued under $25,000 is
described below and shown in Table 6.4 and Chart 6.1.
African Americans represent 27.01% of the available non-building construction businesses and
received 21.38% of the dollars on non-building construction contracts valued under $25,000. This
underutilization is statistically significant.
Asian Americans represent 0.73% of the available non-building construction businesses and
received 0.00% of the dollars on non-building construction contracts valued under $25,000. While
this group was underutilized, there were too few available firms to determine statistical
significance.
Hispanic Americans represent 2.92% of the available non-building construction businesses and
received 0.69% of the dollars on non-building construction contracts valued under $25,000. This
underutilization is statistically significant.
Native Americans represent 0.73% of the available non-building construction businesses and
received 0.61% of the dollars on non-building construction contracts valued under $25,000. While
this group was underutilized, there were too few available firms to determine statistical
significance.
Caucasian Females represent 15.33% of the available non-building construction businesses and
received 10.56% of the dollars on non-building construction contracts valued under $25,000. This
underutilization is statistically significant.
Non-minority Males represent 53.28% of the available non-building construction businesses and
received 66.76% of dollars on non-building construction contracts valued under $25,000. This
overutilization is statistically significant.
Minority-owned Businesses represent 31.39% of the available non-building construction
businesses and received 22.68% of the dollars on non-building construction contracts valued under
$25,000. This underutilization is statistically significant.
Woman-owned Businesses253 represent 19.71% of the available non-building construction
businesses and received 13.57% of dollars on non-building construction contracts valued under
$25,000. This underutilization is statistically significant.
253 Ethnic and gender categories have been described in Table 2.1 in Chapter 2: Prime Contractor Utilization Analysis.
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Table 6.4: Disparity Analysis: Non-Building Construction Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $587,640 21.38%27.01%$742,350 -$154,710 0.79 < .05 *
Asian Americans $0 0.00%0.73%$20,064 -$20,064 0.00 ----
Hispanic Americans $18,968 0.69%2.92%$80,254 -$61,286 0.24 < .05 *
Native Americans $16,850 0.61%0.73%$20,064 -$3,214 0.84 ----
Caucasian Females $290,345 10.56%15.33%$421,334 -$130,989 0.69 < .05 *
Non-minority Males $1,834,900 66.76%53.28%$1,464,637 $370,263 1.25 < .05 †
TOTAL $2,748,702 100.00%100.00%$2,748,702
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $82,729 3.01%4.38%$120,381 -$37,652 0.69 not significant
African American Males $504,911 18.37%22.63%$621,969 -$117,058 0.81 not significant
Asian American Females $0 0.00%0.00%$0 $0 --------
Asian American Males $0 0.00%0.73%$20,064 -$20,064 0.00 ----
Hispanic American Females $0 0.00%0.00%$0 $0 --------
Hispanic American Males $18,968 0.69%2.92%$80,254 -$61,286 0.24 < .05 *
Native American Females $0 0.00%0.00%$0 $0 --------
Native American Males $16,850 0.61%0.73%$20,064 -$3,214 0.84 ----
Caucasian Females $290,345 10.56%15.33%$421,334 -$130,989 0.69 < .05 *
Non-minority Males $1,834,900 66.76%53.28%$1,464,637 $370,263 1.25 < .05 †
TOTAL $2,748,702 100.00%100.00%$2,748,702
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $623,458 22.68%31.39%$862,731 -$239,274 0.72 < .05 *
Woman Business Enterprises $373,073 13.57%19.71%$541,715 -$168,642 0.69 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 6.1: Disparity Analysis: Non-Building Construction Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
$0
$200,000
$400,000
$600,000
$800,000
$1,000,000
$1,200,000
$1,400,000
$1,600,000
$1,800,000
$2,000,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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2. Engineering Professional Services Prime Contracts Valued under
$25,000
The disparity analysis of engineering professional services prime contracts valued under $25,000
is described below and shown in Table 6.5 and Chart 6.2.
African Americans represent 20.92% of the available engineering professional services businesses
and received 73.49% of the dollars on engineering professional services contracts valued under
$25,000. This study does not statistically test the overutilization of minority or gender groups.
Asian Americans represent 6.69% of the available engineering professional services businesses
and received 0.00% of the dollars on engineering professional services contracts valued under
$25,000. This underutilization is statistically significant.
Hispanic Americans represent 5.86% of the available engineering professional services
businesses and received 0.00% of the dollars on engineering professional services contracts valued
under $25,000. This underutilization is statistically significant.
Native Americans represent 2.09% of the available engineering professional services businesses
and received 0.00% of the dollars on engineering professional services contracts valued under
$25,000. This underutilization is statistically significant.
Caucasian Females represent 23.43% of the available engineering professional services
businesses and received 5.90% of the dollars on engineering professional services contracts valued
under $25,000. This underutilization is statistically significant.
Non-minority Males represent 41.00% of the available engineering professional services
businesses and received 20.62% of dollars on engineering professional services contracts valued
under $25,000. This study does not statistically test the underutilization of non-minority males.
Minority-owned Businesses represent 35.56% of the available engineering professional services
businesses and received 73.49% of dollars on engineering professional services contracts valued
under $25,000. This study does not statistically test the overutilization of minority or gender
groups.
Woman-owned Businesses represent 33.47% of the available engineering professional services
businesses and received 79.38% of dollars on engineering professional services contracts valued
under $25,000. This study does not statistically test the overutilization of minority or gender
groups.
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Table 6.5: Disparity Analysis: Engineering Professional Services Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $263,868 73.49%20.92%$75,118 $188,750 3.51 **
Asian Americans $0 0.00%6.69%$24,038 -$24,038 0.00 < .05 *
Hispanic Americans $0 0.00%5.86%$21,033 -$21,033 0.00 < .05 *
Native Americans $0 0.00%2.09%$7,512 -$7,512 0.00 < .05 *
Caucasian Females $21,169 5.90%23.43%$84,132 -$62,963 0.25 < .05 *
Non-minority Males $74,028 20.62%41.00%$147,232 -$73,204 0.50 **
TOTAL $359,065 100.00%100.00%$359,065
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $263,868 73.49%5.44%$19,531 $244,337 13.51 **
African American Males $0 0.00%15.48%$55,587 -$55,587 0.00 < .05 *
Asian American Females $0 0.00%2.51%$9,014 -$9,014 0.00 < .05 *
Asian American Males $0 0.00%4.18%$15,024 -$15,024 0.00 < .05 *
Hispanic American Females $0 0.00%1.26%$4,507 -$4,507 0.00 ----
Hispanic American Males $0 0.00%4.60%$16,526 -$16,526 0.00 < .05 *
Native American Females $0 0.00%0.84%$3,005 -$3,005 0.00 ----
Native American Males $0 0.00%1.26%$4,507 -$4,507 0.00 ----
Caucasian Females $21,169 5.90%23.43%$84,132 -$62,963 0.25 < .05 *
Non-minority Males $74,028 20.62%41.00%$147,232 -$73,204 0.50 **
TOTAL $359,065 100.00%100.00%$359,065
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $263,868 73.49%35.56%$127,701 $136,167 2.07 **
Woman Business Enterprises $285,037 79.38%33.47%$120,189 $164,848 2.37 **
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 6.2: Disparity Analysis: Engineering Professional Services Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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3. Purchases and Other Services Prime Contracts Valued under $25,000
The disparity analysis of purchases and other services prime contracts valued under $25,000 is
described below and shown in Table 6.6 and Chart 6.3.
African Americans represent 31.82% of the available purchases and other services businesses and
received 3.88% of the dollars on purchases and other services contracts valued under $25,000.
This underutilization is statistically significant.
Asian Americans represent 3.57% of the available purchases and other services businesses and
received 0.16% of the dollars on purchases and other services contracts valued under $25,000.
This underutilization is statistically significant.
Hispanic Americans represent 4.22% of the available purchases and other services businesses and
received 0.00% of the dollars on purchases and other services contracts valued under $25,000.
This underutilization is statistically significant.
Native Americans represent 1.95% of the available purchases and other services businesses and
received 0.00% of the dollars on purchases and other services contracts valued under $25,000.
This underutilization is statistically significant.
Caucasian Females represent 24.68% of the available purchases and other services businesses
and received 74.32% of the dollars on purchases and other services contracts valued under
$25,000. This study does not statistically test the overutilization of minority or gender groups.
Non-minority Males represent 33.77% of the available purchases and other services businesses
and received 21.64% of dollars on purchases and other services contracts valued under $25,000.
This study does not statistically test the underutilization of non-minority males.
Minority-owned Businesses represent 41.56% of the available purchases and other services
businesses and received 4.03% of dollars on purchases and other services contracts valued under
$25,000. This underutilization is statistically significant.
Woman-owned Businesses represent 38.31% of the available purchases and other services
businesses and received 74.32% of dollars on purchases and other services contracts valued under
$25,000. This study does not statistically test the overutilization of minority or gender groups.
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Table 6.6: Disparity Analysis: Purchases and Other Services Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $126,602 3.88%31.82%$1,038,555 -$911,953 0.12 < .05 *
Asian Americans $5,100 0.16%3.57%$116,573 -$111,473 0.04 < .05 *
Hispanic Americans $0 0.00%4.22%$137,768 -$137,768 0.00 < .05 *
Native Americans $0 0.00%1.95%$63,585 -$63,585 0.00 < .05 *
Caucasian Females $2,425,912 74.32%24.68%$805,410 $1,620,502 3.01 **
Non-minority Males $706,416 21.64%33.77%$1,102,140 -$395,724 0.64 **
TOTAL $3,264,031 100.00%100.00%$3,264,031
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $0 0.00%10.39%$339,120 -$339,120 0.00 < .05 *
African American Males $126,602 3.88%21.43%$699,435 -$572,833 0.18 < .05 *
Asian American Females $0 0.00%0.97%$31,793 -$31,793 0.00 ----
Asian American Males $5,100 0.16%2.60%$84,780 -$79,680 0.06 < .05 *
Hispanic American Females $0 0.00%0.97%$31,793 -$31,793 0.00 ----
Hispanic American Males $0 0.00%3.25%$105,975 -$105,975 0.00 < .05 *
Native American Females $0 0.00%1.30%$42,390 -$42,390 0.00 < .05 *
Native American Males $0 0.00%0.65%$21,195 -$21,195 0.00 ----
Caucasian Females $2,425,912 74.32%24.68%$805,410 $1,620,502 3.01 **
Non-minority Males $706,416 21.64%33.77%$1,102,140 -$395,724 0.64 **
TOTAL $3,264,031 100.00%100.00%$3,264,031
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $131,702 4.03%41.56%$1,356,480 -$1,224,778 0.10 < .05 *
Woman Business Enterprises $2,425,912 74.32%38.31%$1,250,505 $1,175,407 1.94 **
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 6.3: Disparity Analysis: Purchases and Other Services Prime Contracts Valued under $25,000,
January 1, 2013, to December 31, 2017
$0
$500,000
$1,000,000
$1,500,000
$2,000,000
$2,500,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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B. Disparity Analysis: Formal Prime Contracts, by Industry
MSD’s disparity analysis for formal prime contracts is presented below.
1. Building Construction Prime Contracts Valued $25,000 to $8,270,000
The disparity analysis of building construction prime contracts valued from $25,000 to $8,270,000
is described below and shown in Table 6.7 and Chart 6.4.
African Americans represent 28.98% of the available building construction businesses and
received 4.44% of the dollars on building construction contracts valued $25,000 to $8,270,000.
This underutilization is not statistically significant.
Asian Americans represent 1.59% of the available building construction businesses and received
0.00% of the dollars on building construction contracts valued $25,000 to $8,270,000. While this
group was underutilized, there were too few available firms to determine statistical significance.
Hispanic Americans represent 4.78% of the available building construction businesses and
received 0.00% of the dollars on building construction contracts valued $25,000 to $8,270,000.
While this group was underutilized, there were too few available firms to determine statistical
significance.
Native Americans represent 1.27% of the available building construction businesses and received
0.00% of the dollars on building construction contracts valued $25,000 to $8,270,000. While this
group was underutilized, there were too few available firms to determine statistical significance.
Caucasian Females represent 16.24% of the available building construction businesses and
received 0.00% of the dollars on building construction contracts valued $25,000 to $8,270,000.
While this group was underutilized, there were too few available firms t o determine statistical
significance.
Non-minority Males represent 47.13% of the available building construction businesses and
received 95.56% of the dollars on building construction contracts valued $25,000 to $8,270,000.
This overutilization is statistically significant.
Minority-owned Businesses represent 36.62% of the available building construction businesses
and received 4.44% of the dollars on building construction contracts valued $25,000 to $8,270,000.
This underutilization is not statistically significant.
Woman-owned Businesses represent 21.97% of the available building construction businesses and
received 0.00% of the dollars on building construction contracts valued $25,000 to $8,270,000.
While this group was underutilized, there were too few available firms to determine statistical
significance.
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Table 6.7: Disparity Analysis: Building Construction Prime Contracts Valued $25,000 to $8,270,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $515,449 4.44%28.98%$3,361,132 -$2,845,683 0.15 not significant
Asian Americans $0 0.00%1.59%$184,678 -$184,678 0.00 ----
Hispanic Americans $0 0.00%4.78%$554,033 -$554,033 0.00 ----
Native Americans $0 0.00%1.27%$147,742 -$147,742 0.00 ----
Caucasian Females $0 0.00%16.24%$1,883,711 -$1,883,711 0.00 ----
Non-minority Males $11,082,304 95.56%47.13%$5,466,457 $5,615,847 2.03 < .05 †
TOTAL $11,597,753 100.00%100.00%$11,597,753
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $0 0.00%4.46%$517,097 -$517,097 0.00 ----
African American Males $515,449 4.44%24.52%$2,844,035 -$2,328,586 0.18 not significant
Asian American Females $0 0.00%0.32%$36,936 -$36,936 0.00 ----
Asian American Males $0 0.00%1.27%$147,742 -$147,742 0.00 ----
Hispanic American Females $0 0.00%0.64%$73,871 -$73,871 0.00 ----
Hispanic American Males $0 0.00%4.14%$480,162 -$480,162 0.00 ----
Native American Females $0 0.00%0.32%$36,936 -$36,936 0.00 ----
Native American Males $0 0.00%0.96%$110,807 -$110,807 0.00 ----
Caucasian Females $0 0.00%16.24%$1,883,711 -$1,883,711 0.00 ----
Non-minority Males $11,082,304 95.56%47.13%$5,466,457 $5,615,847 2.03 < .05 †
TOTAL $11,597,753 100.00%100.00%$11,597,753
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $515,449 4.44%36.62%$4,247,585 -$3,732,135 0.12 not significant
Woman Business Enterprises $0 0.00%21.97%$2,548,551 -$2,548,551 0.00 ----
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Prime Contract Disparity Analysis
Chart 6.4: Disparity Analysis: Building Construction Prime Contracts Valued $25,000 to $8,270,000,
January 1, 2013, to December 31, 2017
$0
$2,000,000
$4,000,000
$6,000,000
$8,000,000
$10,000,000
$12,000,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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Prime Contract Disparity Analysis
2. Non-Building Construction Prime Contracts Valued $25,000 to
$500,000
The disparity analysis of non-building construction prime contracts valued $25,000 to $500,000 is
described below and shown in Table 6.8 and Chart 6.5.
African Americans represent 27.01% of the available non-building construction businesses and
received 14.15% of the dollars on non-building construction contracts valued $25,000 to $500,000.
This underutilization is statistically significant.
Asian Americans represent 0.73% of the available non-building construction businesses and
received 0.00% of the dollars on non-building construction contracts valued $25,000 to $500,000.
While this group was underutilized, there were too few available firms to determine statistical
significance.
Hispanic Americans represent 2.92% of the available non-building construction businesses and
received 1.62% of the dollars on non-building construction contracts valued $25,000 to $500,000.
This underutilization is not statistically significant.
Native Americans represent 0.73% of the available non-building construction businesses and
received 0.92% of the dollars on non-building construction contracts valued $25,000 to $500,000.
This study does not statistically test the overutilization of minority or gender groups.
Caucasian Females represent 15.33% of the available non-building construction businesses and
received 9.80% of the dollars on non-building construction contracts valued $25,000 to $500,000.
This underutilization is statistically significant.
Non-minority Males represent 53.28% of the available non-building construction businesses and
received 73.50% of the dollars on non-building construction contracts valued $25,000 to $500,000.
This overutilization is statistically significant.
Minority-owned Businesses represent 31.39% of the available non-building construction
businesses and received 16.69% of the dollars on non-building construction contracts valued
$25,000 to $500,000. This underutilization is statistically significant.
Woman-owned Businesses represent 19.71% of the available non-building construction
businesses and received 15.31% of the dollars on non-building construction contracts valued
$25,000 to $500,000. This underutilization is statistically significant.
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Prime Contract Disparity Analysis
Table 6.8: Disparity Analysis: Non-Building Construction Prime Contracts Valued from $25,000 to $500,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $8,974,483 14.15%27.01%$17,131,821 -$8,157,339 0.52 < .05 *
Asian Americans $0 0.00%0.73%$463,022 -$463,022 0.00 ----
Hispanic Americans $1,030,594 1.62%2.92%$1,852,089 -$821,495 0.56 not significant
Native Americans $583,766 0.92%0.73%$463,022 $120,744 1.26 **
Caucasian Females $6,219,064 9.80%15.33%$9,723,466 -$3,504,402 0.64 < .05 *
Non-minority Males $46,626,134 73.50%53.28%$33,800,620 $12,825,514 1.38 < .05 †
TOTAL $63,434,041 100.00%100.00%$63,434,041
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $3,491,186 5.50%4.38%$2,778,133 $713,053 1.26 **
African American Males $5,483,296 8.64%22.63%$14,353,688 -$8,870,392 0.38 < .05 *
Asian American Females $0 0.00%0.00%$0 $0 --------
Asian American Males $0 0.00%0.73%$463,022 -$463,022 0.00 ----
Hispanic American Females $0 0.00%0.00%$0 $0 --------
Hispanic American Males $1,030,594 1.62%2.92%$1,852,089 -$821,495 0.56 not significant
Native American Females $0 0.00%0.00%$0 $0 --------
Native American Males $583,766 0.92%0.73%$463,022 $120,744 1.26 **
Caucasian Females $6,219,064 9.80%15.33%$9,723,466 -$3,504,402 0.64 < .05 *
Non-minority Males $46,626,134 73.50%53.28%$33,800,620 $12,825,514 1.38 < .05 †
TOTAL $63,434,041 100.00%100.00%$63,434,041
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $10,588,843 16.69%31.39%$19,909,955 -$9,321,112 0.53 < .05 *
Woman Business Enterprises $9,710,251 15.31%19.71%$12,501,599 -$2,791,349 0.78 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Prime Contract Disparity Analysis
Chart 6.5: Disparity Analysis: Non-Building Construction Prime Contracts Valued from $25,000 to $500,000,
January 1, 2013, to December 31, 2017
$0
$5,000,000
$10,000,000
$15,000,000
$20,000,000
$25,000,000
$30,000,000
$35,000,000
$40,000,000
$45,000,000
$50,000,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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Prime Contract Disparity Analysis
3. Engineering Professional Services Prime Contracts Valued from
$25,000 to $500,000
The disparity analysis of engineering professional services prime contracts valued from $25,000
to $500,000 is described below and shown in Table 6.9 and Chart 6.6.
African Americans represent 20.92% of the available engineering professional services businesses
and received 16.65% of the dollars on engineering professional services contracts valued from
$25,000 to $500,000. This underutilization is not statistically significant.
Asian Americans represent 6.69% of the available engineering professional services businesses
and received 0.00% of the dollars on engineering professional services contracts valued from
$25,000 to $500,000. This underutilization is statistically significant.
Hispanic Americans represent 5.86% of the available engineering professional services
businesses and received 1.36% of the dollars on engineering professional services contracts valued
from $25,000 to $500,000. This underutilization is not statistically significant.
Native Americans represent 2.09% of the available engineering professional services businesses
and received 0.00% of the dollars on engineering professional services contracts valued from
$25,000 to $500,000. While this group was underutilized, there were too few available firm s to
determine statistical significance.
Caucasian Females represent 23.43% of the available engineering professional services
businesses and received 11.03% of the dollars on engineering professional services contracts
valued from $25,000 to $500,000. This underutilization is statistically significant.
Non-minority Males represent 41.00% of the available engineering professional services
businesses and received 70.96% of the dollars on engineering professional services contracts
valued from $25,000 to $500,000. This overutilization is statistically significant.
Minority-owned Businesses represent 35.56% of the available engineering professional services
businesses and received 18.01% of the dollars on engineering professional services contracts
valued from $25,000 to $500,000. This underutilization is statistically significant.
Woman-owned Businesses represent 33.47% of the available engineering professional services
businesses and received 12.30% of the dollars on engineering professional services contracts
valued from $25,000 to $500,000. This underutilization is statistically significant.
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Prime Contract Disparity Analysis
Table 6.9: Disparity Analysis: Engineering Professional Services Prime Contracts Valued from $25,000 to $500,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $1,529,963 16.65%20.92%$1,922,517 -$392,554 0.80 not significant
Asian Americans $0 0.00%6.69%$615,205 -$615,205 0.00 < .05 *
Hispanic Americans $125,000 1.36%5.86%$538,305 -$413,305 0.23 not significant
Native Americans $0 0.00%2.09%$192,252 -$192,252 0.00 ----
Caucasian Females $1,013,793 11.03%23.43%$2,153,219 -$1,139,426 0.47 < .05 *
Non-minority Males $6,520,876 70.96%41.00%$3,768,134 $2,752,742 1.73 < .05 †
TOTAL $9,189,632 100.00%100.00%$9,189,632
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $116,312 1.27%5.44%$499,854 -$383,543 0.23 not significant
African American Males $1,413,651 15.38%15.48%$1,422,663 -$9,012 0.99 not significant
Asian American Females $0 0.00%2.51%$230,702 -$230,702 0.00 ----
Asian American Males $0 0.00%4.18%$384,503 -$384,503 0.00 ----
Hispanic American Females $0 0.00%1.26%$115,351 -$115,351 0.00 ----
Hispanic American Males $125,000 1.36%4.60%$422,954 -$297,954 0.30 not significant
Native American Females $0 0.00%0.84%$76,901 -$76,901 0.00 ----
Native American Males $0 0.00%1.26%$115,351 -$115,351 0.00 ----
Caucasian Females $1,013,793 11.03%23.43%$2,153,219 -$1,139,426 0.47 < .05 *
Non-minority Males $6,520,876 70.96%41.00%$3,768,134 $2,752,742 1.73 < .05 †
TOTAL $9,189,632 100.00%100.00%$9,189,632
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $1,654,963 18.01%35.56%$3,268,279 -$1,613,316 0.51 < .05 *
Woman Business Enterprises $1,130,105 12.30%33.47%$3,076,027 -$1,945,922 0.37 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Prime Contract Disparity Analysis
Chart 6.6: Disparity Analysis: Engineering Professional Services Prime Contracts Valued from $25,000 to $500,000,
January 1, 2013, to December 31, 2017
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
$5,000,000
$6,000,000
$7,000,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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Prime Contract Disparity Analysis
4. Purchases and Other Services Prime Contracts Valued from $25,000 to
$500,000
The disparity analysis of purchases and other services prime contracts valued from $25,000 to
$500,000 is described below and shown in Table 6.10 and Chart 6.7.
African Americans represent 31.82% of the available purchases and other services businesses and
received 35.87% of the dollars on purchases and other services contracts valued from $25,000 to
$500,000. This study does not statistically test the overutilization of minority or gender groups.
Asian Americans represent 3.57% of the available purchases and other services businesses and
received 3.73% of the dollars on purchases and other services contracts valued from $25,000 to
$500,000. This study does not statistically test the overutilization of minority or gender groups.
Hispanic Americans represent 4.22% of the available purchases and other services businesses and
received 0.00% of the dollars on purchases and other services contracts valued from $25,000 to
$500,000. While this group was underutilized, there were too few available firms to determine
statistical significance.
Native Americans represent 1.95% of the available purchases and other services businesses and
received 0.00% of the dollars on purchases and other services contracts valued from $25,000 to
$500,000. While this group was underutilized, there were too few available firms to determine
statistical significance.
Caucasian Females represent 24.68% of the available purchases and other services businesses
and received 16.30% of the dollars on purchases and other services contracts valued from $25,000
to $500,000. This underutilization is not statistically significant.
Non-minority Males represent 33.77% of the available purchases and other services businesses
and received 44.10% of the dollars on purchases and other services contracts valued from $25,000
to $500,000. This overutilization is not statistically significant.
Minority-owned Businesses represent 41.56% of the available purchases and other services
businesses and received 39.60% of the dollars on purchases and other services contracts valued
from $25,000 to $500,000. This underutilization is not statistically significant.
Woman-owned Businesses represent 38.31% of the available purchases and other services
businesses and received 16.30% of the dollars on purchases and other services contracts valued
from $25,000 to $500,000. This underutilization is statistically significant.
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Table 6.10: Disparity Analysis: Purchases and Other Services Prime Contracts Valued $25,000 to $500,000,
January 1, 2013, to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $1,968,854 35.87%31.82%$1,746,360 $222,495 1.13 **
Asian Americans $204,550 3.73%3.57%$196,020 $8,530 1.04 **
Hispanic Americans $0 0.00%4.22%$231,660 -$231,660 0.00 ----
Native Americans $0 0.00%1.95%$106,920 -$106,920 0.00 ----
Caucasian Females $894,664 16.30%24.68%$1,354,320 -$459,656 0.66 not significant
Non-minority Males $2,420,491 44.10%33.77%$1,853,280 $567,212 1.31 not significant
TOTAL $5,488,559 100.00%100.00%$5,488,559
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $0 0.00%10.39%$570,240 -$570,240 0.00 < .05 *
African American Males $1,968,854 35.87%21.43%$1,176,120 $792,734 1.67 **
Asian American Females $0 0.00%0.97%$53,460 -$53,460 0.00 ----
Asian American Males $204,550 3.73%2.60%$142,560 $61,990 1.43 **
Hispanic American Females $0 0.00%0.97%$53,460 -$53,460 0.00 ----
Hispanic American Males $0 0.00%3.25%$178,200 -$178,200 0.00 ----
Native American Females $0 0.00%1.30%$71,280 -$71,280 0.00 ----
Native American Males $0 0.00%0.65%$35,640 -$35,640 0.00 ----
Caucasian Females $894,664 16.30%24.68%$1,354,320 -$459,656 0.66 not significant
Non-minority Males $2,420,491 44.10%33.77%$1,853,280 $567,212 1.31 not significant
TOTAL $5,488,559 100.00%100.00%$5,488,559
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $2,173,404 39.60%41.56%$2,280,960 -$107,555 0.95 not significant
Woman Business Enterprises $894,664 16.30%38.31%$2,102,760 -$1,208,096 0.43 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) this study does not test statistically the overutilization of MWBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Prime Contract Disparity Analysis
Chart 6.7: Disparity Analysis: Purchases and Other Services Prime Contracts Valued $25,000 to $500,000,
January 1, 2013, to December 31, 2017
$0
$500,000
$1,000,000
$1,500,000
$2,000,000
$2,500,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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III. Disparity Analysis Summary
A. Building Construction Prime Contracts
As indicated in Table 6.11, there were too few contracts awarded to determine the statistical
significance for prime contractors on building construction contracts valued $25,000 to
$8,270,000.
Table 6.11: Disparity Summary: Building Construction Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Building Construction
Contracts Valued from
$25,000 to $8,270,000
African Americans No Disparity
Asian Americans No Disparity
Hispanic Americans No Disparity
Native Americans No Disparity
Caucasian Females Underutilized
Minority-owned Businesses No Disparity
Woman-owned Businesses Underutilized
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Prime Contract Disparity Analysis
B. Non-Building Construction Prime Contracts
As indicated in Table 6.12, disparity was found for African American, Hispanic American,
Caucasian female, minority-owned business, and woman owned business prime contractors on
non-building construction contracts valued under $25,000. Disparity was also found for African
American, Caucasian female, minority-owned business, and woman-owned business prime
contractors on non-building construction contracts valued $25,000 to $500,000
Table 6.12: Disparity Summary: Non-Building Construction Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Non-Building Construction
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans Disparity Disparity
Asian Americans No Disparity No Disparity
Hispanic Americans Disparity No Disparity
Native Americans No Disparity No Disparity
Caucasian Females Disparity Disparity
Minority-owned Businesses Disparity Disparity
Woman-owned Businesses Disparity Disparity
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Prime Contract Disparity Analysis
C. Engineering Professional Services Prime Contracts
As indicated in Table 6.13, disparity was found for Asian American, Hispanic American, Native
American, and Caucasian female prime contractors on engineering professional services contracts
valued under $25,000. Disparity was also found for Asian American, Caucasian female, minority-
owned business, and woman-owned business prime contractors on engineering professional
services contracts valued $25,000 to $500,000.
Table 6.13: Disparity Summary: Engineering Professional Services
Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Engineering Professional Services
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans No Disparity No Disparity
Asian Americans Disparity Disparity
Hispanic Americans Disparity No Disparity
Native Americans Disparity No Disparity
Caucasian Females Disparity Disparity
Minority-owned Businesses No Disparity Disparity
Woman-owned Businesses No Disparity Disparity
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D. Purchases and Other Services Prime Contracts
As indicated in Table 6.14, disparity was found for African American, Asian American, Hispanic
American, Native American, and minority-owned business prime contractors on purchases and
other services contracts valued under $25,000. Disparity was found for woman-owned business
prime contractors on purchases and other services contracts valued $25,000 to $500,000.
Table 6.14: Disparity Summary: Purchases and Other Services Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Purchases and Other Services
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans Disparity No Disparity
Asian Americans Disparity No Disparity
Hispanic Americans Disparity No Disparity
Native Americans Disparity No Disparity
Caucasian Females No Disparity Underutilized
Minority-owned Businesses Disparity No Disparity
Woman-owned Businesses No Disparity Disparity
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Subcontract Disparity Analysis
CHAPTER 7: Subcontract Disparity Analysis
I. Introduction
The objective of this chapter is to determine if available Minority and Woman-owned Business
Enterprise (MWBE) subcontractors were underutilized in the Metropolitan St. Louis Sewer
District’s (MSD) contracts awarded during the January 1, 2013 to December 31, 2017 study period.
A detailed discussion of the statistical method used to conduct the disparity analysis is described
in Chapter 6: Prime Contract Disparity Analysis. The subcontract disparity analysis applied the
same statistical method.
Under a fair and equitable system of awarding subcontracts, the proportion of subcontracts and
subcontract dollars awarded to MWBEs should be relatively close to the proportion of available
MWBE subcontractors in the Metropolitan St. Louis Sewer District’s market area. Availability is
defined as the number of willing and able market area businesses. The methodology for
determining willing and able market area businesses is detailed in Chapter 5: Prime Contractor
and Subcontractor Availability Analysis.
If the ratio of utilized MWBE subcontractors compared to available MWBE subcontractors is less
than one, a statistical test calculates the probability of observing the empirical disparity ratio or
any event which is less probable.254 Croson states that an inference of discrimination can be made
prima facie if the observed disparity is statistically significant. Under the Croson standard, non-
minority male-owned businesses (non-MWBE) are not subjected to a statistical test of
underutilization.255
II. Disparity Analysis
The disparity analysis was performed on the compiled subcontracts issued from January 1, 2013
to December 31, 2017. As detailed in Chapter 3: Subcontractor Utilization Analysis, extensive
effort was undertaken to compile subcontractor records for Metropolitan St. Louis Sewer District’s
building construction, non-building construction, engineering professional services, and purchases
and other services contracts awarded during the study period.
The subcontract disparity findings in the three industries are detailed in Section III. The outcomes
of the statistical analyses are presented in the “P-Value” column of the tables. A description of the
statistical outcomes in the disparity tables are listed in Table 7.1.
254 When conducting statistical tests, a confidence level must be established as a gauge for the level of certainty that an obser ved occurrence is not
due to chance. It is important to note that a 100 -percent confidence level or a level of absolute certainty can never be obtained in statistics. A
95-percent confidence level is the statistical standard used in physical and social sciences, and is thus used in the present report to determine if
an inference of discrimination can be made.
255 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
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Table 7.1: Statistical Outcome Descriptions
P-Value Outcome Definition of P-Value Outcome
< 0.05 * This underutilization is statistically significant.
not significant
• MWBEs: This underutilization is not statistically significant.
• Non-minority males: This overutilization is not statistically
significant.
< 0.05 † This overutilization is statistically significant.
---- While this group was underutilized, there were too few available firms
to determine statistical significance.
** This study does not statistically test the overutilization of minority or
gender groups or the underutilization of non-minority males.
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Subcontract Disparity Analysis
III. Disparity Analysis: All Subcontracts by Industry
A. Building Construction Subcontracts
The disparity analysis of building construction subcontracts is described below and listed in Table
7.2 and Chart 7.1.
African Americans represent 35.77% of the available building construction businesses and
received 20.66% of the building construction subcontract dollars. This underutilization is
statistically significant.
Asian Americans represent 3.16% of the available building construction businesses and received
0.00% of the building construction subcontract dollars. This underutilization is statistically
significant.
Hispanic Americans represent 4.62% of the available building construction businesses and
received 0.51% of the building construction subcontract dollars. This underutilization is
statistically significant.
Native Americans represent 1.09% of the available building construction businesses and received
1.41% of the building construction subcontract dollars. This study does not statistically test the
overutilization of minority or gender groups.
Caucasian Females represent 19.22% of the available building construction businesses and
received 6.49% of the building construction subcontract dollars. This underutilization is
statistically significant.
Non-minority Males represent 36.13% of the available building construction businesses and
received 70.94% of the building construction subcontract dollars. This overutilization is
statistically significant.
Minority-owned Businesses represent 44.65% of the available building construction businesses
and received 22.57% of the building construction subcontract dollars. This underutilization is
statistically significant.
Woman-owned Businesses256 represent 29.93% of the available building construction businesses
and received 7.51% of the building construction subcontract dollars. This underutilization is
statistically significant.
256 Ethnic and gender categories have been described in Table 2.1 in Chapter 2: Prime Contractor Utilization Analysis.
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Table 7.2: Disparity Analysis: Building Construction Subcontracts,
January 1, 2013 to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $3,426,554 20.66%35.77%$5,932,732 -$2,506,178 0.58 < .05 *
Asian Americans $0 0.00%3.16%$524,663 -$524,663 0.00 < .05 *
Hispanic Americans $83,979 0.51%4.62%$766,816 -$682,837 0.11 < .05 *
Native Americans $233,872 1.41%1.09%$181,614 $52,258 1.29 **
Caucasian Females $1,076,138 6.49%19.22%$3,188,339 -$2,112,201 0.34 < .05 *
Non-minority Males $11,766,892 70.94%36.13%$5,993,270 $5,773,622 1.96 < .05 †
TOTAL $16,587,434 100.00%100.00%$16,587,434
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $168,853 1.02%8.27%$1,372,197 -$1,203,343 0.12 not significant
African American Males $3,257,701 19.64%27.49%$4,560,536 -$1,302,835 0.71 < .05 *
Asian American Females $0 0.00%0.85%$141,256 -$141,256 0.00 ----
Asian American Males $0 0.00%2.31%$383,408 -$383,408 0.00 ----
Hispanic American Females $0 0.00%0.97%$161,435 -$161,435 0.00 ----
Hispanic American Males $83,979 0.51%3.65%$605,381 -$521,402 0.14 not significant
Native American Females $0 0.00%0.61%$100,897 -$100,897 0.00 ----
Native American Males $233,872 1.41%0.49%$80,717 $153,155 2.90 **
Caucasian Females $1,076,138 6.49%19.22%$3,188,339 -$2,112,201 0.34 < .05 *
Non-minority Males $11,766,892 70.94%36.13%$5,993,270 $5,773,622 1.96 < .05 †
TOTAL $16,587,434 100.00%100.00%$16,587,434
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $3,744,405 22.57%44.65%$7,405,825 -$3,661,420 0.51 < .05 *
Woman Business Enterprises $1,244,991 7.51%29.93%$4,964,123 -$3,719,132 0.25 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) denotes that this study does not test statistically the overutilization of M/WBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 7.1: Disparity Analysis: Building Construction Subcontracts,
January 1, 2013 to December 31, 2017
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B. Nonbuilding Construction Subcontracts
The disparity analysis of non-building construction subcontracts is described below and listed in
Table 7.3 and Chart 7.2.
African Americans represent 31.20% of the available non-building construction businesses and
received 52.41% of the non-building construction subcontract dollars. This study does not
statistically test the overutilization of minority or gender groups.
Asian Americans represent 3.11% of the available non-building construction businesses and
received 0.01% of the non-building construction subcontract dollars. This underutilization is
statistically significant.
Hispanic Americans represent 3.91% of the available non-building construction businesses and
received 0.82% of the non-building construction subcontract dollars. This underutilization is
statistically significant.
Native Americans represent 0.98% of the available non-building construction businesses and
received 0.09% of the non-building construction subcontract dollars. While this group was
underutilized, there were too few available firms to determine statistical significance.
Caucasian Females represent 17.69% of the available non-building construction businesses and
received 7.92% of the non-building construction subcontract dollars. This underutilization is
statistically significant.
Non-minority Males represent 43.11% of the available non-building construction businesses and
received 38.75% of the non-building construction subcontract dollars. This study does not
statistically test the underutilization of non-minority males.
Minority-owned Businesses represent 39.20% of the available non-building construction
businesses and received 53.32% of the non-building construction subcontract dollars. This study
does not statistically test the overutilization of minority or gender groups.
Woman-owned Businesses represent 27.82% of the available non-building construction
businesses and received 18.19% of the non-building construction subcontract dollars. This
underutilization is statistically significant.
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Table 7.3: Disparity Analysis: Non-building Construction Subcontracts,
January 1, 2013 to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $146,358,711 52.41%31.20%$87,131,202 $59,227,509 1.68 **
Asian Americans $23,581 0.01%3.11%$8,688,297 -$8,664,716 0.00 < .05 *
Hispanic Americans $2,276,874 0.82%3.91%$10,922,430 -$8,645,556 0.21 < .05 *
Native Americans $253,572 0.09%0.98%$2,730,607 -$2,477,035 0.09 ----
Caucasian Females $22,125,499 7.92%17.69%$49,399,172 -$27,273,673 0.45 < .05 *
Non-minority Males $108,228,437 38.75%43.11%$120,394,966 -$12,166,529 0.90 **
TOTAL $279,266,674 100.00%100.00%$279,266,674
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $28,166,932 10.09%7.73%$21,596,623 $6,570,310 1.30 **
African American Males $118,191,779 42.32%23.47%$65,534,580 $52,657,199 1.80 **
Asian American Females $0 0.00%0.98%$2,730,607 -$2,730,607 0.00 ----
Asian American Males $23,581 0.01%2.13%$5,957,689 -$5,934,108 0.00 < .05 *
Hispanic American Females $497,735 0.18%0.89%$2,482,370 -$1,984,636 0.20 ----
Hispanic American Males $1,779,140 0.64%3.02%$8,440,059 -$6,660,920 0.21 < .05 *
Native American Females $0 0.00%0.53%$1,489,422 -$1,489,422 0.00 ----
Native American Males $253,572 0.09%0.44%$1,241,185 -$987,613 0.20 ----
Caucasian Females $22,125,499 7.92%17.69%$49,399,172 -$27,273,673 0.45 < .05 *
Non-minority Males $108,228,437 38.75%43.11%$120,394,966 -$12,166,529 0.90 **
TOTAL $279,266,674 100.00%100.00%$279,266,674
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $148,912,738 53.32%39.20%$109,472,536 $39,440,202 1.36 **
Woman Business Enterprises $50,790,166 18.19%27.82%$77,698,195 -$26,908,029 0.65 < .05 *
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) denotes that this study does not test statistically the overutilization of M/WBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 7.2: Disparity Analysis: Non-building Construction Subcontracts,
January 1, 2013 to December 31, 2017
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C. Engineering Professional Services Subcontracts
The disparity analysis of engineering professional services subcontracts is described below and
listed in Table 7.4 and Chart 7.3.
African Americans represent 36.39% of the available engineering professional services businesses
and received 22.68% of the engineering professional services subcontract dollars. This
underutilization is statistically significant.
Asian Americans represent 4.99% of the available engineering professional services businesses
and received 5.69% of the engineering professional services subcontract dollars. This study does
not statistically test the overutilization of minority or gender groups.
Hispanic Americans represent 5.31% of the available engineering professional services
businesses and received 9.01% of the engineering professional services subcontract dollars. This
study does not statistically test the overutilization of minority or gender groups.
Native Americans represent 1.45% of the available engineering professional services businesses
and received 0.02% of the engineering professional services subcontract dollars. This
underutilization is statistically significant.
Caucasian Females represent 26.73% of the available engineering professional services
businesses and received 22.08% of the engineering professional services subcontract dollars. This
underutilization is not statistically significant.
Non-minority Males represent 25.12% of the available engineering professional services
businesses and received 40.52% of the engineering professional services subcontract dollars. This
overutilization is statistically significant.
Minority-owned Businesses represent 48.15% of the available engineering professional services
businesses and received 37.40% of the engineering professional services subcontract dollars. This
underutilization is statistically significant.
Woman-owned Businesses represent 42.35% of the available engineering professional services
businesses and received 33.11% of the engineering professional services subcontract dollars. This
underutilization is not statistically significant.
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Table 7.4: Disparity Analysis: Engineering Professional Services Subcontracts,
January 1, 2013 to December 31, 2017
Ethnicity Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African Americans $21,075,815 22.68%36.39%$33,811,785 -$12,735,970 0.62 < .05 *
Asian Americans $5,284,725 5.69%4.99%$4,637,900 $646,826 1.14 **
Hispanic Americans $8,370,222 9.01%5.31%$4,937,119 $3,433,103 1.70 **
Native Americans $15,303 0.02%1.45%$1,346,487 -$1,331,184 0.01 < .05 *
Caucasian Females $20,515,023 22.08%26.73%$24,835,205 -$4,320,181 0.83 not significant
Non-minority Males $37,646,515 40.52%25.12%$23,339,108 $14,307,407 1.61 < .05 †
TOTAL $92,907,603 100.00%100.00%$92,907,603
Ethnicity and Gender Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
African American Females $10,177,991 10.95%11.92%$11,071,115 -$893,124 0.92 not significant
African American Males $10,897,824 11.73%24.48%$22,740,669 -$11,842,846 0.48 < .05 *
Asian American Females $57,045 0.06%1.93%$1,795,316 -$1,738,271 0.03 < .05 *
Asian American Males $5,227,680 5.63%3.06%$2,842,584 $2,385,096 1.84 **
Hispanic American Females $0 0.00%0.97%$897,658 -$897,658 0.00 ----
Hispanic American Males $8,370,222 9.01%4.35%$4,039,461 $4,330,761 2.07 **
Native American Females $15,303 0.02%0.81%$748,048 -$732,745 0.02 ----
Native American Males $0 0.00%0.64%$598,439 -$598,439 0.00 ----
Caucasian Females $20,515,023 22.08%26.73%$24,835,205 -$4,320,181 0.83 not significant
Non-minority Males $37,646,515 40.52%25.12%$23,339,108 $14,307,407 1.61 < .05 †
TOTAL $92,907,603 100.00%100.00%$92,907,603
Minority and Females Actual Dollars Utilization Availability Expected Dollars Dollars Lost Disp. Ratio P-Value
Minority Business Enterprises $34,746,065 37.40%48.15%$44,733,290 -$9,987,226 0.78 < .05 *
Woman Business Enterprises $30,765,363 33.11%42.35%$39,347,342 -$8,581,979 0.78 not significant
( * ) denotes a statistically significant underutilization.
( † ) denotes a statistically significant overutilization.
( ** ) denotes that this study does not test statistically the overutilization of M/WBEs or the underutilization of Non-minority Males.
( ---- ) denotes an underutilized group with no contracts awarded, too few contracts awarded, or too few available firms to test statistical significance.
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Chart 7.3: Disparity Analysis: Engineering Professional Services Subcontracts,
January 1, 2013 to December 31, 2017
$0
$5,000,000
$10,000,000
$15,000,000
$20,000,000
$25,000,000
$30,000,000
$35,000,000
$40,000,000
African Americans Asian Americans Hispanic
Americans
Native Americans Caucasian
Females
Non-minority Males
Do
l
l
a
r
s
Ethnic/Gender Groups
Actual Dollars
Expected Dollars
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IV. Subcontract Disparity Summary
As indicated in Table 7.5, disparity was found for African American, Asian American, Hispanic
American, Caucasian female, and-Minority-and Woman-owned business building construction
subcontractors. Disparity was also found for Asian American, Hispanic American, Caucasian
female, and Woman-owned business non-building construction subcontractors. For engineering
professional services disparity was found for African American, Native American, and Minority-
owned business subcontractors. Caucasian Females and Woman-owned Businesses were
substantially underutilized albeit not at a statistically significant level.
Table 7.5: Subcontract Disparity Summary,
January 1, 2013 to December 31, 2017
Ethnicity / Gender Building
Construction
Non-building
Construction
Engineering
Professional
Services
African Americans Disparity No Disparity Disparity
Asian Americans Disparity Disparity No Disparity
Hispanic
Americans Disparity Disparity No Disparity
Native Americans No Disparity No Disparity Disparity
Caucasian Females Disparity Disparity Underutilized
Minority-owned
Businesses Disparity No Disparity Disparity
Woman-owned
Businesses Disparity Disparity Underutilized
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CHAPTER 8: Regression Analysis
I. Introduction
Private sector business practices which are not subject to government minority and woman-owned
business enterprise (MWBE) or disadvantaged business enterprise (DBE) requirements are
indicators of marketplace conditions which could affect the formation and growth of MWBEs.
Concrete Works of Colorado v. City of Denver257 (Concrete Works II) set forth a framework for
considering a passive participant model for an analysis of discrimination in private sector business
practices. In accordance with Concrete Works II, regression analyses were conducted to examine
three outcome variables—business ownership rates, business earnings, and business loan approval.
Each regression analysis compared minority group members258 and Caucasian females to
Caucasian males by controlling for race and gender-neutral explanatory variables such as age,
education, marital status, and access to capital. The impact of the explanatory variables on the
outcome variables is described in this chapter.
The U.S. Census American Community Survey Public Use Microdata Sample (PUMS) data was
used to compare minority and Caucasian Females’ probability of owning a business to the
probability of Caucasian Males owning a business. Logistic regression was used to determine if
race and gender have a statistically significant effect on the probability of business ownership. The
PUMS data was also used to compare the business earnings of MWBEs to Caucasian Male-owned
Businesses. Ordinary Least Squares (OLS) analysis was utilized to analyze the PUMS data for
disparities in business earnings after controlling for race and gender -neutral factors. The Federal
Reserve Board’s National Survey of Small Business Finances (NSSBF) dataset was used to
compare MWBEs’ business loan approval probabilities to Caucasian Male-owned Businesses’
loan approval probabilities, while controlling for other business explanatory variables.
The applicable limits of the private sector discrimination findings are set forth in Builders
Association of Greater Chicago v. City of Chicago 259 (City of Chicago), where the court established
that even when there is evidence of private sector discrimination, the findings cannot be used as
the factual predicate for a government sponsored, race-conscious MWBE or DBE program unless
there is a nexus between the private sector data and the public agency actions. The private sector
findings, however, can be used to develop race- neutral programs to address barriers to the
formation and development of MWBEs. Given the case law, caution must be exercised in the
interpretation and application of the regression findings. Case law regarding the application of
private sector discrimination is discussed below in detail.
257 Concrete Works of Colo., Inc. v. City of Denver, 86 F. Supp. 2d 1042, 1073 (D. Colo. 2000), rev'd on other grounds, 321 F.3d 950 (10th Cir.
2003), cert. denied, 540 U.S. 1027 (2003).
258 Minority group members include both males and females.
259 Builders Association of Greater Chicago v. City of Chicago, 298 F.Supp.2d 725 (N.D. III. 2003).
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II. Legal Analysis
A. Passive Discrimination
The controlling legal precedent set forth in the 1989 City of Richmond v. J.A. Croson Co.260
decision authorized state and local governments to remedy discrimination in the award of
subcontracts by its prime contractors on the grounds that the government cannot be a “passive
participant” in such discrimination. In January 2003, Concrete Works II and City of Chicago
extended the private sector analysis to the investigation of discriminatory barriers that MWBEs
encountered in the formation and development of businesses and their consequence for state and
local remedial programs. Concrete Works II set forth a framework for considering such private
sector discrimination as a passive participant model for analysis. The obligation of presenting an
appropriate nexus between the government remedy and the private sector discrimination was
addressed in City of Chicago.
The Tenth Circuit Court decided in Concrete Works II that business activities conducted in the
private sector, if within the government’s market area, are also appropriate areas to explore the
issue of passive participation. However, the appropriateness of the City of Denver’s remedy, given
the finding of private sector discrimination, was not at issue before the court. The question before
the court was whether sufficient facts existed to determine if the private sector business practices
under consideration constituted discrimination. For technical legal reasons261 the court did not
examine whether a consequent public sector remedy, i.e., one involving a goal requirement on the
City of Denver’s contracts, was “narrowly tailored” or otherwise supported by the City’s private
sector findings of discrimination.
B. Narrow Tailoring
The question of whether a particular public sector remedy is narrowly tailored when it is based
solely on business practices within the private sector was at issue in City of Chicago. City of
Chicago, decided ten months after Concrete Works II, found that certain business practices
constituted discrimination against minorities in the Chicago market area. However, the District
Court did not find the City of Chicago’s MWBE subcontracting goal to be a remedy “narrowly
tailored” to address the documented private discriminatory business practices that had been
discovered within the City’s market area. The court explicitly stated that certain discriminatory
business practices documented by regression analyses constituted private sector discrimination. It
is also notable that the documented discriminatory business practices reviewed by the court in the
City of Chicago were similar to those reviewed in Concrete Works. Notwithstanding the fact that
discrimination in the City of Chicago’s market area was documented, the court determined that
the evidence was insufficient to support the City’s race-based subcontracting goals. The court
ordered an injunction to invalidate the City of Chicago’s race-based program.
260 488 U.S. 469 (1989).
261 Plaintiff had not preserved the issue on appeal. Therefore, it was no longer part of the case.
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Note the following statements from that opinion:
Racial preferences are, by their nature, highly suspect, and they cannot be used to
benefit one group that, by definition, is not either individually or collectively the
present victim of discrimination. There may well also be (and the evidence suggests
that there are) minorities and women who do not enter the industry because they
perceive barriers to entry. If there is none, and their perception is in error, that false
perception cannot be used to provide additional opportunities to MWBEs already
in the market to the detriment of other firms who, again by definition, neither
individually nor collectively are engaged in discriminatory practices.262
Given these distortions of the market and these barriers, is the City’s program
narrowly tailored as a remedy? It is here that I believe the program fails. There is
no "meaningful individualized review" of MWBEs, Gratz v. Bollinger, 539 U.S.
244, 156 L. Ed. 2d 257, 123 S.Ct. 2411, 2431 (2003) (Justice O’Connor
concurring). Chicago’s program is more expansive and more rigid than plans that
have been sustained by the courts. It has no termination date, nor has it any means
for determining a termination date. The ‘graduation’ revenue amount is very high,
$27,500,000, and very few have graduated. There is no net worth threshold. A third
generation Japanese-American from a wealthy family, and with a graduate degree
from MIT, qualifies (and an Iraq immigrant does not). Waivers are rarely or never
granted on construction contracts, but “regarding the availability of waivers is of
particular importance... a ‘rigid numerical quota’ particularly disserves the cause of
narrow tailoring” Adarand Constructors v. Slater, supra, at 1177. The City’s
program is “rigid numerical quota,” a quota not related to the number of avail able,
willing and able firms but to concepts of how many of those firms there should be.
Formalistic points did not survive strict scrutiny in Gratz v. Bollinger, supra, and
formalistic percentages cannot survive scrutiny.263
The federal circuit appellant decision in Rothe Development Corp. v. U.S. Department of
Defense264 (Rothe) involved the issue of capacity. There were two earlier appeals prior to the
appellant court’s holding in November 2008 that the Department of Defense’s (DOD) small
disadvantaged business program was unconstitutional on its face.
One of the arguments proffered by Rothe on appeal was that the district court erred by relying on
six disparity studies which failed to establish that DOD played any role in the discriminato ry
exclusion of minority-owned contractors.
262 Builders Association of Greater Chicago v. City of Chicago, 298 F.Supp.2d 725 (N.D. III. 2003).
263 Id.
264 545 F.3d 1023 (Fed. Cir. 2008).
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The court acknowledged that two of the studies relied on by congress attempted to deal with
capacity. The New York City study limited prime contracts to those valued at $1 million and under
and the firms in the Dallas study had a “demonstrated capacity to win large competitively bid
contracts.” Thus, the court concluded that several studies that were relied upon demonstrated the
firms had the capacity to perform a contract. The court expressed an additional concern as to
whether the firms could do more than one contract a time and deduced that a regression analysis
was recommended as the corrective for going forward.265
Caution should also be exercised when determining which minority or gender group is appropriate
for race-conscious or gender-conscious remedies. For an MWBE program to be narrowly tailored,
there must be a statistical finding of underutilization of minority subcontractors. Where the
underutilization of a minority group is not found to be statistically significant, the minority group
should not be included in race-conscious remedies.266
C. Conclusion
As established in City of Chicago, private sector discrimination cannot be used as the factual basis
for a government sponsored, race-based MWBE program without a nexus to the government's
actions. Therefore, the disparity findings that might be revealed in the regression analyses are not
sufficient factual predicate for a race-based MWBE Program by the Metropolitan St. Louis Sewer
District (MSD) since a nexus cannot be established between MSD and the private sector data.
These economic indicators documented in the regression analyses, albeit not a measure of passive
discrimination, are illustrative of private sector discrimination and can support the MSD -
sponsored, race- neutral programs.
III. Regression Analysis Methodology
Regression analysis is the methodology employed to ascertain whether there are private sector
economic indicators of discrimination in MSD’s market area that could impact the formation and
development of MWBEs. The industries of focus for the three regression analyses are construction,
professional services, and goods and other services. Due to sample size issues, the professional
services industry includes architecture and engineering businesses. These three industries most
closely represent the four industries studied in the Metropolitan St. Louis Sewer District Disparity
Study (Study) while allowing for inconsistencies between the PUMS and NSSBF datasets.
265 Id.
266 H.B. Rowe Company v. Tippett, 615 F.3d 233, Court of Appeals, Fourth Circuit (N.C.), July 22, 2010 (NO. 09 -1050). The Rowe Court also
ruled that statistical evidence of overutilization of women business enterprises that is not statistically significant is suf ficient factual
predicate for gender-based remedies.
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As noted, three separate regression analyses are used. They are the Business Ownership Analysis,
the Earnings Disparity Analysis, and the Business Loan Approval Analysis. All analyses takes into
consideration race and gender-neutral factors such as age, education, and creditworthiness in
assessing whether the explanatory factors examined are disproportionately affecting minorities and
females when compared to similarly situated Caucasian Males.
IV. Datasets Analyzed
The 2008 through 2010 PUMS datasets produced by the United States Census Bureau were
compiled and used to analyze business ownership and earnings disparities within the Study’s
market area. The market area consists of the City of St. Louis and St. Louis County. The data were
identified using Public Use Microdata Areas (PUMA), a variable within the PUMS dataset that
reports data for counties and independent cities within states. The dataset includes information on
personal profile, industry, work characteristics, and family structure. The PUMS data allowed for
an analysis by an individual’s race and gender.
The 2003 NSSBF was utilized to examine business loan approval rates in the Business Loan
Approval Analysis. The NSSBF dataset contains observations for business and owner
characteristics including the business owner’s credit and resources, and the
business’s credit and financial health. The NSSBF records the geographic location of the business
by Census Division, instead of city, county, or state. While the NSSBF data is available by Census
Division, the subdivision containing the State of Missouri or the West North Central Division267
lacked sufficient data to perform an accurate regression analysis by minority status, gender, and
industry. Therefore, the sample was expanded to the entire United States.
The 2003 NSSBF contains the most recent available data on access to credit for the West North
Central Division. The dataset allowed for an analysis of all minority groups combined by industry.
V. Regression Models Defined
A. Business Ownership Analysis
The Business Ownership Analysis examines the relationship between the probability of being a
business owner and independent socio-economic variables. Business ownership, the dependent
variable, includes business owners of incorporated and non-incorporated firms. The business
ownership variable only utilizes two values. A value of "1" indicates that a person is a business
owner, whereas a value of "0" indicates that a person is not a business owner. When the dependent
variable is defined this way, it is called a binary variable.268 In this case, a logistic regression model
267 The West North Central, a subset of the Midwest Region, include s North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, and
Minnesota.
268 In this case, the standard Ordinary Least Squares (OLS) Regression model cannot be employed and a logistic model is utilized to predict the
probability of business ownership.
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is utilized to predict the probability of business ownership using independent socio -economic
variables. Three logistic models are run to predict the probability of business ownership in the
construction, professional services, and supplies and contractual services industries. Categories of
the independent variables analyzed include educational level, citizenship status, personal
characteristics, and race/gender.
For each of the three industries, the logistic regression is used to id entify the probability that an
individual owns a business given his or her background including race, gender, and race and
gender-neutral factors. The dependent variable in this model is binary, coded as "1" for individuals
who are self-employed and "0" for individuals who are not self-employed.269 Table 8.1 presents
the independent variables used for the Business Ownership Analysis.
Table 8.1: Independent Variables used in the Business Ownership Analysis
Personal
Characteristics
Educational
Attainment Race Gender
Age
Age Squared
Home Owner
Home Value
Finances
Speaking English at Home
Children Under The Age of Six
Marital Status
Bachelor's Degree
Advanced Degree
African American
Asian American
Native American
Hispanic American
Other Minority270
Female
B. Earnings Disparity Analysis
The Earnings Disparity Analysis examines the relationship between annual self - employment
income and independent socio-economic variables. Wages are defined as the individual’s total
dollar income earned in the previous twelve months. Categories of independent socio-economic
variables analyzed include educational level, citizenship status, personal characteristics, business
characteristics, and race/gender.
All of the independent variables are regressed against wages in an Ordinary Least Squares (OLS)
regression model. The OLS model estimates a linear relationship between the independent
variables and the dependent variable. This multivariate regression model estimates a line similar
to the standard y = mx+b format but with additional independent variables. The mathematical
purpose of a regression analysis is to estimate a best fit line for the model and assess which findings
are statistically significant.
269 Note: The terms “business owner” and “self-employed” are used interchangeably throughout the chapter.
270 Other Minority includes individuals who belong to two or more racial groups.
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In the tables below, a finding of disparity is denoted by an asterisk (*) when the independent
variable has a p-value at or below .05. A finding of disparity indicates that there is a non-random
relationship between wages and the independent variable. Tables of regression results indicate the
sign of each variable's coefficient from the regression output. If the coefficient sign is positive, it
means there is a positive relationship between the dependent variable and the independent variable.
For example, if age is positively related to wages, this implies that older business owners tend to
have higher business earnings, holding all other variables constant. If the coefficient sign for the
independent variable is negative, this implies an inverse relationship between the dependent
variable and the independent variable. For example, if being Caucasian Female is negatively
related to wages, then business owners who are Caucasian Female tend to have lower business
earnings.
An OLS regression analysis is used to assess the presence of business earning disparities. OLS
regressions have been conducted separately for each industry. Table 8.2 presents the independent
variables used for the Earnings Disparity Analysis.271
Table 8.2: Independent Variables Used for Earnings Disparity Analysis
Personal
Characteristics
Educational
Attainment Race Gender
Age
Age Squared
Business Type
Home Owner
Home Value
Finances
Speaking English at Home
Children Under The Age of Six
Marital Status
Bachelor's Degree
Advanced Degree
African American
Asian American
Native American
Hispanic American
Other Minority
Female
C. Business Loan Approval Analysis
The Business Loan Approval Analysis examines the relationship between the probability of
obtaining a business loan and variables related to socio-economic factors and business
characteristics. The model is an ordered logistic model where the dependent variable is the reported
probability of obtaining a business loan.
271 If an independent variable is a binary variable, it will be coded as "1" if the individual has that variable present and "0" if otherwise (i.e. for
the Hispanic American variable, it is coded as "1" if the individual is Hispanic American and "0" if otherwise). If an indepe ndent variable is
a continuous variable, a value will be used (i.e. one’s age can be labeled as 35).
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The NSSBF data was collected by the U.S. Federal Reserve. The NSSBF collects information on
small businesses (fewer than 500 employees) in the United States such as owner characteristics,
firm size, use of financial services, and the income and balance sheets of the firm. The 2003
NSSBF dataset is the most recently released dataset.
In the tables below, a finding of disparity is denoted by an asterisk (*) when the independ ent
variable has a p-value at or below .05. A finding of disparity indicates that there is a non-random
relationship between obtaining a business loan and each independent variable. The tables
containing the regression results also indicate the sign of each variable's coefficient from the
regression output. If the coefficient sign is positive, it means there is a positive relationship
between the independent and dependent variables. For example, if having a bachelor’s degree has
a positive coefficient, then business owners with a bachelor’s degree are more probable to obtain
a business loan, holding all other variables constant. If the sign of the coefficient for the
independent variable is negative, this implies an inverse relationship between the independent and
dependent variables. For instance, if a business with a female owner has a negative coefficient,
this implies an indirect relationship between a female owner and obtaining a business loan.
Therefore, a business whose owner is female has a decreased probability of obtaining a business
loan (or a higher probability of being denied a business loan).
An ordered logistic regression is used to examine the factors that might explain loan approvals for
the business owners. The dependent variable is a categorical variable where "2" denotes never
being denied a business loan, "1" denotes sometimes being denied a business loan, and "0" denotes
always being denied a business loan.272 The independent variables describe three sets of factors:
• Business owner’s minority and gender group classification
• Business owner’s credit and resources
• Business’ credit and financial health
272 An ordered logistic model could be used differently for this model by assessing the numbers: 1= always denied a loan, 2= some times denied
a loan, and 3= never denied a loan.
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Table 8.3 presents the independent variables used for the Business Loan Approval Analysis.273
Table 8.3: Independent Variables Used for Business Loan Approval Analysis
Business Owner’s
Characteristics
Business’s Credit and
Financial Health Race Gender
Bachelor's Degree
Advanced Degree
Use of Personal Credit Card for
Business
Age of Business
Capital Leases
Vehicle Loans
Stockholder Loans
Location
Credit Score
Organization Type
Total Mortgage Principal Owned
Minority
Caucasian
Female
It should be noted that, due to data constraints, not all variables could be included in each industry
specification. For example, certain types of loans or the use of personal credit cards for business
are more common in certain industries. Therefore, while the theoretical underpinnings of the model
are applied uniformly for each industry, some of the independent variables may differ in each
industry specification.
VI. Findings
A. Business Ownership Analysis
The business ownership variable is defined by the number of individuals reporting self -
employment. The analysis considered incorporated and non-incorporated businesses. The data in
this section comes from the City of St. Louis and St. Louis County. The geographic was specified
using PUMA, a variable within the PUMS dataset that can specify the different counties within
states.274
Previous studies have shown that many non-discriminatory factors such as education, age, and
marital status are associated with self -employment. In this analysis, race and gender-neutral factors
are combined with race and gender-specific factors in a logistic regression model to determine
whether observed race or gender disparities are independent of the race and gender-neutral factors
known to be associated with self- employment. It must be noted that many of these variables, such
as having an advanced degree, while seeming to be race and gender-neutral, may in fact be
correlated with race and gender. For example, if females are less probable to have advanced
273 If an independent variable is a binary variable, it will be coded as "1" if the individual has that variable present and "0" if otherwise (i.e. for
the Hispanic American variable, it is coded as "1" if the individual is Hispanic American and "0" if otherwise). If an indep endent variable is
a continuous variable, a value will be used (i.e. one’s age can be labeled as 35).
274 The PUMS data were collected by the U.S. Census Bureau from a five percent sample of U.S. households. The observations were w eighted
to preserve the representative nature of the sample in relation to the population as a whole.
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degrees, and the regression results show that individuals with advanced degrees are significantly
more probable to own a business, females may be disadvantaged in multiple ways. First, females
may have statistically significant lower business ownership rates; therefore, they face a direct
disadvantage as a group. Second, they are indirectly disadvantaged as they tend to have less
advanced degrees, which significantly increase one’s chances of owning a business.
1. Logistic Model Results for Construction Business Ownership
Probabilities
Table 8.4 presents the logistic regression results for the probability of owning a business in the
construction industry, based on the 20 variables analyzed in this model.
Table 8.4: Construction Industry Logistic Model
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The construction industry logistic regression results indicate:275
• The probability of construction business ownership is positively associated with
increased age; older individuals are more probable to be business owners in the
construction industry, but not at a statistically significant level.
• Caucasian Females are significantly less probable to be business owners in the
construction industry than Caucasian Males.
• Asian Americans are significantly more probable to be business owners in the
construction industry than Caucasian Males.
• African Americans and Hispanic Americans are less probable than Caucasian
Males to be business owners in the construction industry, but not at a significant
level.
275 For the Business Ownership Analysis, the results are presented for age, education, race, and gender variables only.
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2. Logistic Model Results for Professional Services Business Ownership
Probabilities
Table 8.5 presents the logistic regression results for the probability of owning a business in the
professional services industry using the 20 variables analyzed in this model.
Table 8.5: Professional Services Logistic Model
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The professional services industry logistic regression results indicate:
• The probability of business ownership is positively associated with an increase in
age; older individuals are more probable to be business owners in the other
professional services industry, but not at a significant level.
• Caucasian Females are significantly less probable to be business owners in the
professional services industry than Caucasian Males.
• African Americans and Asian Americans are significantly less probable to be
business owners in the professional services industry than Caucasian Males.
• Other Minorities are less probable to be business owners in the professional
services industry, but not at a significant level.
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3. Logistic Model Results for Supplies and Contractual Services
Business Ownership Probabilities
Table 8.6 presents the logistic regression results for the probability of owning a business in the
other supplies and contractual services industry using the 20 variables analyzed in this model.
Table 8.6: Supplies and Contractual Services Logistic Model
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The supplies and contractual services industry logistic regression results indicate:
• The probability of business ownership is positively associated with an increase in
age; older individuals are significantly more probable to be business owners in the
supplies and contractual services industry.
• Having a bachelor’s degree significantly increases the probability of being a
business owner in the supplies and contractual services industry.
• Caucasian Females are significantly less probable to be business owners in the
supplies and contractual services industry than Caucasian Males.
• African Americans are significantly less probable to be business owners in the
supplies and contractual services industry than Caucasian Males.
• Hispanic Americans and Other Minority groups are less probable than Caucasian
Males to be business owners in the supplies and contractual services industry, but
not at a significant level.
B. Business Earnings Analysis
The business earnings variable is identified by self-employment income276 from the years 2007
through 2010 for the three industries: construction, professional services, and supplies and
contractual services. The analysis considered incorporated and non- incorporated businesses.
Previous studies have shown that many non-discriminatory factors such as education, age, and
marital status are associated with self-employment income. In this analysis, race and gender-
neutral factors are combined with race and gender groups in an OLS regression model to determine
whether observed race or gender disparities were independent of the race and gender-neutral
factors known to be associated with self- employment income.
1. OLS Regression for Business Earnings in the Construction Industry
Table 8.7 depicts the results of the OLS regression for business earnings in the construction
industry based on the 21 variables analyzed in this model.
276 The terms “business earnings” and “self-employment income” are used interchangeably.
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Table 8.7: Construction Industry OLS Regression
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2. OLS Regression Results for Business Earnings in the Professional
Services
Table 8.8: depicts the results of the OLS regression for business earnings in the professional
services industry based on the 20 variables analyzed in this model.
Table 8.8: Professional Services OLS Regression
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The OLS regression results for business earnings in the other professional services industry
indicate the following:
• Older business owners are significantly more probable to have higher business
earnings in the other professional services industry.
• Business owners with a bachelor’s or an advanced degree are significantly more
probable to have higher business earnings in the other professional services
industry.
• Caucasian Female business owners are significantly more probable to have lower
business earnings in the other professional services industry than Caucasian Males.
• Other Minority business owners are significantly more probable to have lower
business earnings in the other professional services industry than Caucasian Males.
• African American business owners are more probable to have lower business
earnings in the other professional services industry than Caucasian Males, but not
at a significant level.
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3. OLS Regression Results for Business Earnings in the Supplies and
Contractual Services Industry
Table 8.9: depicts the results of the OLS regression for business earnings in the other supplies and
contractual services industry based on the 20 variables analyzed in this model.
Table 8.9: Supplies and Contractual Services OLS Regression
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The OLS regression results for business earnings in the supplies and contractual services industry
indicate the following:
• Older business owners are more probable to have higher business earnings in the
supplies and contractual services industry, but not at a statistically significant level.
• Caucasian Female business owners are significantly more probable to have lower
business earnings in the supplies and contractual services industry than Caucasian
Males.
• African American and Asian American business owners are significantly more
probable to have lower business earnings in the supplies and contractual services
industry than Caucasian Males.
• Hispanic American business owners are more probable to have lower business
earnings in the supplies and contractual services industry than Caucasian Males,
but not at a statistically significant level.
C. Business Loan Approval Analysis
Access to business capital in the form of loans is measured by the Business Loan Approval
Analysis. The probability of business loan approval variable is a score that reflects the
reported probability of experiencing loan approval. The data in this section comes from the
2003 NSSBF dataset. Previous studies have shown that many non- discriminatory factors
such as education, experience of the business owner, and firm characteristics could lead to
differences in a business owner’s loan approval rate. In this analysis, race and gender -
neutral factors are combined with race and gender groups in an ordered logistic regression
model to determine whether observed race or gender disparities were independent of the
race and gender-neutral factors known to be associated with business loan approval.
Access to business capital in the form of loans is measured by the probability of obtaining
a business loan among the 4,240 business owners in the three industries. It should be noted
that the dataset does not contain sufficient information on all ethnic groups to allow for a
separate examination of each group. Therefore, results are provided for a ll minorities and
Caucasian Females, referred to as Minority Business Enterprises (MBEs) and Woman -
owned Business Enterprises (WBEs) or collectively as MWBEs. The NSSBF records the
geographic location of the firm by Census Division instead of city, county, or state. Due to
insufficient data in the construction, professional services, and supplies and contractual
services industries, the sampling region was expanded to include the entire United States,
with independent variables indicating the effect on a business’s loan approval when located
in the St. Louis Metropolitan Statistical Area and the Census’ Midwest Region.
The results of the ordered logistic regression for each set of factors are presented in the tables
below.
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1. Ordered Logistic Regression Results for Business Loan Approval in the
Construction Industry
The ordered logistic regression results for business loan approval in the construction
industry based on the 12 variables analyzed in this model are depicted in Table 8.10.
Table 8.10: Ordered Logistic Model for the Business Loan Approval Analysis in the
Construction Industry
Statistically significant ordered logistic regression results for the construction industry
Business Loan Approval Analysis indicate the following:
a. Business Owner’s Minority Group and Gender Classification
Caucasian Females have a significantly lower probability of obtaining a business loan in
the construction industry than Caucasian Males.
Minority groups have a higher probability of obtaining a business loan in the construction
industry than Caucasian Males, but not at a significant level.
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b. Business Owner’s Characteristics
Business owners with a bachelor’s degree have a significantly higher probability of
obtaining a business loan in the construction industry.
Business owners with an advanced degree have a significantly higher probability of
obtaining a business loan in the construction industry.
c. Firm’s Credit and Financial Health
Businesses domiciled in the Midwest Region have a significantly higher probability of
obtaining a business loan in the construction industry.
Businesses domiciled in the St. Louis Metropolitan Statistical Area have a significantly
lower probability of obtaining a business loan in the construction industry.
Businesses with a low Dunn and Bradstreet credit score have a significantly lower
probability of obtaining a business loan in the construction industry.
Older businesses have a significantly higher probability of obtaining a business loan in the
construction industry.
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2. Ordered Logistic Regression Results for Business Loan Approval in the
Professional Services Industry
The ordered logistic regression results for business loan approval in the professional
services industry based on the 12 variables analyzed in this model are depicted in Table
8.11.
Table 8.11: Ordered Logistic Model for the Business Loan Approval Analysis in the
Professional Services Industry
Statistically significant ordered logistic regression results for the professional services
industry Business Loan Approval Analysis indicate the following:
a. Business Owner’s Minority Group and Gender
Classification
Caucasian Females have a lower probability of obtaining a business loan in the professional
services industry than Caucasian Males, but not at a significant level.
Minority groups have a significantly lower probability of obtaining a busin ess loan in the
professional services industry than Caucasian Males.
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b. Business Owner’s Characteristics
Business owners with a bachelor’s degree have a higher probability of obtaining a business
loan in the professional services industry, but not at a significant level.
Business owners with an advanced degree have a higher probability of obtaining a business
loan in the professional services industry, but not at a significant level.
c. Firm’s Credit and Financial Health
Businesses domiciled in the Midwest Region have a significantly higher probability of
obtaining a business loan in the professional services industry.
Businesses with a low Dunn and Bradstreet credit score have a significantly lower
probability of obtaining a business loan in the professional services industry.
3. Ordered Logistic Regression Results for Business Loan Approval in the
Supplies and Contractual Services Industry
The ordered logistic regression results for business loan approval in the supplies and
contractual services industry based on the 13 variables analyzed in this model are depicted
in Table 8.12.
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Table 8.12: Ordered Logistic Model for the Business Loan Approval Analysis in the
Supplies and Contractual Services Industry
Statistically significant ordered logistic regression results for the supplies and contractual
services industry Business Loan Approval Analysis indicate the following:
a. Business Owner’s Minority Group and Gender
Classification
Females have a higher probability of obtaining a business loan in the supplies and
contractual services industry than Caucasian Males, but not at a significant level.
Minority groups have a significantly lower probability of obtaining a business loan in the
supplies and contractual services industry than Caucasian Males.
b. Business Owner’s Characteristics
Business owners with a bachelor’s degree have a higher probability of obtaining a business
loan in the supplies and contractual services industry, but not at a significant level.
Business owners with an advanced degree have a higher probability of obtaining a business
loan in the supplies and contractual services industry, but not at a significant level.
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Business owners that use a personal credit card for business have a significantly lower
probability of obtaining a business loan in the supplies and contractual services industry.
c. Firm’s Credit and Financial Health
Businesses domiciled in the Midwest Region have a significantly higher probability of
obtaining a business loan in the supplies and contractual services industry.
Businesses with existing capital leases have a significantly lower probability of obtaining
a business loan in the supplies and contractual services industry.
Businesses with a low Dunn and Bradstreet credit score have a significantly lower
probability of obtaining a business loan in the supplies and contractual services industry.
Older businesses have a significantly higher probability of obtaining a business loan in the
supplies and contractual services industry.
VII. Conclusion
Three regression analyses were conducted to determine whether there were factors in the private
sector which might help explain any statistical disparities between MWBE availability and
utilization identified in the Disparity Study. The three analyses examined the following outcome
variables—business ownership, business earnings, and business loan approval.
These analyses were performed for three industries—construction, professional services, and
supplies and contractual services. The regression analyses examined the effect of race and gender
on the three outcome variables. The Business Ownership Analysis and the Earnings Disparity
Analysis used data from the 2007 through 2010 PUMS datasets for the City of St. Louis and St.
Louis County, and compared business ownership rates and earnings for MWBEs to those of
similarly situated Caucasian Males. The Business Loan Approval Analysis used the 2003 NSSBF
dataset and compared business loan approval rates for MWBEs to those of similarly situated
Caucasian Males.
A. Business Ownership Analysis
The Business Ownership Analysis examined the impact of different explanatory variables on an
individual’s probability of owning a business. Controlling for race and gender- neutral factors, the
Business Ownership Analysis results show statistically significant disparities in the probability of
owning a business for minorities and females when compared to similarly situated Caucasian
Males. Caucasian Females experience the greatest disparity as they are significantly less probable
to own a business in all industry specifications. African Americans and Asian Americans are
significantly less probable to own a business in two of the industries; professional services and
goods and other services for African Americans, and construction and professional services for
Asian Americans.
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Hispanic Americans, Native Americans, and Other Minorities did not have any statistically
significant findings.
Table 8.13 depicts the Business Ownership regression analysis results by race, gender, and
industry.
Table 8.13: Statistically Significant Business Ownership Disparities
Race/
Gender Construction Professional
Services
Supplies and
Contractual Services
Caucasian Female Yes Yes Yes
African American Yes Yes
Asian American Yes Yes
Hispanic American Yes Yes
Native American
Other Minority
B. Business Earnings Analysis
Controlling for race and gender-neutral factors, the Business Earnings Analysis documented
statistically significant disparities in business earnings for minorities and females when compared
to similarly situated Caucasian Males. Caucasian Females have lower business earnings at a
statistically significant level for two of the industries – professional services and supplies and
contractual services. African Americans and Asian Americans have significantly lower business
earnings in the supplies and contractual services industry. Finally, Other Minorities have
significantly lower business earnings in the professional services industry.
Hispanic Americans and Native Americans had no statistically significant findings.
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Table 8.14 depicts the Earnings Disparity regression results by race, gender, and industry.
Table 8.14: Statistically Significant Business Earnings Disparities
Race/
Gender Construction Professional
Services
Supplies and
Contractual Services
Caucasian Female Yes Yes
African American Yes
Asian American Yes
Hispanic American
Native American
Other Minority Yes
C. Business Loan Approval Analysis
Controlling for race and gender-neutral factors, the Business Loan Approval Analysis reveals
statistically significant disparities for MWBEs when compared to similarly situated Caucasian
Males. Caucasian Females had a statistically significant disparity in the construction industry, and
minorities had statistically significant disparities in the professional services and supplies and
contractual services industry.
The statistically significant disparity documented for MWBEs when compared to similarly situated
Caucasian Males points to the presence of race and gender-based discrimination as a factor in
access to business capital. Access to business capital in the private sector constitutes a major factor
in business development, continuity, and growth. The documented disparity in MWBEs’ access to
business capital may have adversely impacted the number of these businesses in the construction,
professional services, and other supplies and contractual services industries available to perform
MSD’s contracts during the Study period.
Table 8.15 depicts the Business Loan Approval Analysis regression results by race, gender, and
industry.
Table 8.15: Statistically Significant Business Loan Approval Disparities
Race/
Gender Construction Professional
Services
Supplies and
Contractual Services
Caucasian Female Yes
Minority Yes Yes
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D. Regression Findings
The analyses of the three outcome variables document disparities that could adversely affect the
formation and growth of MWBEs within the construction, professional services, and supplies and
contractual services industries. In the absence of a race and gender -neutral explanation for the
disparities, the regression findings point to racial and gender discrimination that leads to depressed
business ownership, business earnings, and business loan approval rates. Such discrimination
creates economic conditions in the private sector that impede minorities and females’ efforts to
create and grow businesses. An impact of these private sector conditions is manifested in MWBEs’
lower business formation rates.
It is important to note there are limitations to the application of the regression findings. No matter
how discriminatory the private sector may be, the findings cannot be used as the factual basis for
a government-sponsored, race-conscious MWBE or DBE program. Therefore, caution must be
exercised in the interpretation and application of the regression findings. Nevertheless, the findings
can be a formula for developing race- neutral programs to eliminate identified barriers to the
formation and development of MWBEs.
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Anecdotal Analysis
CHAPTER 9: Anecdotal Analysis
I. Introduction
This chapter presents anecdotal testimony gathered through in-depth, one-on-one interviews and
business community meetings. The purpose of this examination is to determine whether the
Metropolitan St. Louis Sewer District (MSD) has committed acts that may have prevented
Minority and Women-owned Business Enterprises (MWBEs) to access MSD contract
opportunities. The anecdotal testimony was analyzed to supplement the statistical findings of
MSD’s Disparity Study.
The importance of anecdotal testimony in a disparity study was discussed in the landmark case,
City of Richmond v. J.A. Croson Co.277 (Croson). The United States Supreme Court, in the 1989
Croson decision, questioned whether or not anecdotal testimony can be used by local governments
to justify remedial, race-conscious relief in the relevant market area. The Court opined that
“evidence of a pattern of individual discriminatory acts can, if supported by appropriate statistical
proof, lend support to a [local entity's] determination that broader remedial relief [be] justified.”278
Anecdotal testimony of individual discriminatory acts, when paired with statistical data, can
document the routine practices affecting MWBEs’ access to contr acting opportunities. The
statistical data can quantify the results of discriminatory practices, while anecdotal testimony
provides the human context to understand the numbers. Anecdotal testimony from business owners
provides information on the types of barriers that are perceived to exist within the market area and
affect the development of MWBEs. In addition, anecdotal testimony was solicited from prime
contractors, subcontractors, and suppliers who received an MSD contract to provide a
comprehensive perspective of their experiences.
A. Anecdotal Evidence of Discrimination - Active and Passive
Participation
Croson authorizes anecdotal inquiries along two lines. The first line of inquiry investigates active
government discrimination as reflected in the award of prime contracts or the government’s
procurement policy and practices.
Anecdotal evidence of passive discrimination pertains to the actions of private sector entities.
Thus, the second line of inquiry examines the government’s passive support of exclusionary
practices that occur in the market area in which its funds are infused. Passive discrimination results
from government officials knowingly using public funds to contract with companies that
277 City of Richmond v. J.A. Croson Co., 488 U.S. 509 (1989).
278 Id.
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discriminate against MWBEs or their failure to take positive steps to prevent discrimination by
contractors who receive public contracts.279
The Court cautioned that anecdotal evidence of discrimination is entitled to less evidentiary weight
than statistical findings, because the evidence concerns more private than government-sponsored
activities. Less weight should be afforded to personal accounts of discrimination that reflect
isolated incidents compared to anecdotal evidence of a municipality’s institutional practices
because of the impact that institutional practices have on market conditions.280 Nonetheless, when
paired with appropriate statistical data, anecdotal evidence of either active or passive forms of
discrimination can support the imposition of a race or gender -conscious remedial program.281
As Croson points out, jurisdictions have at their disposal “a whole array of race-neutral devices to
increase the accessibility of City contracting opportunities to small entrepreneurs of all races.”282
Nevertheless, the Court found that anecdotal evidence has value because it can paint a portrait of
the practices and procedures that generally govern the award of public contracts in the relevant
market area. These narratives, according to Croson, can identify specific generic practices that
MSD can implement, improve, or eliminate to increase contracting opportunities for businesses
owned by all citizens. In this Study, the utility of the anecdotal evidence is considered within the
parameters of the law.
B. Anecdotal Methodology
The methods used to collect anecdotal information consisted of soliciting public comments from
the business community meetings and one-on-one interviews. Extensive effort was undertaken to
solicit business owners who were willing to provide anecdotal accounts. The sources used to
identify potential interviewees included business community meetings, certification directories,
and outreach efforts. All of the business owners interviewed were domiciled in the geographical
market area. The boundaries of the market area are described in Chapter 4: Market Area Analysis.
1. Business Community Meetings
The initial phase of the anecdotal process was the collection of public comments at two business
community meetings that were held in April 2019. The objectives of the meetings were to
announce the Study; inform the business community about the Study's legal framework,
methodology, and timeline; and give business owners the opportunity to speak with MSD
representatives regarding contracting opportunities. The meetings also sought to solicit the
business community’s support for the Study and to identify business owners willing to participate
in the anecdotal interviews.
279 Croson, 488 U.S. at 491-93, 509.
280 Concrete Works of Colorado v. City and County of Denver , 36 F.3d at 1530 (10th Cir. 1994): "while a fact finder should accord less weight
to personal accounts of discrimination that reflect isolated incidents, anecdotal evidence of a municipality’s institutional practices carry
more weight due to the systemic impact that such institutiona l practices have on market conditions.”
281 Croson, 488 U.S. at 509.
282 Id.
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The outreach efforts to promote the two business community meetings targeted firms in the
building construction, non-building construction, engineering professional services, and purchases
and other services industries. The meetings were held at the following times and locations listed
in Table 9.1:
Table 9.1: Metropolitan St. Louis Sewer District Community Meetings
Business Community Meetings
Location Date Time
Moolah Shrine Center April 22, 2019 1:30 p.m.
Harrison Education Center April 23, 2019 9:00 a.m.
Testimony from these meetings has been incorporated in this chapter.
2. One-on-One Interviews
The second phase of the anecdotal process was screening businesses that indicated an interest in
being interviewed. A screener was used to collect basic demographic data and specific information
to determine the relevant experiences of the business owner. The screener also captured
information regarding the interviewee’s experience with public contracting and willingness to
recount the experiences to a trained interviewer.
In the one-on-one interviews, anecdotal probes were used to solicit information from the
interviewees. The questions sought to determine if the business owner encountered or had specific
knowledge of instances in which formal or informal contracting practices had a positive or adverse
impact on MWBEs during the January 1, 2013 to December 31, 2017 study period. The interviews
were completed with business owners who provide the types of goods and services procured by
MSD.
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II. Anecdotal Findings
The anecdotal testimony was gathered through in-depth one-on-one
interviews and comments from the business community meetings.
The interviewees included business owners that worked on a building
construction, non-building construction, engineering professional
services, or purchases and other services project in the City or County
of St. Louis. The anecdotal accounts reported by the interviewees’
represent their experiences working primarily on projects within
MSD’s market area.
The interviewees were asked about their experiences navigating
MSD’s procurement process, challenges obtaining financing, and
barriers based on race and gender. The participants were also asked
if they had any recommendations to enhance MSD’s Supplier
Diversity Program.
A. Racial Barriers and Sexism
Some minority business owners believe that racial barriers and
sexism have affected their business development. The perceptions of
their experiences are presented below.
A minority female owner of an engineering professional services firm
described biases in her industry:
I am not supposed to be in the room. Many of the meetings
I attend, I'm the only engineer. Now, there are other
minorities in the room doing a great job serving cocktails.
Being an engineer, others can make me feel like I do not
belong. Many times I feel disrespected and want to cry. But
I remind myself you are going to network and get through
this.
A minority male owner of a purchases and other services firm
believes his race has had a negative impact on some of his business
relationships:
No one has ever said, "Well, the reason we're treating you
this way is based on your race." Nobody is crazy or dumb enough to say that.
But when you consider all the factors, with everything else being equal, the
only thing that differentiates me from some of these other businesses getting
The statistical findings
revealed that MWBEs have
the capacity to perform
substantial formal
contracts.
∞
MWBEs demonstrated the
capacity to perform
engineering professional
services prime contracts as
large as $20,449,983.
∞
MWBEs demonstrated the
capacity to perform non-
building construction
professional services prime
contracts as large as
$10,408,339.
∞
MWBEs demonstrated the
capacity to perform
purchases and other
services contracts as large
as $415,785.
∞
PRIME CONTRACTOR
AVAILABILITY
ANALYSIS, CHAPTER 5
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the work is race. We have the equipment and the talent. For whatever reason,
are passed over.
A minority male owner of a purchases and other services company
believe he is subjected to heightened scrutiny because of his race:
I come under much more scrutiny than others because of
my race. They are not saying, "Hey, because you are
black.” But you know the feeling. I'm in a blue-collar
industry, but I have to work twice as hard just to be
average. But I don't get any additional work. I get the bare
minimum. MSD only wants to spend 10% of this project
with minorities. I can offer so much more. But I get the
bare minimum.”
A minority female owner of a purchases and other services company
reported that race has negatively impacted her business:
My race is a negative influence on my business. It's not a
standard practice for someone who's been in business as
long as I have and whose credit rating is as good as my
credit rating to still get unfavorable purchasing terms.
For a freight broker, credit rating determines the number
of days that it takes for a freight broker to pay a motor
carrier after the carrier delivered a load. My credit rating
is outstanding, and that information is available to every
carrier who wants to do business with me. But they still
tell me flat-out, "Oh, you’re going to pay half up front,"
or "I have to pay as soon as I deliver the load."
A minority female owner of a purchases and other services company regularly experiences
discrimination in the marketplace:
As a woman-owned business and a minority, it's tough trying to get business.
Most of the time, you know you are being discriminated against. We have to
prove ourselves every day.
The size distribution
analysis revealed that
79.81% of the prime
contracts awarded by
MSD were valued at less
than $100,000.
∞
Only 3.06% of MSD’s
awarded prime contracts
were valued at
$3,000,000 and greater.
PRIME CONTRACTOR
AVAILABILITY
ANALYSIS, CHAPTER 5
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A minority female owner of a construction company describes the impact race has had on her
business opportunities:
Being a minority puts us at an unfair advantage when trying to procure work
with MSD. In the market area, the perception of MWBEs is lower quality work
or poor performance. Or they don't know how to run their business.
A minority female owner of an engineering professional services firm reported that her expertise
is questioned because of her race:
I've been asked, “How is it that you came up with a
technology like this?” Well, in my mind, why can't I
come up with innovative technology? But I understood
that they were questioning me as an African American
female. I am not supposed to be an engineer or a
developer. They believe that I am out of my lane. I went
to an all-Caucasian conference and extended my hand
and the gentleman did not even want to shake my hand.
So, it's very challenging. And I believe, in the mindset
of many people, if you are a black woman, you are not
supposed to be an engineer.
A minority male owner of a construction company believes
minorities still experience discrimination in MSD’s market
area:
Every business has the exact same challenges. The only
difference is that we African Americans experience
racial discrimination. Everyone has to obtain capital,
labor, and insurance. So, those are challenges. We
have to deal with discrimination in addition to all those
other things. It is everywhere and has prevented
minority-owned businesses from flourishing.
A minority female owner of a purchases and other services
company believes minorities experience more difficulties than
non-minorities in trying to be competitive:
Hispanic Americans
represent 6.41% of the
available engineering
professional services
businesses and received
0.00% of the dollars on
engineering professional
services contracts valued
under $25,000.
∞
The Supreme Court in
Croson held that an
inference of
discrimination can be
made if the disparity is
statistically significant.
PRIME CONTRACTOR
DISPARITY ANALYSIS,
CHAPTER 6
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It is especially difficult for minority female women business owners to
experience equity in contracting. We are put in a less competitive position.
A minority male owner of a construction company reported that he is treated differently by prime
contractors because of his race:
We get treated differently on jobs. The microscope is
always on the minority company, whether or not you
are needed to meet a goal. They nitpick. In most of
those cases, Caucasian contractors seem like they
always have their eye on the minority companies. If
you do anything wrong, that gives them a reason to
write you up, not call you back, or kick you off the job.
Usually, the spot is filled by a non-minority company.
B. Difficulty Breaking into the Contracting
Network
A minority male owner of a purchases and other services
company described the obstacles minority firms face trying to
secure contracting opportunities:
Our challenges are tenfold: from trying to get
financing to contractors using us to meet a goal
without giving us any work. I can offer so much more.
A minority female owner of a purchases and other services
company explained why she believes breaking into MSD’s
contracting network is difficult:
When we try to bid jobs, it seems like MSD already
knows who they are going to select. So, for a couple of
years I stopped pursuing work anymore. There is a lot
of politics. I'm discouraged, but a lot of these big jobs
are already preset. We go through all the motions and
spend a lot of time, but it just a waste of our time. So,
we just stick with the little jobs. So many times, we
Five of MSD’s 55
engineering professional
services prime contractors
received $195,845,510, or
70% of the total prime
contract dollars.
∞
Six of MSD’s 102 non-
building construction
prime contractors
received $534,385,441, or
70% of the total prime
contract dollars.
∞
Seven of MSD’s 52
purchases and other
services prime contractors
received $7,955,651, or
70% of the total prime
contract dollars.
----
PRIME CONTRACTOR
UTILIZATION
ANALYSIS, CHAPTER 2
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feel that we try to compete, but it is a waste of time because the selection is
already pre-done.
A minority female owner of a purchases other services company described the challenge
suppliers experience attempting to break into the contracting network:
It is challenging because a lot of companies have longevity and created a
monopoly on the industry. So, some manufacturers and suppliers did not want
to do business with us, because they had exclusive contracts with other larger
companies. It has lightened up just a little bit. I have been able to inch my way
through. It still can be because sometimes we are told, "No, we already have a
supplier there.” Or we have an agreement not to supply anyone else in the
area. So, it can be very challenging. They will tell you that they have when they
do not. Or “we can't have a supplier
within a certain number of miles” or something ridiculous. But they should not
have a monopoly on the industry.
A minority male owner of a construction firm explained why he has been unable to get work
from MSD:
Although I have four trucks, I have been turned down for work because I’m
unable to wait 90 days for the contractor to pay me. I haven’t been able to
move up the ladder and get my company financially stable to wait that long for
payment. So, that is very frustrating.
A minority female owner of a purchases and other services company believes the same
companies get the work in her industry:
Generally, most of the contracts are awarded to the same companies. It is very
difficult to get in. It has a lot to do with networking and who knows you and
who's willing to bring you in. It’s really relationship-based as opposed to skill
or competency-based.
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A minority female owner of a purchases and other services company believes she is locked out
of contracting opportunities with MSD:
I believe those opportunities are closed to me. It seems like MSD has maybe
five or six companies that they generally work with. I have to work as a
subcontractor. So, inclusion for me is in the set-aside on MSD’s projects. That
is the only way I'm able to get in the door. It seems like I've been shut out of
the process.
A minority male owner of a construction company believes it is
difficult for MWBEs to build the necessary relationships to break
into the contracting community:
I would definitely say starting out it was very difficult to
get my foot in the door. Once we did get our foot in the
door, we performed the work and were successful on
the project. We were complimented on our work and
invited to work on more projects. But I do think that it
is very difficult for an MWBE to get their foot in the
door and participate in the bidding process. I would
say that it's due to a combination of things. I think it's
the inability to build relationships. The general
contractors use vendors that they are familiar with.
A minority female owner of a purchases and other services
company believes that relationships with MSD decision makers
are needed to be successful in the bidding process:
We have bid on MSD projects in the past. But we
always lose by five bucks to the bigger companies that
have better pricing than us.
C. Good Old Boy Network
The good old boy network is an informal network that could
advantage friends, colleagues, and associates in the award of
prime contracts and subcontracts. Many instances were described where interviewees believed that
the good old boy network operates as a barrier to their participation on MSD’s contracts.
Non-minority males
represent 47.04% of the
available building
construction businesses
and received 95.56% of
the dollars on building
construction contracts
valued from $25,000 to
$8,270,000.
∞
Non-minority males
represent 41.03% of the
available engineering
professional services
businesses and received
70.96% of the dollars on
engineering professional
services contracts valued
from $25,000 to
$500,000.
∞
PRIME CONTRACTOR
AVAILABILITY
ANALYSIS, CHAPTER 5
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A Caucasian female owner of a purchases and other services firm
believes MSD has preferred contractors. And that MSD can do more
to encourage its vendors to subcontract with others who have not
worked for MSD.
We have heard, "Well, we already have this company, and
they already work with these three vendors.” But if they
don't think about it differently, then they will never change
the perception that it's going to be the same old, same old.
And if you keep doing it that way, there's no incentive for
anyone else to try to play. Why bother? Here's the thing, if
you're just going to hire the incumbent because it's easier
then don't put out an RFP. Don't waste the time of the
bidders, just extend the contract. Don't go through the
motions if you have no intention of making the change.
A minority male owner of a purchases and other services company
reported that MSD’s prime contractors prefer to work with the same
subcontractors:
Any big company I go to says, “we already have vendors.” Since that is the
case, why have a diversity program, why host networking events, and why do
companies need to get certified? All these things take away my time. I would
rather bid on fewer opportunities than waste my time.
A minority female owner of a purchases and other services company also believes the same
contractors get most of the work:
Some of the larger companies are longstanding staples in our area. They have
been here the longest, and they have the relationships. Some of them have been
the only players for decades. Trying to get to convince the decision makers that
we can provide better service and more personalized service can be a
challenge
The capacity analysis
indicates that non-
minority males are not
awarded more contracts
because of any single
socioeconomic factor or
combination of factors.
∞
PRIME CONTRACTOR
AVAILABILITY
ANALYSIS, CHAPTER 5
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A Caucasian female owner of a purchases and other services firm described why she believes
small businesses are locked out of contracting opportunities:
I couldn't golf if you paid me. But deals are made on the golf course after a
couple of martinis. There is still that mentality of you are out with your good
buddy. One of my suppliers takes clients to sports events and they drink too
much and they have fun. That is just the status quo. Especially if you're on a
first name basis they can say, "Hey, can you do me a favor? I need this by next
Thursday.” They'll find a way to single source it. Some competitors try to make
it a single source thing because they are already in. So, they use that as the
excuse, and it’s poppycock.
The male African American owner of a haling company said that certain trucking companies
control the marketplace:
Certain companies control the trucking infrastructure on MSD’s construction
projects. They have the power, and it’s unfair. There may be 50 individual
small companies, and some may be certified. But the contractor is only going
to deal with the bigger established companies that can provide half of the
trucks on their own.
D. Difficulty Navigating the Bid Process
Several business owners described barriers they encountered in trying to navigate MSD’s bid
process, which diminished their ability to prepare a responsive bid.
A minority female owner of a construction company reported that it is difficult to learn about
MSD’s bidding opportunities:
We have to be intentional to find opportunities. A missed opportunity is missed
revenue.
A minority female owner of a purchases and other services company is unsure how to learn about
bid information regarding the services she provides:
I reached out to the person at purchasing, and I filled out the necessary
paperwork to become a vendor. I never received any other follow-up on their
part. I never got any leads. They never responded back with a confirmation.
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When I applied at other agencies to become a
vendor, I received a vendor number and protocols as
to where to send invoices, log-in information on how
to search for bids. I have never received that from
MSD after I submitted my information. I know they
are doing business, but never received anything else.
A minority male owner of a construction company reported that
it is difficult learn the identity of the successful bidder:
Usually, the projects are posted on their website, but
it's difficult to find out who has won the project and
the general contractor. They should publicize the
winner so small minority businesses can reach out to
them for potential work.
A minority female owner of a construction company believes
that some prime contractors engage in bid shopping which
disadvantages subcontractors:
I try to prevent prime contractors from shopping our
numbers. I have been told that my competitors mark-
up is 8 percent, and could I do it with a 5 percent
mark-up. Why would I do that? Why undercut
another contractor?
E. Excessive Certification Procedures
A minority male owner of a purchases and other services
company believes that the MWBE certification process can be
burdensome for small businesses:
There seems to be more political red tape to obtain a
minority business certification; it required a lot of
paperwork. I'm truly aggravated with what it takes
for a minority business to prove that they are a
minority business. It's just another way to keep
minority businesses from being able to operate in the
Hispanic Americans
represent 3.76% of the
available non-building
construction businesses
and received 0.69% of the
dollars on non-building
construction contracts
valued under $25,000.
∞
Asian Americans represent
6.84% of the available
engineering professional
services businesses and
received 0.00% of the
dollars on engineering
professional services
contracts valued under
$25,000.
∞
Caucasian Females
represent 23.50% of the
available engineering
professional services
businesses and received
5.90% of the dollars on
engineering professional
services contracts valued
under $25,000.
∞
Native Americans
represent 1.71% of the
available engineering
professional services
businesses and received
0.00% of the dollars on
engineering professional
services contracts valued
under $25,000.
PRIME CONTRACT
DISPARITY CHAPTER,
CHAPTER 6
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mainstream. We haven't received any help from MSD in regard to being a
minority business.
A Caucasian female owner of a purchases and other services company
also believes the certification process is burdensome:
It’s difficult trying to get all the paperwork together and meet
all the other requirements when I'm a legitimate business. I
have to make revenue. And the number of hours I had my
assistant working on it does not seem worth it.
A minority male owner of a construction company reported that he has
knowledge of MWBE front companies:
I have seen this abuse. Sometimes on the WBE side where a
wife comes into a construction company with a husband, the
husband is the craftsperson.
A minority male owner of a purchases and other services company is also
aware of fronts:
I've seen fronts firsthand. Yeah. I'm not going to say any
names, but there is one particular company that wanted as
much MSD work as they could get, but they weren't minority-
owned. They did a little “enabling” to appear to be minority-
owned, but they really weren't. But the effect is that it pushes
us out of competition. They literally obliterated us.
F. Barriers to Financing
Access to adequate financing is vital to business survival and especially crucial to the solvency of
small, minority, and new businesses. Many business owners reported challenges obtaining
financing for their small companies.
A minority male owner of a purchases and other services company has experienced difficulty in
securing financing:
The capacity eSurvey
revealed that willing
minority and woman-owned
businesses have
demonstrated capacity
comparable to similarly
situated willing non-
minority male-owned
businesses.
Despite similar educational
attainment, years in
business, and number of
employees, non-minority
male-owned businesses still
received most of MSD’s
contracts as detailed in
Chapter 2: Prime Contractor
Utilization Analysis.
PRIME CONTRACTOR
UTILIZATION
ANALYSIS, CHAPTER 2
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It has been difficult. Do they say it’s because of my race? Of course, they will
not, because they would be penalized for not being fair and equitable. But I
don't know. The only thing that I can think of is race.
A minority female owner of a construction company reported that access to financial resources is
a challenge for minority businesses:
Access to capital whether it's bonding or funding—our rates tend to be higher
rates than non-MWBE contractors.
A minority female owner of a purchases and other services company believes that access to capital
is an issue for MWBEs:
First of all, it's very hard to obtain funding. Not having working capital means
we’re unable to bid on larger projects.
A minority female owner of a purchases and other services company believes that access t o
funding for African American women in technology is especially difficult:
I have been a part of the ecosystem in St. Louis for quite some time. I applied
for various local funds that are advertised for minority women in technology. I
have been denied for each of them despite my experience and reputation. In St.
Louis, African American women are not highly regarded in the technology
industry.
A minority owner of a construction company reported that access to financing is extremely
difficult for MWBEs:
Probably 90% of minority and women-owned businesses face challenges
getting access to capital, insurance, and bonding. We don’t get the financing,
so we are missing the needed capital flow.
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G. Late Payments
Interviewees shared how late payments affected their
businesses.
A minority male owner of an engineering professional services
company experienced late payments from MSD’s prime
contractors:
If you’re not the prime contractor, payment is an
issue. We are at the mercy of the prime contractor.
A minority female owner of a construction company described
the impact MSD’s payment practices have on subcontractors:
MSD usually pays from 60 to 90 days. And so, for
subcontractors, we have to add another 30 days for
payment.
A minority male owner of a construction company described
his experiences with late payments from prime contractors:
We have not had late payments from MSD, but I have
had late payments from prime contractors. We have
had issues getting payments on time. Our terms are
net 30 with no retention. Most of our work is done at
the beginning of the project; therefore, cashflow is
essential and we simply can't wait six to nine months for the project to get
completed before we get paid. I think that should be an issue that MSD can
work on.
A minority male owner of a construction company reported that late payment from prime
contractors is an issue for him and his colleagues:
Some prime contractors want us to wait 60 to 90 days for my first payout from
the job. So, this is very frustrating. It’s almost like they wait purposefully
because they know that only the financially fit companies are going to be able
to perform the job. It’s not fair. It doesn’t allow opportunity for smaller
Non-minority males
represent 36.13% of the
available subcontract
building construction
businesses and received
70.94% of the dollars on
building construction
contracts.
∞
Non-minority males
represent 25.12% of the
available subcontract
engineering professional
services businesses and
received 40.52% of the
dollars on engineering
professional services
contracts.
∞
SUBCONTRACTOR
DISPARITY ANALYSIS,
CHAPTER 7
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minority companies like me to compete. It’s a daily conversation that my peers
and other companies are having regarding MSD work.
A minority male owner of a landscape design firm says late payments have been an issue in
contracting with MSD:
I don't know if it's MSD or the prime contractor, but there always seems to be
this huge lag time. We ran into that a lot when we worked on MSD projects.
We had to take money from other projects to fund what we would do for MSD.
That's something that needs to change. MSD told us to talk to the prime
contractor because they claim the prime contractor was paid.
H. Supplier Diversity Program
The interviewees reported on their observations regarding MSD’s Supplier Diversity Program.
Recommendations to enhance the programs were also offered by the business owners.
A minority female owner of a construction company believes the lack of prime con tract MWBE
goals has made it difficult for her to obtain prime contracting opportunities:
The MWBE Program forces us to be subcontractors. It also doesn't allow us to
build relationships with MSD project managers, the procurement team, or
even the diversity team, because we are always working through another
company. I think that the intent of the original program related to the disparity
study was good. I think that the interpretation of the program and how it rolled
out in reality had some unintended consequences for MWBEs. But as one of
the largest public agencies in the market, we all want to work with them. So,
hopefully there's a way to level the playing field a little bit so that we can
actually do that.
A Caucasian female owner of a construction company explained why MSD’s Supplier Diversity
Program has not benefitted her company:
From personal experience, I have not gotten much benefit from it. I never
received help with anyone on the plan holders list. I have not been able to get
help to point me in the right direction or answer any questions so that I can
actually put a bid to it.
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A minority female owner of an engineering professional services firm expressed frustration
regarding the perception of African American business owners:
One thing that really hurts is the fact that many of the narratives in many
businesses make it seem as though African Americans are not trying and are
not interested in opportunities. So, for example, many narratives say, "Oh, we
only hire 3% African American. Oh, we provide these opportunities, but they
do not apply." I believe that 3% as far as the number of African Americans
that are in the more professional industries, technology, science, math, is not
because they don't want the opportunities. They're not given the opportunities.
And many African Americans submit application after application after
application and are denied each time without given a chance.
A minority female owner of a construction firm believes that the Supplier Diversity Program could
do more to build the capacity of MWBEs:
The goal of the MSD program is to build capacity and grow, but their program
is actually hurting MWBE contractors. I, as 100% minority owned company,
can only participate as a subcontractor. They don't count my participation,
and we cannot self-perform as a prime contractor since they don't count us. So,
I am forced to always be a subcontractor.
A minority male owner of a construction company reported that the Supplier Diversity Program
has had a positive impact on his small business, albeit seldomly:
It’s helped because there are certain jobs where I’ve been requested by a
broker. When they needed minority participation on a job has allowed me to
come out of the pack of and get the spot. But that hasn’t been very often.
A minority male owner of a construction company explained why he no longer responds to MSD’s
bids:
Quite frankly for myself and my peers, until we know the goals are going to be
enforced, we’re not going to waste our time bidding. Why would I spend my
office hours estimating hours when I’m going after a project that may not have
an MBE requirement? Because the prime contractors don’t care if they use us
or not, regardless, if we do good work or not.
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Anecdotal Analysis
Several MWBEs commented that their MWBE certifications did not provide any benefit to their
companies:
I have not gotten any work because of my MWBE certifications. My
certification has not been the basis of any of the business that I've received.
I have not received any work from my MWBE certification.
Quite frankly, having a minority certification hurts a lot of companies. Smaller
minority companies are abused for their certification by being given scopes of
work that do not yield profits on the job.
I have been in business for decades, and I have only received one award that I
will say was given to us because it was a woman minority award.
Less than five percent of my business has come from my MWBE certification.
MWBE certification was seen as helpful by other companies:
Yes, my MWBE certification have given us the opportunity to win business.
Oh, certainly the Supplier Diversity Program has value. That is the reason we
are included on projects. Without the MWBE certification, it's hard to compete
with the other contractors.
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Absolutely the Supplier Diversity Program has afforded me an opportunity to
compete with the larger firms. Without it, we'd be shut out. I still have to be
competitive, but we get an opportunity, not an advantage.
I. Exemplary Practices of MSD
Several business owners described exemplary practices they had witnessed in their dealings with
MSD.
A minority male owner of an engineering professional services company provided examples of
MSD staff who were helpful:
The engineering director when I call, always makes arrangement to
accommodate. MSD is a large organization. MSD is a good organization. I
still believe if these provisions and amendments can be made in good faith and
no delay, it shouldn’t be looked at as though we’re trying to take away
something, when really, we’re only looking for fairness and equity and justice
for everybody.”
A representative for a majority-owned construction company believes that MSD’s Supplier
Diversity Program is necessary:
The Supplier Diversity Program is absolutely necessary for the community in
order for minority and women business owners to get a piece of the pie. It has
helped our company because we actually meet our goals which is part of our
business model. So, if we were not meeting our goals, then our business model
would be a failure.
The minority owner of an engineering professional services company described her positive
experience with several MSD staff members:
When the supervisor showed up on the job from MSD, they provided guidance
on completing our work. Basically, he told us to bring in a machine and dig
about six to eight inches down and pull out the rock and then bring in dirt. We
were very appreciative because it saved us time, energy, effort, and money.
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A minority male owner of a purchases and other services
company spoke highly of the Supplier Diversity Program team:
I certainly believe they are of extreme value. If they
were not there, some opportunities would not
materialize for MBEs or WBEs. So, I do believe that
these programs are very beneficial for all the MWBE
companies in the area. We feel they treated us very
well.
A minority male owner of a construction firm spoke highly of
the Supplier Diversity Program:
They have done a good job. I think there's a
commitment to working with MWBEs. I think they
are staffed with some pretty good people who have
made a difference. They have provided access for
minorities and women through their program. I think
it's probably one of the better programs in the
metropolitan area.
1. Recommendations to Enhance MSD’s Procurement
Standards
The interviewees provided recommendations to enhance and
expand MSD’s procurement standards to make them more
transparent and efficient.
A representative for majority-owned construction company
recommends increased communication and transparency:
A lot more transparency and a better communication
channel is needed. Sometimes we don't know there's
a problem until the dam bursts. We want to know
about problems beforehand. Now, if that means that
I have to come into your office every day, I'm willing
to do that. If that means I got to send more emails,
SUBCONTRACT
DISPARITY ANALYSIS,
CHAPTER 8
African Americans represent
35.77% of available
subcontract building
construction services firms
and received 20.66% of the
subcontract dollars.
∞
Asian Americans represent
3.16% of available
subcontract building
construction services firms
and received none of the
subcontract dollars.
∞
Hispanic Americans represent
4.62% of available
subcontract building
construction services firms
and received 0.51% of the
subcontract dollars.
∞
Caucasian Females represent
19.22% of available
subcontract building
construction services firms
and received 6.49% of the
subcontract dollars.
∞
SUBCONTRACT
DISPARITY ANALYSIS,
CHAPTER 7
African Americans represent
35.77% of available
subcontract building
construction services firms
and received 20.66% of the
subcontract dollars.
∞
Asian Americans represent
3.16% of available
subcontract building
construction services firms
and received none of the
subcontract dollars.
∞
Hispanic Americans represent
4.62% of available
subcontract building
construction services firms
and received 0.51% of the
subcontract dollars.
∞
Caucasian Females represent
19.22% of available
subcontract building
construction services firms
and received 6.49% of the
subcontract dollars.
∞
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I'm willing to do that, but let's communicate, communicate, communicate, and
be more transparent.
A minority male owner of an engineering professional services firm suggests implementing
subcontracting goals on architecture and engineering work:
I would highly suggest that MSD re-instate the goals on design work.
A minority male owner of a construction company recommends implementing MWBE goals for
all ethnic groups:
If we’re a recognized MBE company, all ethnicities should participate in the
subcontract goals.
A minority female owner of a purchases and other services company recommends a more
transparent award process:
I think they could do more to explain the expectation for evaluating a bid or
making the process is easy to follow. They should be very specific about what
they're looking for.
A minority female owner of a purchases and other services firm recommends more small
contracting opportunities form MWBEs:
I would recommend more small contracts for small businesses. I don't want to
be just on a minority list. I want to be on the list, period. That's the first thing.
As a supplier, as a reputable company and supplier of their needs, that's the
first thing. I want to be on the list and not have to jump through a lot of hoops
to be on that list. If it's a perk to be a woman-owned or minority-owned
business, I want to be on that list as well.
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A minority male owner of an engineering professional services company recommends MSD
establish a formal process for issuing change orders:
First, formalize the change order process. I recommend formalizing the
reporting process for inspectors in issuing change orders.
A minority male owner of a construction company recommends MSD conduct more outreach to
MWBEs:
I would just like to see more outreach to minority businesses and women-
owned businesses. They could do more Zoom meetings with MWBEs so that
they can get to know us. A lot of times we are evaluated with what's on paper,
and I think that if MSD got to know us, they would see that we are capable of
doing the work and that we want to do the work.
An Asian American female owner of a party supply company wants more emphasis on women-
owned businesses:
I wish they put a little bit more highlight on woman-owned businesses. I wish
they could treat the union and woman business the same. And as far as more
information to get help from a woman of this niche, I wish they would send out
more information. So, we can get that information to what needs to be done for
that certification. And what's eligible out there.
A minority female owner of a purchases and other services company recommends that MSD host
more networking opportunities and instate penalties for not meeting MWBE goals:
More interaction with the prime contractors on the bidders list and MWBEs to
make them aware of upcoming projects. MSD should have strict penalties for
prime contractors that do not meet their goals.
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A minority male owner of a construction company suggests stricter enforcement of MWBE goals:
I suggest that they enforce their diversity goal by conducting audits on their
prime contractors with multi-million-dollar projects. This will ensure MWBEs
are not being uses as a pass-through.
A minority male owner of a construction firm suggests capacity building opportunities for
MWBEs:
I think they need to understand what barriers are preventing us from building
our capacity. This would improve the level of access minority-owned
businesses have to MSD contracts.
A Caucasian female owner of a construction company suggests that MSD publish an electronic
newsletter to provide more exposure to MWBEs:
One thing that could be extremely beneficial is to spotlight or a highlight
MWBEs. They could introduce their company and tell their story. The
newsletter could be monthly.
A minority female owner of a purchases and other services company recommends that MSD
conduct more outreach to MWBEs:
I think more emphasis is needed regarding outreach to MWBEs. Oftentimes,
we don't know about upcoming contracting opportunities.
A minority male owner of a construction company recommends more engagement from MSD
before starting the work:
When a project starts, there needs to be an in-person or Zoom meeting to
engage the minority subcontractors. Whether they are seasoned veterans or
new to the procurement process. When a project is awarded, there needs to be
that next step. They should talk about the contracting policies that impact them
and the contractual process in general. This could help complete the project
ahead of schedule, which will save time and money.
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Anecdotal Analysis
A minority male owner of an engineering professional services firm recommends modification to
the evaluation criteria for civil engineering firms:
If you have experience, it should not be required that it be recent. Most of the
time the skill to do this type of work doesn’t change that much in terms of the
design. Especially if you have a master’s degree. If you have a master’s, you
know a little bit more than someone who has a Bachelor’s.
III. Summary
The results of the anecdotal analysis from this Update Disparity Study was compared to anecdotal
findings from MSD’s 2012 Disparity Study in Table 9.2 below. The business owners that
participated in the anecdotal analysis for the 2012 Study described the barriers they encountered
working on or attempting to work on an MSD project. The barriers identified are listed in Table
9.2 below.
Table 9.2: Barriers Reported in MSD 2012 Disparity Study
Barriers Reported in MSD 2012 Disparity Study
Racial Barriers Harassment
Subjected to Higher Standards of Review Difficulty breaking into the contracting community
Difficulty meeting pre-qualification requirements Bid shopping
Inadequate lead time to respond to solicitations Difficulty negotiating supplier agreements
Knowledge of MWBE fronts Certification process challenges
Late payments Barriers to financial resources
Both the 2012 and 2021 MSD disparity studies presented a qualitative analysis of the barriers and
exemplary practices business owners experienced while working with or seeking work from MSD.
The interviewees were identified from business community meetings, certification directories, and
outreach efforts. The anecdotes were solicited through one-on-one interviews and the public
comment period at the business community meetings.
The interviewees that participated in the 2021 anecdotal analysis referenced fewer barriers to
accessing MSD contracts. The barriers are identified in Table 9.3 below:
Table 9.3: Barriers Reported in MSD 2021 Disparity Study
Barriers Reported in MSD 2021 Disparity Study
Racial barriers and sexism Difficulty breaking into the contracting network
Good old boy network Difficulty navigating the bid process
Excessive certification procedures Barriers to financing
Late payments
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Anecdotal Analysis
The 2021 participants did not report issues with pre-qualification requirements, bid shopping,
inadequate lead time or issues with supplier agreements. Business owners from both studies
commended the mission and services of MSD’s Supplier Diversity Program. Recommendations
were offered to further enhance the program’s effectiveness in fulfilling its mission. This anecdotal
information, together with the statistical findings will inform the remedies presented in Chapter
10: Recommendations.
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CHAPTER 10: Recommendations
I. Introduction
The 1989 landmark decision of City of Richmond v. J. A. Croson Co. (Croson)283 requires local
governments to demonstrate a strong basis in evidence of ongoing effects of past or present
discrimination in the relevant marketplace prior to the enactment of race-conscious remedies. To
establish a compelling interest to employ racial classifications, the evidence of discrimination must
be statistically significant.284 This Disparity Study (Study) update, authorized by the Metropolitan
St. Louis Sewer District (MSD) in 2018, determined that there is a disparity in the utilization of
Minority and Woman Business Enterprises (MWBE) that are ready, willing, and able to provide
building construction, non-building construction, engineering professional services, and purchases
and other services to MSD and its prime contractors during January 1, 2013, to December 31,
2017.
The prime contracts examined included building construction, non- building construction,
engineering professional services, non-engineering professional services,285 and supplies and
contractual services. At the subcontract level, the same industries were studied except for supplies
and contractual services.
In this update Study, a statistical disparity was found on prime contracts for all industries except
building construction. However, Caucasian females were underutilized in building construction
prime contracts. Additionally, a disparity was found on building construction, non -building
construction, and engineering professional services subcontracts. The assessment of the MWBE
participation is detailed in Chapter 6: Prime Contract Disparity Analysis and Chapter 7:
Subcontract Disparity Analysis, and summarized in this chapter. Additionally, this chapter
identifies programs and administrative policy changes that could remedy the effects of the
documented discrimination. These include both race and gender-conscious remedies, as well as
race and gender-neutral remedies.
The chapter is organized into four sections: (1) Introduction, (2) Disparity Analysis Findings,
which presents the statistically significant findings of disparity in the award of both prime contracts
and subcontracts, (3) Race and Gender-Conscious Remedies, which provides narrowly tailored
recommendations to address the statistically significant disparities, and (4) Race and Gender-
neutral Remedies, which details program and administrative policy changes to address the
documented discrimination.
283 City of Richmond v. J.A. Croson Co., 488 U.S. 469 (1989).
284 Id.
285 This 2021 study did not provide a separate analysis of non -engineering professional services.
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II. Disparity Analysis Findings
The statistically significant findings of disparity in the award of prime contracts and subcontracts
were calculated in compliance with the constitutional parameters set forth in Croson286 and its
progeny.
A. Prime Contract Disparity Findings
MSD issued 2,749 prime contracts from January 1, 2013 to December 31, 2017. The prime
contracts awarded included seven for building construction, 890 for non-building construction,
299 for engineering professional services, and 1,553 for purchasing and other services. The
payments made by MSD during the study period totaled $1,238,982,577 for all 2,749 prime
contracts. Payments included $30,684,903 for building construction, $917,808,132 for non-
building construction, $279,103,076 for engineering professional services, and $11,386,466 for
purchases and other services.
Table 10.1: Total Prime Contracts and Dollars Expended
All Industries, January 1, 2013, to December 31, 2017
Industry Total Number
of Contracts
Total
Dollars Expended
Building Construction 7 $30,684,903
Non-Building Construction 890 $917,808,132
Engineering Professional Services 299 $279,103,076
Purchases and Other Services 1,553 $11,386,466
Total Expenditures 2,749 $1,238,982,577
286 Croson, at 488 U.S. 469 (1989).
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Recommendations
1. Building Construction Prime Contracts
As indicated in Table 10.2, there were too few contracts awarded to determine the statistical
significance for building construction prime contracts valued $25,000 to $8,270,000.
Table 10.2: Disparity Summary: Building Construction Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Building Construction
Contracts Valued from
$25,000 to $8,270,000
African Americans No Disparity
Asian Americans No Disparity
Hispanic Americans No Disparity
Native Americans No Disparity
Caucasian Females Underutilized
Minority-owned Businesses No Disparity
Woman-owned Businesses Underutilized
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2. Non-Building Construction Prime Contracts
As indicated in Table 10.3, disparity was found for African American, Hispanic American,
Caucasian female, minority-owned business, and woman owned business prime contractors on
non-building construction contracts valued under $25,000. Disparity was also found for African
American, Caucasian female, minority-owned business, and woman-owned business prime
contractors on non-building construction contracts valued $25,000 to $500,000
Table 10.3: Disparity Summary: Non-Building Construction Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Non-Building Construction
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans Disparity Disparity
Asian Americans No Disparity No Disparity
Hispanic Americans Disparity No Disparity
Native Americans No Disparity No Disparity
Caucasian Females Disparity Disparity
Minority-owned Businesses Disparity Disparity
Woman-owned Businesses Disparity Disparity
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3. Engineering Professional Services Prime Contracts
As indicated in Table 10.4, disparity was found for Asian American, Hispanic American, Native
American, and Caucasian female prime contractors on engineering professional services contracts
valued under $25,000. Disparity was also found for Asian American, Caucasian female, minority-
owned business, and woman-owned business prime contractors on engineering professional
services contracts valued $25,000 to $500,000.
Table 10.4: Disparity Summary: Engineering Professional Services
Prime Contract Dollars, January 1, 2013, to December 31, 2017
Ethnicity/Gender
Engineering Professional Services
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans No Disparity No Disparity
Asian Americans Disparity Disparity
Hispanic Americans Disparity No Disparity
Native Americans Disparity No Disparity
Caucasian Females Disparity Disparity
Minority-owned Businesses No Disparity Disparity
Woman-owned Businesses No Disparity Disparity
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4. Purchases and Other Services Prime Contracts
As indicated in Table 10.5, disparity was found for African American, Asian American, Hispanic
American, Native American, and minority-owned business prime contractors on purchases and
other services contracts valued under $25,000. Disparity was found for woman-owned business
prime contractors on purchases and other services contracts valued $25,000 to $500,000.
Table 10.5: Disparity Summary: Purchases and Other Services Prime Contract Dollars,
January 1, 2013, to December 31, 2017
Ethnicity/Gender
Purchases and Other Services
Contracts Valued
under $25,000
Contracts Valued from
$25,000 to $500,000
African Americans Disparity No Disparity
Asian Americans Disparity No Disparity
Hispanic Americans Disparity No Disparity
Native Americans Disparity No Disparity
Caucasian Females No Disparity Underutilized
Minority-owned Businesses Disparity No Disparity
Woman-owned Businesses No Disparity Disparity
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B. Subcontractor Disparity Findings
As indicated in Table 10.6, disparity was found for African American, Asian American, Hispanic
American, Caucasian female, Minority-, and Woman-owned building construction subcontractors.
Disparity was also found for Asian American, Hispanic American, Caucasian female, and Woman-
owned non-building construction subcontractors. Additionally, disparity was found for African
American, Native American, and Minority-owned engineering professional services
subcontractors.
Table 10.6: Subcontract Disparity Summary,
January 1, 2013, to December 31, 2017
Ethnicity / Gender Building
Construction
Non-building
Construction
Engineering
Professional Services
African Americans Disparity No Disparity Disparity
Asian Americans Disparity Disparity No Disparity
Hispanic Americans Disparity Disparity No Disparity
Native Americans No Disparity No Disparity Disparity
Caucasian Females Disparity Disparity Underutilized
Minority-owned Businesses Disparity No Disparity Disparity
Woman-owned Businesses Disparity Disparity Underutilized
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III. Race and Gender-Conscious Remedies
This section presents recommendations to remedy the statistically significant findings of disparity
documented in the Study. The remedies are narrowly tailored to the Study findings to meet the
Croson standard. Pursuant to the Croson standard, the Court permits the implementation of race
and gender-conscious remedies after consideration of a race and gender-neutral program. MSD
has implemented for five years a race and gender neutral and a race and gender-conscious MWBE
program, yet statistically significant disparity is still present in the procurement for both prime
contracts and subcontracts. Based on the disparity findings at the prime contract and subcontract
levels, MSD should continue to utilize race and gender-conscious remedial measures as part of its
Supplier Diversity Program. The proposed race and gender-conscious remedies are based on the
disparity findings and only apply to the ethnic and gender groups in the industries in which they
were statistically significantly underutilized.
A. Prime Contract Remedies
MSD’s Charter prohibits the use of bid discounts for procuring construction or purchases and other
services. Therefore, bid discounts are not recommended as a remedial measure. However, MSD
should continue to provide a 10% multiplier to purchases and other services contracts and 10%
multiplier to \ professional services prime contracts for eligible MWBEs.MSD should also
consider applying a 31% MWBE goal on small professional services contracts. The small contract
size should be determined based on the anticipated contracts.
B. Implement Subcontract Remedies
MSD should implement subcontract remedies for ethnic and gender groups that have statistically
significant disparity. Potential subcontract remedies include subcontract.
1. Set Subcontract MWBE Goals
Race and gender-conscious subcontracting goals should be established for building construction,
non-building construction and engineering professional services prime contracts. The
subcontracting goals should apply to ethnic and gender groups with a statistically significant
disparity.
To meet the narrowly tailored standard, the MWBE construction subcontract goal should be based
on the availability levels for each ethnic group determined to be underutilized at a statistically
significant level. The MWBE goals should be applied as follows:
• Building Construction - 21% MBE and 10% WBE Subcontracting goals
• Non-Building Construction - 10% MBE and 10% WBE subcontracting goals
• Engineering Professional Services - 18% MBE and 13% WBE
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2. Revise Certified MWBE Participation Requirements for Truckers
Commercially Useful Function requirements should be modified to clearly distinguish the levels
of participation for all types of transportation services including hauling of product to ensure
proper credit is given. MSD should adopt St. Louis County’s participation requirements for
MWBE truckers, as revised on April 30, 2021. The County’s revised participation requirements
ensure MWBE truckers participation includes all transportation services. Credit for the
participation of an MWBE trucker applies to the total value of the transportation service provided
when the MWBE operates its own trucks.
IV. Race and Gender-Neutral Remedies
The race and gender-neutral recommendations are offered to enhance the procurement process and
remove program barriers that minority, women, and small businesses encountered when
attempting to do business with MSD. As proposed, these recommendations do not require findings
of statistically significant disparity to be implemented. However, they would increase the capacity
of MWBEs and other small businesses to do business with MSD and its prime contractors.
A. Capacity Building Measures
1. Implement a Sheltered Market Program
MSD should implement a Sheltered Market Program designed to maximize the award of informal
contracts to certified MWBEs and SLBEs. The program should be established for purchases and
other services contracts that do not exceed $10,000. MSD’s solicitations under $10,000 do not
require advertising. The awards would be made on a rotating basis. No business in the rotation
should be eligible to receive a second assignment until all other businesses on the list have been
offered at least one assignment.
Eligible MWBEs and SLBEs should be classified in the sheltered market database by NAICS code.
The Supplier Diversity Program Office will determine the criteria for the purchases and other
services contracts that should be evaluated for inclusion in the Sheltered Market Program.
Minimally, consideration will be given to the following factors:
• Estimated value of $10,000 or less
• Scope of work is limited to a single trade of service
If a bid is not secured from a solicited certified MWBE or SLBE, the procurement should be
opened to the general public. The Supplier Diversity Program Office should execute the following
pre-award responsibilities:
• Utilize the MWBE and SLBE Directory to ensure those businesses are solicited for
contracts in the Sheltered Market Program.
• Post a description of the Sheltered Market Program on the Supplier Diversity Prog ram
Office’s webpage and in MSD marketing and promotional materials.
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• Expand routine staff training to ensure MSD department managers are informed about the
Program and its requirements.
• Advertise contracting opportunities in MWBE and SLBE focused and gener al circulation
media and trade publications.
• Email certified MWBEs and SLBEs of upcoming informal contracting opportunities.
• Solicit small businesses to certify with the Supplier Diversity Program Office.
2. Limit Use of Master Agreements
Master Agreements are used by MSD to award construction and professional services contracts.
Using this method, MSD bundles multiple construction and professional services contracts into a
few large solicitations with multi-year renewal options. MSD should reduce the use of large, multi-
year contracts to provide more prime contracting opportunities for MWBEs and small businesses.
MSD should limit the use of master agreements to maximize competition in the procurement of
construction and professional services contracts. Furthermore, the multi-year renewal options
should be eliminated, thereby allowing more businesses to participate in this procurement method.
3. Modify the Electronic Subcontract Tracking System
MSD has a robust subcontract tracking system that efficiently tr acks MWBE subcontractors by
name, award amount, and payment. The system should also track the MWBE’s ethnicity and
gender. Additionally, the tracking system should be modified to track non-MWBE subcontractors
by name and contract amount. Non-MWBE award and payment amounts are tracked, but the
system does not capture the data by individual contractor’s name. MWBE and non-MWBE
subcontractor payment should be tracked from contract award through contract close-out,
including all change orders and amendments.
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