How we work · Our approach
We find what causes a disparity, and what to do about it.
Anyone can divide availability by utilization and report a number. Fairfax County needs to know why the number looks the way it does, where in its own process the gap forms, and what it can do about it.
The disparity index: a group's share of contract dollars (utilization) divided by its share of firms in the market (availability). For Fairfax the preliminary public-data values are minority availability 37.2% against utilization 9.0% for an index of 0.24, and women availability 25.5% against utilization 4.9% for an index of 0.19, both far below the 0.80 substantial-underutilization threshold. The inputs are real and public: Census ABS 2022 for the Washington-Arlington-Alexandria market and the Fairfax FY23 SWaM report (all-SWaM utilization 29.0%).
It shows the size and direction of the gap between presence and participation, and it shows where to look first. A value well under 0.80 is a legitimate signal that minority-owned and women-owned firms receive a smaller share of dollars than their share of the supplier base would predict, and it lets the County compare its position against regional peers (WMATA M/WBE near 0.48; the Commonwealth of Virginia near 0.41, a value HSG recomputes from BBC's reported figures). It is a credible, transparent first read of the landscape. Those peer indices come from full primary-data studies with survey-based availability, so they are a directional reference rather than a like-for-like comparison with Fairfax's preliminary proxy.
Computing the ratio takes minutes. A study that stops at the ratio, with a registration-based availability count and a single headline index, is the standard product the large, established disparity-study firms typically deliver. It is enough to assert that a gap exists. It is also the read a hostile expert can take apart in deposition, because it is a correlation with no theory of cause, no controls for capability, and no location in the procurement process. We treat the ratio as the first step and build the causal and locational analysis behind it, so the County receives recommendations it can act on and defend.
Where we go
The ratio is the start, not the answer
Start with the simple measure. Compare the share of firms in the market owned by minorities or women against the share of contract dollars those firms receive. In the Washington-Arlington-Alexandria market, minority-owned availability sits near 37.2% and women-owned near 25.5%, while County and FCPS utilization runs at 9.0% for minority firms and 4.9% for women-owned firms. Divide those and the preliminary disparity indices are 0.24 and 0.19, both well under the 0.80 substantial-underutilization threshold. These are preliminary public-data proxies, computed from an equal-weight firm count rather than a survey of firms ready and able to do the work. We can produce them in an afternoon, and we have. They are on the portal with every figure traceable to its source.
A single ratio tells you a gap exists. It does not tell you what produced the gap, because one divided figure carries no information about cause. The deeper work traces the procurement funnel stage by stage, from vendor registration to awareness of opportunities to bidding to the responsiveness and responsibility check to award to prompt payment to subcontract participation. We add a private-sector regression, a qualified-willing-and-able availability survey, the 16-barrier framework, and structured verified interviews. Where firms drop off in the funnel points to the kind of problem at work, and a supply problem, a selection problem, a payment problem, and a network problem each call for a different fix.
Pinpointing the cause is what lets a recommendation be specific. Once the analysis shows which stage of the funnel the drop-off happens at, and which explanation holds up, the fix follows from it. A drop-off at registration points to outreach and a simpler onboarding path. A drop-off at the bid stage points to how opportunities are advertised and how qualifications are written. A drop-off after award, in slow payment, points to the County's payment practices. Each fix attaches to a mechanism the County can change. We build the recommendations race-neutral first, in the order the law and 49 C.F.R. 26.51 expect. Most of what closes these gaps is open to every firm and does not turn on the race or gender of its owner: unbundling large contracts, fixing payment timelines, broadening bid lists, and helping firms build the relationships that informal networks otherwise ration. The goal is more firms from every segment of the community competing for and winning County work.
The discipline that makes a finding credible
What a gap can and cannot tell you
A low disparity index does not prove the County did anything wrong, and we do not start from that assumption. A raw difference between availability and utilization is a correlation, and a correlation can have several sources, only some of which point back at the County. The cause may be something the County controls, such as how bid lists are built or how prequalification and bonding thresholds are set. It may be marketplace-wide, reaching across public and private buyers and rooted in access to capital or in the informal networks that decide who gets the first referral. It may be a legitimate, non-discriminatory difference in the firms themselves, in size, capacity, or the lines of work they are positioned to bid. Our job is to test those explanations against the evidence. We control for capability and qualifications, we examine whether the County's own criteria are appropriate and least restrictive, and we build the record to the evidentiary standard the Fourth Circuit set in H.B. Rowe and the Supreme Court set in Croson. A finding that survives that scrutiny is one the County can stand behind. A benign explanation is just as useful to surface, because it shows where effort is not needed. We report whichever answer the evidence supports.
The ladder of analysis
From a gap to its cause
Each step answers a specific causal question and addresses a rival explanation, so the study can say not only that a gap exists but why, and where the County can act. The tag on each step marks whether the cause it isolates is something the County controls, a marketplace-wide condition, or a legitimate difference in capability.
PhD-led stratified custom-census survey of firms in a spend-derived market area, NAICS-weighted to Fairfax and FCPS expenditure, telephone plus email, to a 95% confidence interval and plus-or-minus 5% per industry subsector. Anchor willingness to active public-work registration and observed bid behavior. Because a firm must register as a vendor to bid, the County's registered-vendor rolls define a bounded, followable universe of firms that have signaled willingness to do public work, the tractable government-contracting market the survey then measures readiness within, knowable in a way the open private economy is not. Following the Houston study and NCHRP 644, and consistent with Croson's qualified-willing-and-able standard, do not capacity-discount the denominator, since current capacity is itself partly a product of past conditions; the only ability filter is genuine market-area presence and line-of-business match. Replace the current equal-weight ABS firm count with this weighted denominator and recompute every index against it.
Rules out the leading attack that the gap is an artifact of an inflated headcount denominator (counting firms that never bid or are out of line-of-business). If the gap persists against a willing-and-able, spend-weighted denominator, an availability-measurement explanation is ruled out.
Build a bid-level dataset of who requested documents, who submitted, and who won, by solicitation. Compute a bid-to-award ratio by ownership and compare it to the availability-to-award ratio. A gap that closes at the bid stage points to a supply or awareness problem upstream; a gap that opens at the bid stage points to a selection problem at evaluation. Pair with offer and lost-contract records where they exist so willingness rests on bid behavior rather than registration alone.
Separates the supply explanation (firms are not bidding) from the selection explanation (firms bid and are not selected). This decides which half of the funnel the rest of the analysis must concentrate on and rules one of the two out as the dominant channel.
Construct a stage-by-stage conversion funnel and compute the retention rate by ownership at each transition: registered share, opportunity-aware share, bidder share, responsive-and-responsible share, awardee share, paid-on-time share, and subcontract-participation share. Locate the stage with the largest ownership-specific drop. Each stage implicates a different cause and a different fix: a registration or awareness drop is a supply and outreach problem, a bid-to-responsive drop is a criteria problem (route to S5), a responsive-to-award drop is a selection or network problem (route to S6), and a payment drop is a cash-flow problem.
Locates causality in process space. It rules out a single global story by forcing the gap to a stage. A supply-stage drop rules out a selection bias claim; a payment-stage drop rules out an availability claim; a sub-stage drop points to prime behavior rather than County selection.
Estimate a contract-level (and firm-level) regression of award and dollars received on ownership while controlling for firm age, firm size (employees and receipts), prior relevant experience, owner education, capital and bonding capacity, contract scope and dollar size, procurement method, and industry cluster. The coefficient on ownership, net of those controls, is the residual gap. Report it with confidence intervals. A residual at or near zero means capability differences explain the raw gap; a significant residual means a portion is not explained by capability.
Rules in or out the legitimate-capability explanation. A raw 0.24 index can reflect that minority-owned firms are younger, smaller, or less capitalized on average. If the gap vanishes under controls, the cause is capability and the remedy is capability-building, not preference. A surviving residual is the evidentiary core of a marketplace-discrimination finding.
Inventory and code every County and FCPS solicitation in the study period for each screen. For each criterion, estimate the share of the available minority-owned and women-owned pool versus the non-minority pool that could satisfy it, using the census firm-age, capital, bonding-capacity, and experience data, and apply a disparate-impact screen by ownership using the EEOC four-fifths convention as an analytic analogy (distinct from the unrelated 0.80 disparity-index threshold, which shares the number by coincidence), flagged for significance. Run a fit-to-scope test (is a five-year or three-prior-contract floor necessary for routine work; is bonding calibrated to real payment risk; is a contract bundled past small-firm reach). Conclude with a least-restrictive-means review producing a keep, right-size, or replace recommendation per criterion, benchmarked to 49 C.F.R. 26.51 and the Virginia Public Procurement Act least-restrictive-qualifications standard. Apply the same audit to RFP 2000004217 itself as a proof of concept. Augment the manual coding with an AI-assisted read of the full procurement-rules corpus that surfaces internal rule conflicts and candidate disparate-impact provisions for a named investigator and counsel to verify; the AI accelerates and broadens the review but makes no finding, and a responsible-AI advisor governs the bias-testing and documentation of that step.
Rules in or out the explanation that the County's neutral-looking requirements are themselves the barrier. A criterion that few minority-owned firms can meet, and that exceeds what the work requires, is a County-controllable cause distinct from any bidder behavior, and it grounds race-neutral remedies before any race-conscious measure is considered.
Operationalize Loury's contact-versus-contract distinction. Measure repeat-player concentration (share of dollars to firms with prior awards and Herfindahl-type concentration by ownership), the share of dollars flowing through sole-source, informal small-purchase, and referral or relationship channels versus open competition, and prime-sub pairing patterns (do the same primes pair with the same subs, and are minority-owned and women-owned firms locked out of those pairings or bound by exclusivity). Pair with the structured anecdotal protocol (S9) on old-boy-network and exclusivity themes. Compare ownership-specific gaps in informal channels against open-competition channels.
Rules in the social-capital channel as a cause and distinguishes it from formal-rule causes (S5) and from capability (S3). It supplies the theory of discrimination that a bare ratio lacks: if gaps concentrate in informal, relationship-driven channels and shrink in open competition, the durable barrier is network access, which both formal-criteria reform and capability-building miss.
Mirror the Houston Chapter 6 design. Estimate private-sector earnings and formation disparities for the Washington metro: linear regressions on individual wages and on business-owner earnings, and logistic regressions on the probability of self-employment and business-formation rates, using PUMS microdata, controlling for race and gender, capital availability (homeownership, home value, mortgage status, unearned income), education, age and age-squared, marital status, English proficiency, disability, and market-area residence. Layer Census ABS and SBO private-sector revenue disparities by NAICS. A significant gap in the private-sector model establishes passive, marketplace-wide discrimination that the County did not create.
Distinguishes County-specific causation from marketplace-wide disadvantage. If the gap is large in the private economy too, part of the cause is passive societal discrimination outside the County's control, which under Croson and H.B. Rowe can support the compelling interest while pointing remedies toward marketplace-facing tools. If the private-sector gap is small but the County gap is large, the cause is more local and County-controllable.
Add a dedicated access-to-credit sub-analysis. Estimate differences in loan denial rates, financing terms, startup capital, and reliance on personal and home equity by ownership, using HMDA, the Survey of Business Owners and ABS company-characteristics modules, Small Business Credit Survey data, and the homeownership and home-value capital proxies from the PUMS model (S7). Anchor to the Fairlie and Robb capital literature. Link capital constraints to firm size, bonding capacity, and the formation gap so the capital channel is explicit rather than folded into a generic capability control.
Rules in capital access as a specific, separable cause rather than an undifferentiated capability gap. It clarifies whether the right remedy is bonding assistance and capital access (a marketplace-facing, often race-neutral tool) versus selection or network reform, and it strengthens the marketplace-discrimination finding by tracing one of its mechanisms.
Run separately instrumented, structured interviews using distinct guides for businesses and for professional and trade organizations, recruited broadly (email, mail, personal contact, public hearings) to reduce self-selection. Code each account to the procurement-funnel stage (S4) and the barrier framework. Verify each owner account against the procurement record where possible (the bid was submitted, the payment was late, the criterion applied), and retain all transcripts. Report corroboration by theme: informal networks, bonding and insurance, slow payment, prime-sub exclusivity, and repeated demands to prove qualifications.
H.B. Rowe requires statistical disparity be corroborated by significant anecdotal evidence, and the standard attack is that anecdotes are unverified or out of context. Verified, retained, stage-coded accounts rule out the noise explanation and tell whether the experiential signature matches the statistical location, while broad recruitment rules out a self-selected-complaint bias.
Apply a dual test to every group-by-cluster-by-category cell: disparity index at or below 0.80 (substantial) and a t-test for statistical significance, with confidence intervals reported. Build the findings as a group-by-category matrix marking each cell disparity or no disparity and flagged for significance, rather than a single headline index. Report honest counter-results, including any group overutilized in a category. Pre-register the methodology and apply the test uniformly so the study can return a null.
Rules out the noise explanation (a gap from small numbers or chance) and the over-inclusion problem (treating all minorities as one undifferentiated group). Croson condemned the laundry-list approach and H.B. Rowe upheld remedies only for groups the evidence supported. Significance plus group-by-category specificity is the binding constraint that decides which findings from every prior step are real and remediable.
What it takes
The data this analysis requires
The deeper analysis is only as good as its inputs. This is the full data picture, what we collect ourselves and what the County and FCPS would provide, so the work is concrete rather than aspirational.
| Dataset | Holder | Why it is needed | Source |
|---|---|---|---|
County prime contract and award records (master contract register) County provides | Fairfax County Department of Procurement and Material Management (DPMM) and the County financial/ERP system | This is the actual utilization numerator. The current portal utilization (minority 9.0%, women 4.9%, all SWaM 29.0%) comes from the published FY23 SWaM summary, which excludes P-card and non-PO spend including capital construction. The line-item award register lets HSG compute utilization at the group-by-category-by-contract-size level that the dual test and over-inclusion doctrine require, rather than a single headline number. It is the County's own marketplace, which Croson requires. | DPMM contract management / ERP financial system (purchase orders, contracts, blanket/term agreements) for the study period, ideally five fiscal years with line-item NIGP/NAICS coding, dollar value, award date, vendor name and ID, solicitation method, and department |
FCPS prime contract and award records County provides | Fairfax County Public Schools, Office of Procurement Services | The FY23 SWaM report combines County and FCPS PO spend, so the study must be able to attribute and analyze each entity separately and together. FCPS is a large, distinct buyer (construction, instructional goods, services) whose category mix differs from the general-government County, and remedies may differ by entity. Without the FCPS register the utilization base is incomplete and the matrix cannot be entity-specific. | FCPS procurement and financial system, parallel to the County register: contracts, POs, award dates, dollar values, NAICS/category, vendor IDs, for the same study period |
Subcontract participation and payment records (compliance system) County provides | Fairfax County DPMM contract-compliance function (and FCPS equivalent); compliance vendor system if one is in use | Disparity often concentrates at the subcontract level where minority and women firms are funneled, so a prime-only analysis understates the gap and misplaces causality. Houston derived its RGMA from the full universe of expenditure data, prime and subcontract, and several of its remedies (forbid prime-sub exclusivity, IDIQ compliance, mandatory subcontractor-data entry) target this stage. Fairfax may have thin subcontract data, which itself is a documented finding (Houston Remedy A is about fixing exactly that gap). | B2GNow-type contract-compliance / subcontractor-monitoring system records, plus subcontractor utilization plans and post-award subcontractor payment confirmations, for the study period |
Vendor payment and prompt-payment records (financial system) County provides | Fairfax County Department of Finance / ERP; FCPS finance | Slow or no payment is one of the most consistently reported barriers in disparity studies (Houston Chapter 7 and the H.B. Rowe record) and a distinct funnel drop-off: a firm can win work and still be squeezed out by cash-flow strain that hits undercapitalized firms hardest. Payment-timing data lets HSG test whether payment lag differs by firm ownership and connects the funnel to the access-to-credit/capital-constraint finding rather than leaving payment as an anecdote. | Accounts-payable / financial system records: invoice date, payment date, payment amount, vendor ID, contract reference, for prime and (where captured) subcontractor payments |
Full solicitation text corpus (for criterion coding) County provides | Fairfax County DPMM (and FCPS) solicitation archive / eVA and County procurement portal postings | Causality is what HSG is selling, and a major County-controllable cause lives in the solicitation terms themselves. Coding solicitations for years-in-business floors, prior-similar-contract demands, reference counts, bonding thresholds, and contract bundling lets HSG quantify how often facially neutral criteria mechanically exclude later-entering diverse firms, and test those criteria against the Virginia Public Procurement Act standard of maximum competition and least-restrictive qualifications. This is the criterion-appropriateness audit and the structural backbone of the funnel diagnosis. | Complete bid/RFP/IFB/RFQ documents for a representative sample of solicitations in the study period, including evaluation criteria, minimum qualifications, experience and reference requirements, bonding/insurance terms, contract size and bundling, and set-aside/SWaM language |
Bid, offer, and unsuccessful-bidder logs (bid tabulations) County provides | Fairfax County DPMM (and FCPS) solicitation files | This is the dataset that separates a supply problem from a selection problem, the core of pinpointing causality. If diverse firms register and are available but rarely bid, the cause is upstream (awareness, bundling, bonding). If they bid at expected rates but lose at award or are found non-responsive/non-responsible disproportionately, the cause is in evaluation and selection. Win-probability models on bid-level data estimate the marginal effect of meeting versus narrowly missing experience and reference requirements while controlling for price and technical score, isolating the screen's independent exclusionary effect (Houston/NCHRP 644 approach). | Bid tabulation sheets and offer logs for awarded solicitations: every firm that submitted, price/score, responsiveness and responsibility determination, and reason for non-award; plus plan-holder/interested-vendor lists where kept |
Vendor registration roll and certification rosters (SWaM/DSBSD) County provides | Fairfax County DPMM (vendor registration); Virginia Department of Small Business and Supplier Diversity (DSBSD) for SWaM/DBE certification | Registration is the first funnel stage: if diverse firms in the market are not registered, the cause is awareness and onboarding, not selection. The roll also seeds the custom availability survey sampling frame and lets HSG measure certification wait times and the need-an-ID-to-get-an-ID friction Jelani has emphasized. DSBSD certification rosters anchor the willing-and-able definition with firms that have already signaled intent to do public work, the registration anchor Houston used to defeat the availability-inflation attack. | County/FCPS vendor registration database; Virginia DSBSD SWaM/micro/small/DBE certification directory; any County-level certification or supplier-diversity registration, with NAICS, ownership demographics, certification status, and registration date |
Custom availability survey (HSG-fielded) We collect or derive | House Strategies Group LLC (PhD-led survey team; fielded by HSG, not held by the County) | This is the single biggest upgrade over the current portal, which uses an equal-weight public ABS firm count flagged as a limitation. A sampled, registration-anchored custom census measures willingness and market-area presence and deliberately declines to capacity-discount, on the ground, consistent with Croson's qualified-willing-and-able standard and NCHRP 644, that current capacity can itself be a product of past conditions. It directly answers La Noue's standard attack that studies inflate availability with firms that never bid or lack capacity. HSG fields it; the County does not hold it but should support outreach and provide the registration frame. | Stratified random survey of firms in the relevant geographic market area, NAICS-weighted to Fairfax/FCPS spend, telephone plus email, to 95% confidence and roughly +/-5% margin of error per industry subsector; measures willing-and-able status without capacity-discounting (mirrors Houston Appendix D custom census and Appendix E vendor questionnaire) |
U.S. Census ABS / SBO firm-level business data We collect or derive | U.S. Census Bureau (public bulk files; HSG retrieves and derives) | ABS/SBO establishes the private-sector, economy-wide picture the County did not generate, which is what grounds passive marketplace discrimination independent of County conduct. It gives the availability cross-check and the firm-formation and receipts disparities (HSG already computed minority availability 37.2%, women 25.5% for the WAA metro and firm-size gaps of roughly 1,730k receipts / 9.7 employees minority versus 4,079k / 16.0 non-minority). It is public, so it cannot be attacked as consultant-manufactured, and it answers the just-hired-someone-to-find-disparity critique. | Annual Business Survey Company Summary 2022 (AB2200CSA01) and 2017 (ABSCS2017); Survey of Business Owners (2012) for trend; nonemployer statistics; firm counts and receipts by owner sex, race, ethnicity, veteran status, NAICS, and geography |
ACS PUMS microdata (but-for regressions) We collect or derive | U.S. Census Bureau (public microdata; HSG retrieves and models) | PUMS is the legal armor. Linear regressions on wages and on business-owner earnings, and logistic regressions on probability of self-employment and business formation, show that holding human capital and capital-access controls constant, minority and women earners and owners still trail (Houston found wage earners about 39% behind, owner earnings about 18% behind, all significant at 95%). A gap that survives those controls points to the network and capital channels Loury describes, which is exactly the causality HSG promises. The controls also operationalize NCHRP 644's business-formation, ownership, and earnings models. | American Community Survey Public Use Microdata Sample, multi-year (e.g., 2017-2021), individual person and household records for the relevant market area: wages, business-owner earnings, self-employment status, plus controls (race, sex, age and age-squared, education, English proficiency, disability, marital status, homeownership and home value, mortgage, unearned/residual income) |
Access-to-credit and capital-access data We collect or derive | Public sources (CFPB/FFIEC HMDA, Federal Reserve, SBA, academic literature); HSG compiles and analyzes | Capital constraint is a leading non-County, non-discriminatory-on-its-face explanation that the study must test rather than assume, and a major driver of why diverse firms enter later, smaller, and with thinner balance sheets (Fairlie & Robb: nearly half of Black families hold under 6,000 dollars in total wealth). Testing the capital channel both strengthens the marketplace finding and protects fairness: it locates part of the gap in economy-wide capital access rather than County fault, which is central to Jelani's no-assumed-fault posture. | HMDA mortgage and home-equity data, Federal Reserve Small Business Credit Survey, Fairlie & Robb / Census CBO capital evidence, SBA lending data, and the capital-availability proxies embedded in the PUMS controls (homeownership, home value, unearned income) |
Anecdotal and interview record (qualitative corpus) We collect or derive | House Strategies Group LLC (designed by the academic bench, executed by the field team; HSG holds the corpus) | H.B. Rowe requires that statistical disparity be corroborated by significant anecdotal evidence, and the court devalued unverified accounts, so the protocol must verify owner accounts (solicitation numbers, dates) and retain transcripts. This is the experiential signature of the funnel: owners describe whether they were stopped at registration, awareness, bidding, selection, payment, or the network, which tells the study where causality lives and which remedies fit. It is also the human face of Loury's discrimination-in-contact thesis. | Structured in-depth interviews (separate guides for businesses and for professional/trade organizations, per Houston Appendices G and H), vendor questionnaire open-ended responses, public hearings and sworn testimony, and business-engagement sessions, recruited via email, postcard, personal contact, and association outreach; with a verification step and full transcript retention |
Relevant geographic and product market definitions (NAICS spend distribution) We collect or derive | Derived by HSG from County/FCPS data (the underlying records are County-held; the derivation is HSG's) | Croson requires the market be the jurisdiction's own. Deriving the RGMA from Fairfax/FCPS spend (prime and sub), the way Houston found nine counties holding 77.1 percent of dollars, defeats the gerrymandered-market attack and makes the availability denominator match what the County actually purchases. The current portal uses the Washington-Arlington-Alexandria metro as a public-data proxy; the full study tightens this from the County's own spend distribution. | Derived from the County/FCPS prime and subcontract spend records: the NAICS/product mix the County actually buys (Houston Appendix A) and the geographic distribution of where those dollars go (Houston Appendix B); used to set the RGMA and the product market rather than adopting either off the shelf |
Items tagged “County provides” are the contract, payment, solicitation, and bid records only the County and FCPS hold. Everything else we collect or derive from public sources and our own survey.
The payoff
From cause to action
Pinpointing the cause is what makes a recommendation targeted instead of blunt. Each cause the analysis can isolate maps to a specific fix and a specific County lever. We lead with race-neutral, opportunity-focused measures and reserve anything race-conscious for the narrow, significant, group-specific gaps that neutral fixes cannot close.
Drop-off concentrated at the vendor-registration and certification stage (ready firms never enter the County's eVA or supplier pool, so the supply of bid-eligible diverse firms is thin before any solicitation runs)
Run targeted registration drives with the regional minority and women business associations, pre-fill and simplify the eVA/SWaM onboarding, and shorten certification turnaround so a willing firm can register and become bid-eligible in days rather than weeks
Certification speed and vendor-registration outreach
Race-neutralDrop-off at the awareness stage (registered diverse firms are in the pool but do not learn of relevant solicitations in time to respond, and bidder lists skew to incumbents)
Publish a rolling 12-to-18-month procurement forecast, push targeted notices to certified firms by NAICS, and hold pre-bid sessions timed early enough to prepare a bid
Outreach and advance forecasting of upcoming opportunities
Race-neutralExperience floors and prior-similar-project minimums in solicitations exceed what the scope actually requires, screening out capable firms at responsibility review before price is read
Audit and right-size past-performance language to the work, accept comparable, aggregated, or subcontractor experience and key-personnel experience in place of firm-level history, and document the justification for any threshold retained
Solicitation drafting and least-restrictive qualification rules under the Virginia Public Procurement Act
Race-neutralDrop-off concentrated at the bidding stage for construction, where bonding capacity caps who can bid as a prime rather than firm capability
Stand up a County bonding-assistance track (fee buy-downs that remove surety cost from bid evaluation, threshold reductions on smaller jobs, and a referral partnership with the SBA Surety Bond Guarantee Program), available to all small firms that cannot bond the full contract
Bonding assistance and solicitation bond-threshold scaling
Race-neutralLarge bundled solicitations consolidate scopes that could be procured separately, confining smaller firms to subcontract roles and foreclosing the prime path
Unbundle where the consolidation is not operationally justified, break large buys into right-sized lots, and require a written bundling justification before aggregating requirements. Documented practice supports this: breaking large contracts into smaller, right-sized lots has been shown to raise small and minority- and women-owned participation with no quotas or set-asides
Unbundling and contract-structuring policy
Race-neutralAwards concentrated among repeat primes reached through informal referral and relationship-based selection (Loury's discrimination in contact, the social-capital channel rather than a formal rule)
Move informal opportunities onto the open record by advertising small-purchase and quote-based buys, rotating quote solicitations across the certified pool, and instituting a structured matchmaking program that introduces unaffiliated firms to primes and buyers
Anti-exclusivity quote rotation, open advertising of informal buys, and matchmaking
Race-neutralSlow or non-prompt payment strains cash flow so that diverse firms decline larger awards or cannot carry the gap between performance and payment
Enforce and tighten prompt-payment timelines, add progress-payment acceleration and mobilization advances on larger contracts, and require primes to flow prompt payment down to subcontractors with monitored compliance
Prompt-payment policy and progress-payment terms
Race-neutralSubcontract participation lags because good-faith-effort requirements are unmonitored, allowing bid shopping and after-award substitution of listed diverse subs
Require subcontractor listing at bid, verify good-faith effort, monitor actual sub payments against the plan, and bar post-award substitution without County approval
Subcontracting good-faith-effort enforcement and payment monitoring
Race-neutralRestrictive or proprietary specifications (brand-name calls, narrow product specs, or credential requirements) limit the field for reasons unrelated to performance
Convert proprietary specs to performance-based or or-equal language, scrutinize each restrictive criterion for necessity, and require justification for any single-source specification
Solicitation drafting and procurement-criteria appropriateness audit
Race-neutralThe binding constraint is upstream and marketplace-wide access to capital (firms are undercapitalized at formation and cannot finance working capital), a condition that reaches well beyond County contracting
Partner with regional CDFIs and community banks on working-capital and mobilization loan funds for small contractors, and pair the financing referral with the prompt-payment and progress-payment fixes that reduce the capital a contract demands; treat the capital gap as a shared-marketplace condition the County mitigates rather than one it caused
Capital-access partnerships plus prompt-payment and progress-payment terms
Race-neutralFirms cluster at the bottom contract-size band and never graduate to larger work because they cannot accumulate the past performance and bonding history larger awards require (a self-perpetuating capacity ceiling, not current incapacity)
Run a mentor-protege and graduated capacity-building track that pairs emerging firms with established primes, builds verifiable past performance on staged scopes, and steps firms up in contract size as they demonstrate readiness
Mentor-protege and graduation pathway in the race-neutral SBE track
Race-neutralA measured gap traces to a legitimate non-discriminatory difference (for example, diverse firms in a category are concentrated in NAICS the County rarely buys, or differ systematically in firm size matched to the work), and the gap does not survive controls for those factors
Make no remedy on this finding, document the non-discriminatory explanation, and redirect effort to categories where a controlled gap remains; revisit if the marketplace composition shifts
None required; route engagement effort to general supplier-diversity outreach where the data warrants
Race-neutralFor a given group and category the preliminary index falls below 0.80 but the gap does not survive the dual test (it is not statistically significant once availability is restricted to qualified, willing, and able firms and controls are applied)
Record no disparity finding for that group-and-category cell, do not set a goal there, and route the firms into the general race-neutral SBE track rather than a group-specific measure
Race-neutral SBE track; no goal-setting for that cell
Race-neutralAfter race-neutral measures are determined insufficient to close it, a statistically significant, group-and-category-specific disparity persists and is corroborated by verified anecdotal evidence of differential treatment that neutral measures cannot close
Set a narrowly tailored, group-and-category-specific participation goal scaled to the proven shortfall, sunset it on a fixed review cycle, and retire it once parity holds; apply it only to the groups and categories the evidence supports
Group-specific goal-setting, time-limited and evidence-bounded
Race-conscious, if warrantedHow we keep it fair and defensible
The commitments that keep the analysis honest
A nuanced study introduces ways to overreach. These are the guardrails we build in from the start, several of them required by the precedent that governs Virginia, so the work is fair to every firm and able to withstand the most skeptical review.
See it in the rest of the portal
The disparity index is the surface read. The barriers module is the catalog of causes this approach tests. The methodology page draws the line between what public data can show and what the full study adds.
Source: Approach framework generated 2026-06-16.