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60 APPENDIX A Importance of Comprehensive Subcontract Data Collection Introduction DBE subcontract awards is imperative when building a proj- ect database for use in a disparity or availability study. Twenty years after Croson, many public agencies with race- An example may illustrate the point. Consider the con- conscious subcontracting programs (including state DOTs) struction contract shown in Table A1, below. The overall still do not systematically collect and maintain adequate sub- value of the contract is $12 million. The total value of the DBE contracting data. Although state DOTs maintain records on subcontracts is $1 million and the total DBE share is therefore their DBE subcontracting, many do not maintain compara- 8.3%. For a disparity study, however, the consultant would ble records regarding non-DBE subcontracting. Although also want to know the dollar share accounted for by each non-DBE subcontract data are not necessary to produce the NAICS code and the DBE share for each code. The former is standard types of DBE utilization reports requested by needed in order to calculate properly weighted availability U.S.DOT or the DOT's executive leadership, which include, estimates. The latter is needed in order to calculate utilization for example, only that share of construction dollars awarded and disparity statistics. These NAICS shares are shown in the during a given time to DBEs, such data are critical to produc- last six rows of Table A1. This exercise should be repeated for ing a high-quality and legally defensible availability or dispar- each contract in the project database. ity study. Some studies have ignored the problem of missing subcon- tract data. For example, one study states bluntly: Non-DBE Subcontract Data Is Just as Important as DBE Subcontract Data The utilization analysis of [M/WBEs] . . . does not include their utilization as sub-contractors or sub-consultants. . . . [We were] In contrast to such limited reporting, a high-quality dispar- unable to secure sub-contracting/sub-consulting dollars from ity or availability study, among other things, should document the actual contract files during the data collection effort, simply the share of all construction dollars awarded by detailed indus- because the contract files do not contain the data relative to sub- try during a given period. In addition, a disparity study should contracting or subconsulting activities. . . . This . . . is striking in that . . . sub-contracting opportunities are often where much of detail the share of dollars in each detailed industry awarded to the utilization of M/WBEs is found. DBEs. Several courts have warned defendants about the use of overly aggregated statistical comparisons in disparity studies Another study states: because such aggregation can provide misleading results.191 This phenomenon is known as Simpson's Paradox. Since The data made available to [us] . . . contain primarily reports of many industries are only represented in state DOT projects subcontracts involving DBE participation, as the overall percent- through subcontracting, knowledge of non-DBE as well as age of subcontracting (less than 8 percent) is significantly lower 191 See Engineering Contractors Association v. Metropolitan Dade County, 943 F. Supp. 1546, 1560 (S.D. Fla. 1996) ("The MRD study presents . . . data aggregated for all cap- ital construction contracts (i.e., SIC 15, 16 and 17 together) and disaggregated by SIC category. . . . The Court will focus primarily on statistical analyses of the disaggre- gated data because these data are more likely to reflect the realities of competition in the construction industry. Firms that build hospitals (SIC 15) do not compete for County contracts with firms that lay asphalt (SIC 16) or firms that install plumbing (SIC 17), therefore comparisons between these disparate entities would not produce a reliable portrait of County contracting trends."). Simpson's Paradox has also been used to criticize combining highway districts together into statewide statistics. See Phillips & Jordan, Inc. v. Watts, 13 F. Supp. 2d 1308, 1315 (N. D. Fla. 1998); Thompson Building and Wrecking Co. v. Augusta, 2007 U.S. Dist. LEXIS 27127, at * 8 (S.D. Geo. March 14, 2007) (criticizing combining MBE statistics with WBE statistics).

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61 Table A1. Subcontract data collection example. Bid Package Contractor Type NAICS DBE Dollar Amount Prime $9,500,000 23621 Subcontractor $750,000 23621 Yes Subcontractor $300,000 23621 Subcontractor $50,000 23731 Subcontractor $50,000 23731 Subcontractor $200,000 23731 Subcontractor $100,000 23731 Yes Subcontractor $30,000 23811 Subcontractor $700,000 23821 Subcontractor $140,000 23821 Yes Subcontractor $10,000 23899 Yes Subcontractor $60,000 23899 Subcontractor $160,000 33599 TOTAL $12,000,000 NAICS Dollar Share DBE Share 23621 87.6% 7.1% 23731 3.3% 25.0% 23811 0.2% 0.0% 23821 7.0% 16.7% 23899 0.6% 14.3% 33599 1.3% 0.0% than subcontracting for most state Departments of Transporta- In the first study, no subcontract data were available from tion (between 40 and 45 percent). the client. In the second and third studies, the only data avail- able from the client were for prime contracts that happened And, another states: to have DBE subcontractors. While it is apparent that all three studies recognized the importance of capturing complete [D]ata were missing [pertaining] to subcontract awards to Non- DBEs. This study disaggregated all contracting activity by prime subcontracting activity data, the problem remained unad- and subcontracting categories. As such, it would have been helpful dressed in the final reports. Any statistical conclusions result- to have information on attainments by Non-DBE subcontractors. ing from such methods may be rejected by the courts since