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Equal Employment Opportunity Commission v. DHL Express (USA), Inc.

United States District Court, N.D. Illinois, Eastern Division

September 30, 2016

EQUAL EMPLOYMENT OPPORTUNITY COMMISSION, Plaintiff,
v.
DHL EXPRESS (USA), INC., Defendant. and REGINALD BAILEY, KENNETH BRISCO, OLIVER DEAN, MELVIN EDWARDS, JOHN ELLIS, RONNIE FORD, BENITA GREEN-RILEY, MICHAEL JOHNSON, ANTHONY JORDAN, MIRANDA LESTER, SANDRA McNEELY, EDGAR MEDLEY, TIMOTHY PRICE, ALONZO STUDSTILL, PAUL THOMAS, RANDY THOMPSON, SHREE WASHINGTON, GEORGE WHITE, and SANDRA WILLIAMS, Intervening-Plaintiffs,

          MEMORANDUM OPINION AND ORDER

          John Z. Lee United States District Judge.

         The United States Equal Employment Opportunity Commission (EEOC) has sued international shipping company, DHL Express USA, Inc., on behalf of ninety-four African American drivers, for discriminating against them based on race in violation of Title VII of the Civil Rights Act of 1964, as amended, 42 U.S.C. § 2000e et seq. and Title I of the Civil Rights Act of 1991, 42 U.S.C. § 1981a. In short, the EEOC asserts that DHL used race to assign less desirable delivery routes to black drivers. DHL denies that this is so.

         During the course of this litigation, both sides have presented experts to analyze the route assignment data maintained by DHL, and now both sides seek to bar the opponent's expert on numerous grounds. DHL moves to bar the EEOC's expert, Dr. Thomas DiPrete. In turn, the EEOC moves to bar DHL's experts, Dr. James Langenfeld and D. Jan Duffy. For the reasons provided herein, the Court denies DHL's motion to bar DiPrete and denies the EEOC's motions to bar Langenfeld and Duffy.

         Legal Standard

         District courts have broad discretion to rule on evidentiary issues prior to trial. See United States v. Chambers, 642 F.3d 588, 594 (7th Cir. 2011). The admissibility of expert testimony is governed by Federal Rule of Evidence 702 and the Supreme Court's seminal case, Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993). See United States v. Parra, 402 F.3d 752, 758 (7th Cir. 2005) (“At this point, Rule 702 has superseded Daubert, but the standard of review that was established for Daubert challenges is still appropriate.”).

         By its terms, Rule 702 allows the admission of testimony by an expert, someone with the requisite “knowledge, skill, experience, training, or education[, ]” to help the trier of fact “understand the evidence or to determine a fact in issue.” Fed.R.Evid. 702. Experts are permitted to testify when their testimony is: (1) “based upon sufficient facts or data”; (2) “the testimony is the product of reliable principles and methods”; and (3) “the expert has reliably applied the principles and methods to the facts of the case.” Id.

         Daubert requires the district court to act as the evidentiary gatekeeper, ensuring that Rule 702's requirements of reliability and relevance are satisfied before allowing the finder of fact to hear the testimony of a proffered expert. See Daubert, 509 U.S. at 589; see also Kumho Tire Co. v. Carmichael, 526 U.S. 137, 147-49 (1999).

         District courts have broad discretion in determining the admissibility of expert testimony. See Gen. Elec. Co. v. Joiner, 522 U.S. 136, 142 (1997); Lapsley v. Xtek, Inc., 689 F.3d 802, 810 (7th Cir. 2012) (“[W]e ‘give the district court wide latitude in performing its gatekeeping function and determining both how to measure the reliability of expert testimony and whether the testimony itself is reliable.'”) (quoting Bielskis v. Louisville Ladder, Inc., 663 F.3d 887, 894 (7th Cir. 2011)). And the proponent of the expert bears the burden of demonstrating that the expert's testimony would satisfy the Daubert standard by a preponderance of the evidence. Lewis v. CITGO Petroleum Corp., 561 F.3d 698, 705 (7th Cir. 2009).

         Analysis

         I. Dr. Thomas DiPrete

         The EEOC's expert, Dr. Thomas DiPrete, is a sociology professor at Columbia University. DiPrete's task was “to determine whether black DHL drivers were more likely than white drivers to drive routes in predominantly black neighborhoods and to drive routes that were ‘less desirable, more difficult, and/or more dangerous.'” Def.'s Mem. Supp. Mot. Strike, Def.'s Ex. 10, DiPrete Rep. at 1. After using regression analysis to study staffing data and pick up delivery data for the delivery areas covered by the DHL stations located in Lisle, Alsip, and Franklin Park, DiPrete concluded that, in general, “black drivers from the [stations] were more likely than white drivers to pick up or deliver packages in neighborhoods that were more black, more non-white, and with higher rates of violent and property crime.” Id. at 2.

         DHL attacks DiPrete's opinions on three fronts. First, DHL argues that DiPrete's opinion is irrelevant to the issues in the case. Second, DHL contends that the regression methodology that DiPrete employed was not reliable or probative. Third, DHL asserts that DiPrete's opinion improperly relies on the opinions of other experts, whom the EEOC has failed to disclose as Fed.R.Civ.P. 26(a)(2) requires.

         A. Relevance

         DHL argues that DiPrete's opinion cannot assist the jury because his regression analysis does not prove that any individual driver was disadvantaged in their route assignments or was intentionally discriminated against by any individual station supervisor. In response, the EEOC counters that DiPrete's multiple regression analyses is relevant because he concludes that for the three DHL stations at issue, there is a correlation between the drivers' race and their assignment to “less desirable” delivery routes. The EEOC's theory is that DHL intentionally shunted black drivers to neighborhoods that were more dangerous, poorer, and predominantly black in comparison to areas to which white drivers were assigned. According to the EEOC, this practice caused black drivers to work in conditions that objectively created hardship by subjecting them to an environment that was humiliating, degrading, and unsafe. See Tart v. Ill. Power Co., 366 F.3d 461, 475 (7th Cir. 2004).

         To help prove this, DiPrete has analyzed the crime rates of the delivery neighborhoods by zip code. He also has analyzed the rates of poverty and percentage of black residents for each zip code area. The EEOC concedes that additional evidence beyond DiPrete's expert report will be necessary to prove that the assignment of drivers to these neighborhoods constituted materially adverse employment actions. But a brick is not a wall, as they say, [1] and the EEOC is not required to rely solely on DiPrete to prove their entire case.

         DHL's objection to the relevance of DiPrete's testimony boils down to this. DHL argues that studying the aggregate effect of its policies does not prove discriminatory intent, because it says nothing about whether a particular driver experienced discriminatory route assignments from a particular supervisor. The EEOC responds that the use of regression analysis to help prove intentional discrimination is well-accepted in disparate treatment cases and is especially useful where, as here, the various factors used by supervisors to determine the working conditions of a group of employees are unknown.

         The Seventh Circuit, in Adams v. Ameritech Services, Inc., 231 F.3d 414, 425 (7th Cir. 2000), considered this recurrent debate about the probity of statistical evidence in discrimination cases:

[W]hat is the proper level of aggregation or disaggregation at which [defendant's] actions should be assessed? At one extreme, one could perhaps look at the [defendant's] entire workforces, management and non-management alike; at the other extreme, one could take a highly individualistic view of humanity and conclude that no two people are exactly alike and statistics are therefore worthless. Neither approach has much to recommend it, of course, but the thought experiment suggests the outer possibilities.

Id. Nonetheless, the Seventh Circuit has repeatedly held that statistical evidence, including regression analysis, may be used to demonstrate discrimination in disparate treatment cases. See id. at 417 (reversing district court's bar of plaintiffs' statistical expert on summary judgment in disparate treatment case); EEOC v. Sears, Roebuck & Co., 839 F.2d 302, 324 n.22 (7th Cir. 1988) (“Multiple regression analyses, designed to determine the effect of several independent variables on a dependent variable, . . . are an accepted and common method of proving disparate treatment claims.”); Mister v. Ill. Cent. Gulf R.R. Co., 832 F.2d 1427, 1430-31 (7th Cir. 1987) (reversing grant of summary judgment in a disparate treatment case where defendant failed to rebut the plaintiffs' statistical showing that the defendant hired a much larger proportion of white than black applicants).

         For example, in Adams, the Seventh Circuit held that an expert's statistical analysis was helpful even when the expert merely concluded that the correlation between an employee's age and the employer's decision to terminate was unlikely to have occurred by chance. 231 F.3d at 425 (holding that, to be relevant, the statistical analysis “need only make the existence of ‘any fact that is of consequence' more or less probable”). As in Adams, DiPrete offers his opinion that it is highly unlikely that the correlation between a driver's race and assignment to a driving route in a predominantly black, higher-poverty, higher-crime neighborhood occurred by chance. As a result, the Court concludes that ...


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