Opinion
18-cv-12719
03-29-2022
PAUL WEIDMAN, et al., Plaintiffs, v. FORD MOTOR COMPANY, Defendant.
OPINION AND ORDER GRANTING IN PART AND DENYING IN PART PLAINTIFFS' MOTION TO EXCLUDE DEFENDANT'S EXPERT JEYA PADMANABAN [#149, #151]
GERSHWIN A. DRAIN UNITED STATES DISTRICT JUDGE
I. INTRODUCTION
Presently before the Court is the Plaintiffs' Motion to Exclude the Defendant Ford Motor Company's Expert Jeya Padmanaban, filed on June 22, 2021. Plaintiffs argue Ms. Padmanaban's testimony must be excluded because her methodology is not reliable, and her conclusions will not assist the factfinder. On July 20, 2021, Defendant filed its Response in Opposition. Defendant argues Plaintiffs' attacks of Ms. Padmanaban's opinion go to the weight, and not to the admissibility of her testimony, thus the Court should deny Plaintiffs' Motion to Exclude Ms. Padmanaban's expert opinion. Plaintiffs filed their Reply in support on August 3, 2021.
Upon review of the parties' submissions, the Court concludes oral argument will not aid in the disposition of this matter. Accordingly, the Court will resolve Plaintiffs' Motion to Exclude the Defendant's Expert Jeya Padmanaban on the briefs. See E.D. Mich. L.R. 7.1(f)(2). For the reasons that follow, the Court will grant in part and deny in part Plaintiffs' Motion to Exclude the Defendant's Expert Jeya Padmanaban.
II. LAW & ANALYSIS
A. Standard of Review
Federal Rule of Evidence 702 governs the admissibility of expert testimony. A party offering an expert's opinion bears the burden of establishing the admissibility of such opinion by a preponderance of the evidence. Nelson v. Tennessee Gas Pipeline Co., 243 F.3d 344, 251 (6th Cir. 2001). Expert testimony is admissible only if it satisfies the requirements of Rule 702 of the Federal Rules of Evidence, which states:
A witness who is qualified as an expert by knowledge, skill, experience, training, or education may testify in the form of an opinion or otherwise if:
(a) the expert's scientific, technical, or other specialized knowledge will help the trier of fact to understand the evidence or to determine a fact in issue;
(b) the testimony is based on sufficient facts or data;
(c) the testimony is the product of reliable principles and methods, and;
(d) the expert has reliably applied the principles and methods to the facts of the case.
Fed. R. Evid. 702. The district court must determine whether the expert's testimony meets three requirements: (1) the expert witness must be qualified by “knowledge, skill, experience, training or education,” (2) the proffered testimony is relevant and “will assist the trier of fact to understand the evidence or to determine a fact in issue,” and (3) the testimony is reliable in that it is based on scientific, technical or other specialized knowledge. Fed.R.Evid. 702; In re Scrap Metal Antitrust Litigation, 527 F.3d 517, 529 (6th Cir. 2008).
The standard to exclude an expert's testimony under Daubert is high, and “rejection of expert testimony is the exception, rather than the rule.” Keyes v. Ocwen Loan Servicing, LLC, 335 F.Supp.3d 951, 956 (E.D. Mich. 2018); Innovation Ventures, L.L.C. v. Custom Nutrition Labs., L.L.C., 520 F.Supp.3d 872, 877 (E.D. Mich. 2021) (citing In re Scrap Metal Antitrust Litig., 527 F.3d 517, 530 (6th Cir. 2008)); Kamp v. FMC Corp., 241 F.Supp.2d 760, 761 (E.D. Mich. 2002) (citing notes to Rule 702) (“[T]he trial court's role as a gatekeeper is not intended to serve as a replacement for the adversary system.”). If there is a reasonable factual basis for expert testimony, it should be admitted. See Keyes, 335 F.Supp.3d at 956 (citing Rule 702; United States v. L.E. Cooke Co., 991 F.2d 336, 342 (6th Cir. 1993)).
“Where the reliability of the evidence is in dispute, it is more appropriate for a judge to admit the evidence than to keep it from the fact-finder because vigorous cross-examination, presentation of contrary evidence, and careful instruction on the burden of proof are the traditional and appropriate means of attacking shaky but admissible evidence.” Avomeen Holdings, LLC v. Thanedar, No. 17-cv-13703, 2019 WL 3491620, at *1 (E.D. Mich. Aug. 1, 2019). Additionally, it is important to distinguish between genuine questions of reliability and questions of credibility and accuracy. In re Scrap Metal, 527 F.3d at 529-30. Any issue regarding the credibility or accuracy of admitted expert testimony goes not to the admissibility of the evidence, but to the weight of the evidence, and can be addressed via crossexamination and “presentation of contrary evidence” by opposing counsel. Id. at 532 (quoting Daubert v. Merrell Dow Pharms., 509 U.S. 570, 596 (1993)).
B. Ms. Padmanaban's Expert Opinion
In her report, Ms. Padmanaban opines that the claims rate for the Brake System Defect in F-150s equipped with engines other than the 3.5L GTDI engine equals___which is much lower than F-150s equipped with the 3.5L GTDI engine subject to Ford's recalls. She further concluded that the claim rate varied significantly based on build date, with class vehicles covered by the first recall having a claim rate of [XXXXX] and class vehicles built after the second recall having a claim rate of [XXXXX]
In addition, Ms. Padmanaban used the claims data to project future annual claim rates for proposed class vehicles and found F-150s with 3.5L GTDI engines subject to the second recall are projected to have an annual claim rate of [XXXXX] at the fifteenth year of service. Id. at 19-20. By comparison, F-150s equipped with all other engines built during the same period are projected to have a annual claim rate, and F-150s with 3.5L GTDI engines built after the recall period are projected to have a [XXXXX] annual claim rate.
Finally, Ms. Padmanaban examined NHTSA's Vehicle Owner's Questionnaire (VOQ) consumer complaint data, and concluded, based on her experience and knowledge of NHTSA defect investigations, that the post-recall complaint rate of [XXXXX] would not typically be considered a [XXXXX] that warrants further investigation by NHTSA.
C. Qualifications
As an initial matter, Ms. Padmanaban is qualified to offer her expert statistical analysis opinions in this matter. She has a degree in Advanced Mathematics from the University of India, and a Master of Science degree from George Washington University in Operations Research. She currently is the president and owner of the statistical and engineering research firm JP Research, Inc., and has been serving in this position since 2005. Before that, she spent 18 years as a Principal Managing Scientist, Senior Operations Research Analyst, and Statistical Consultant. Her work experience entails over 20 years of experience performing reliability and survival analyses using several statistical software packages. She has performed numerous statistical studies using warranty and claims data to predict the number of future claims and failures, and the annual claim rates for various consumer products. She has received awards for her statistical research, such as the Society of Automotive Engineers (SAE) Outstanding Technical Achievement Award and was selected in 2020 by the Association for the Advancement of Automotive Medicine Board of Directors to receive the Award of Merit for lifetime contribution in the area of automotive safety research. She has been invited by NHTSA to make presentations and assess field performance of motor vehicles and components. Ms. Padmanaban has been qualified to provide testimony regarding statistical analysis of automotive performance data by other district courts. See Anderson v. Ford Motor Co., No. 17-03244,2020 WL 1853321 (W.D. Mo. Feb. 14, 2020); Montgomery v. Mitsubishi Motors Corp., No. 04-3234, 2006 WL 1967361, at *6 (E.D. Pa. Jul. 6, 2006) (declining to exclude Ms. Padmanaban's opinion based on a similar data set); see also, e.g., Fox v. Gen. Motors LLC, No. 1:17-cv-209, 2019 WL 3483171, at *24 (N.D.Ga. Feb. 4, 2019) (“Using statistical tools to analyze a dataset is a common practice in many fields[.]”); cf. Kondash v. Kia Motors Am., Inc., No. 1:15-cv-506, 2020 WL 5816228, at *8-9 (S.D. Ohio Sep. 30, 2020) (finding Ms. Padmanaban's methodology to calculate claims rates “generally accepted” and reliable).
In Roberts v. General Motors, LLC, No. 4:13-cv-541 CAS, 2015 WL 6955362 (E.D. Mo. Nov. 10, 2015), the court found the state government database that compiled information about crashes from police reports relied upon by Ms. Padmanaban was an inadequate foundation for the particular accident-data comparisons at issue because the database did not contain sufficient information to permit her to control for the relevant variables. 2015 WL 6955362, at *12-13.
Ms. Padmanaban did not use that database in this case or even offer a similar accident-data analysis. Because Ms. Padmanaban did not use the state police accident database here, Roberts fails to support the exclusion of Ms. Padmanaban's statistical analysis testimony. To the contrary, the Roberts court, like others, found that she was sufficiently qualified to provide testimony based on other statistical analyses of automotive performance data. Roberts, 2015 WL 6955362, at *9 (“Plaintiff does not challenge Ms. Padmanaban's qualifications as a statistician and the Court finds she is qualified to assist the jury.”).
Plaintiffs complain that Ms. Padmanaban is a “quintessential expert for hire” willing to testify “no matter what [Ford]” requests that she opine. That an expert regularly works for a particular client, or on a particular side of litigation, does not render the opinion inadmissible. In re Paoli R.R. Yard PCB Litig., 35 F.3d 717, 753 (3d Cir. 1994) (that most of the expert's recent work had been for plaintiffs in litigation “may undermine her credibility but does not eradicate her expertise.”).
Nor does it subject the expert to heightened scrutiny as Plaintiffs argue. Here, Ms. Padmanaban's statistical analyses are based claims data related to automobiles, a narrow area of expertise that she regularly works in, and one in which courts have frequently found her qualified to provide expert testimony.
D. Claims Rate Opinions
Plaintiffs also complain that Ms. Padmanaban's report purports to calculate the claim rate for all Class Vehicles, but she did not rely on complete data. She relied on [XXXXX] and complaints to NHTSA. As such, Plaintiffs assert her report fails to account for consumers who experienced the Brake System Defect, but had the repair performed by an independent mechanic similar to many of the named Plaintiffs, who did not have their master cylinders repaired at a Ford dealership. Further, Ms. Padmanaban's report did not examine [XXXXX] An increase [XXXXX] would demonstrate a link to defect-related failure, but Ms. Padmanaban's opinion fails to consider this data.
Contrary to Plaintiffs' argument, there is no support for excluding Ms. Padmanaban's opinion because some other information, such as [XXXXX] also might be relevant in Plaintiffs' view. At best, this argument goes to the weight to accord her testimony, and not to its admissibility. See Best v. Lowe's Home Ctrs., Inc., 563 F.3d 171, 181 (6th Cir. 2009) (“Admissibility under Rule 702 does not require perfect methodology[.]”); Innovation Ventures, 2021 WL 598545, at *11 (arguments as to the factual sufficiency of an expert opinion or analysis goes to the weight of the evidence); In re Scrap Metal, 527 F.3d at 523 (allegations that an expert witness used “erroneous data,” and therefore “necessarily produced an erroneous conclusion” are not enough to exclude an expert opinion). Ms. Padmanaban's claims rate opinions are admissible.
E. Survival Analysis Opinions
Next, Plaintiffs argue Ms. Padmanaban compounded her error by using her faulty claim rate data to calculate a “survival analysis” to “predict the future claim rates for the proposed class vehicles.” Plaintiffs also complain Ms. Padmanaban's survival opinions are based on [XXXXX], a general purpose data science software rather than [XXXXX] software, which was used by The results using the [XXXXX] |software reach different conclusions than Ms. Padmanaban's projections.
Here, Plaintiffs' contention that Ms. Padmanaban should have used [XXXXX] to conduct her survival analysis instead of [XXXXX] goes to the weight, rather than the admissibility of her testimony. Ms. Padmanaban deemed [XXXXX] to be the most appropriate software to analyze the information that was available because it provides the flexible parametric models that were needed to address the complex mixture of F-150 brake recalls and repair events.
Plaintiffs inaccurately claim Ms. Padmanaban “appeared to conflate the role of parametric and nonparametric analysis in conducting survival analysis.” ECF No. 149 at 12. As Ms. Padmanaban testified, a sequential combination of both parametric and non-parametric analyses were used to conduct the survival analysis:
[W]hen we did the future prediction, we had to do both. We basically had to do a non-parametric analysis to see where the data fits in, and then we had to do a parametric analysis to project it for future claims using a distribution that we were safe in using based on the nonparametric analysis we did before. So it's a combination of both.
Plaintiffs' argument that it was improper for Ms. Padmanaban's analysis to include a non-parametric analysis is not supported by any expert analysis of her model or legal authority. And again, in addition to those factual flaws, Plaintiffs' argument would at best go only to weight, not admissibility. See Keyes, 335 F.Supp.3d at 956. Ms. Padmanaban's survival analysis opinions are admissible.
F. Recall Opinions
Lastly, Plaintiffs maintain Ms. Padmanaban's opinions about the appropriateness and adequacy of Ford's recalls are baseless. Specifically, Ms. Padmanaban opines that (1) “Ford's decision on the vehicles to include in the first recall group in July 2016 for replacement of master cylinder was a reasonable decision”; (2) “Ford's decision not to extend the second recall to additional vehicles was a reasonable decision”; and (3) “a rate of would not typically be considered by NHTSA as a [XXXXX] that would warrant further investigation.” Plaintiffs argue Ms. Padmanaban offered no explanation for her belief that NHTSA would consider failure rate of somewhere below [XXXXX] to be “pretty good” or “pretty low.” She also failed to consider the [XXXXX]
Here, contrary to Ford's argument, Ms. Padmanaban's experience with NHTSA and their recall and safety regulation processes do not render her qualified to provide opinions about the adequacy of Ford's recall decisions. Rather than just reporting data, Ms. Padmanaban opines on whether the master cylinder failure claims rate in the Class Vehicles justifies Ford's recall decisions, but she has no basis to draw these conclusions. Ms. Padmanaban does not compare her claims rate to master cylinder failure claims rates in other vehicles, nor does she provide a legitimate opinion about what an acceptable claims rate for brake failure would be. Ford cites to other cases where Ms. Padmanaban compared her calculated rates to those of other manufacturer's vehicles, but she failed to do that here. See, e.g., Anderson, 2020 Wl 1853321, at *3 (Ms. Padmanaban compared “estimated failure rates across automobile manufacturers”); Montgomery, 2006 WL 1967361, at *2 (Ms. Padmanaban “compared the risk of fatality or injury for an occupant in a Mitsubishi Montero four-wheel drive vehicle to the same risk in occupants of other sports utility vehicles”).
Ms. Padmanaban speculates the failure rate she calculated to be acceptable because she believes NHTSA “usually say[s] anything less than [XXXXX] pretty good. ” This does not pass Daubert muster. This is especially true because Ms. Padmanaban admits she did not consider the [XXXXX] in her assessment of an acceptable claims rate. Because Ms. Padmanaban offers no reliable evidence about what an acceptable claims rate would be, her opinions that the claims rates justified Ford's recall decisions must be excluded.
III. CONCLUSION
Accordingly, for the reasons articulated above, Plaintiffs' Motion to Exclude Defendant's Expert Jeya Padmanaban [#149, #151] is GRANTED IN PART and DENIED IN PART.
Ms. Padmanaban may offer her claims rate and survival analysis opinions. Ms. Padmanaban's recall opinions are inadmissible under Rule 702.
SO ORDERED.