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April 21, 2022 Practice Points

Regression Analysis for Trade Secrets Misappropriation

What are the possible uses of this method to construct a monetary claim for damages?

By Steele French

One factor in determining monetary relief for trade secret misappropriation is the fact and extent of any pecuniary loss or actor’s pecuniary gain caused using the misappropriated trade secrets. The degree of certainty to which the causality is established can play a role in the amount of monetary relief deemed appropriate. Ultimately, the performed analysis should address potentially conflating relevant factors when determining damages. In some cases, a regression may be appropriate. This Practice Point focuses on the possible uses of regression analysis to construct a monetary claim for damages.

Regression analysis is a method for this assessment that courts have, at times, accepted (see United States v. Valencia, 600 F.3d 389, 427 (5th Cir. 2010); see also Huawei Techs. Co. v. T-Mobile US, Inc., 2017 U.S. Dist. Lexis 218166 at *29 (E.D. Tex. Sept. 10, 2017); St. Clair Intell. Prop. Consultants v. Acer, Inc., 935 F. Supp. 2d 779, 782 (D. Del. 2013)). A regression is a mathematical model that seeks to explain a dependent variable, such as sales price or quantity, with a set of independent variables, such as product features or time. The appropriate set of independent variables is determined by the practitioner.

In the case of trade secret misappropriation, a few possible instances where regression analysis may be a helpful approach are as follows: (1) lost sales or a negative inflection of the plaintiff’s sales trend of the associated products, (2) price erosion and (3) a change in the usage rate of the products or services. A properly constructed regression model can potentially help establish a relationship between the misappropriation and market outcomes.

A product’s sales trend can be impacted by a broad array of factors, such as the product life cycle, product features, exogenous shocks, long-term time trends, new market entrants, etc. When a trade secret is misappropriated, this can mean the defendant offers a competing product in advance of the but-for world. As the defendant gains market share, there may be a corresponding inflection in the sales trend of the plaintiff’s product. A potential regression could estimate a coefficient quantifying the change in the sales pattern, which can be used to quantify damages from the theft. Since the model can control for potentially conflating factors, the statistical significance of the coefficient can be used as evidence of cause.

A traditional quantification of damages from trade secret misappropriation is the avoided cost of developing the trade secret avoided by defendant. These avoided costs may be passed to consumers through a lower price, and the plaintiff may be forced to lower their price to compete. Here, a regression analysis could potentially establish cause and quantify the extent of the price change associated with the early entry of the defendant. If available and appropriate, an effective control is the price of related products unimpacted by the trade secret or the early entry of the defendant.

Many businesses operate on an advertising sales model or achieve revenue through streams other than direct payment from the consumer. Under these circumstances, the trade secret may help provide the consumer with a better experience and increase usage. A regression model can estimate the extent to which the trade secret impacted consumer behavior. If appropriate, the percentage change in consumer behavior can be used as an apportionment factor and apply it to the appropriate data as part of a quantification of any of the three damage claims listed above.

Regression analysis is a data-intensive process. To be properly constructed, it requires the production of detailed sales data, product information, and other potentially impactful documents from both the plaintiff and defendant. If sufficient data is available in the record of a case, regression analysis may facilitate a broader understanding of the factors impacting the sales of the product, thereby yielding insight into causation and damages opinions. However, it may not be appropriate in every situation. Each case is different, and counsel should seek appropriate experts to determine the appropriateness and feasibility of regression analysis for an individual case and circumstance.

Steele French is a senior director with Ankura in Emeryville, California.

The views expressed herein are those of the author(s) and not necessarily the views of Ankura Consulting Group, LLC., its management, its subsidiaries, its affiliates, or its other professionals. Ankura is not a law firm and cannot provide legal advice.

Ankura is the Litigation Advisory Services Sponsor of the ABA Litigation Section. This article should not be construed as an endorsement by the ABA or ABA Entities.

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