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Statistical Modeling for Litigation

Often, modern litigation is driven by numbers. Plaintiffs in class actions assemble massive datasets cataloguing alleged harms, or may send products to laboratories for testing before a lawsuit has even begun. Defendants have piles of spreadsheets documenting sales, warranty claims, and product testing histories. Settlement values may depend on how much harm may be expected in the future.


In a perfect world, this pile of messy facts could be ordered into clean, clear, and sensible predictions, without costing more than the stakes in the litigation itself, and without needing to ask the court for yet another extension.

This is a difficult task for many attorneys and their clients. Attorneys often lack advanced training in statistics or economics, and many experts come with hefty price tags or don't understand the flow of litigation. There is a gap between the demands of high-stakes litigation and the market for experts.

Our aim is to fill this gap. Speaking both the language of litigation and statistics gives us a cost-effective way to aid parties involved in numbers-driven lawsuits. Whether the issue is inherently statistical, econometric, or psychometric, we can offer a path forward. Our aim is to provide modeling that's sensible and understandable, because we understand that black box estimates are hard to explain and defend.

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