Tuholski Litigation Consulting LLC
Tuholski Litigation Consulting LLC

Bayesian Simulations… A New Way To Look At Financial Exposure In Litigation

In our last two posts, we discussed the concept of the “expected value” of your case and how those values are affected by non-legal factors.  In this post, we will discuss proprietary methodology developed by Tuholski Litigation Consulting that can be used in assessing a client’s financial exposure in a way that is different than the way virtually all trial consultants think about this topic.  This methodology is particularly effective when considering the risks associated with taking a case to trial and verdict, as it more accurately captures the universe of possible verdicts in a quantifiable way.

Before describing the methodology developed by Tuholski Litigation Consulting, let’s consider the various ways counsel could assess their client’s potential exposure when bringing a case to a jury verdict.  Our experience indicates that there are at least three methods, in increasing order of accuracy, that counsel could use to assess their client’s exposure:

1.  Gut feelings/hunches/personal experience

2.  Archival verdict searches

3.  Mock trial

We should note that our intention here is not to dismiss an experienced trial counsel’s feelings about their client’s exposure, but rather to illustrate that there are ways further narrow our predictions as to an ultimate jury verdict.  Further, to the extent that case facts and witnesses are idiosyncratic, experience and archival searches lose predictive value.  A well-conducted mock trial in which there is well developed damage arguments for both sides is an effective way to gain an understanding of a client’s potential exposure.  The problem that we have seen in the consulting industry is that most consultants do not have the background training and experience to treat and analyze the data in a way that is truly informative and ultimately predictive of a trail outcome.  Let’s discuss an example:

Consider a case in which plaintiff seeks damages in the amount of $2 million, and the case is researched through a mock trial with three deliberating jury panels that ultimately return verdicts of $500,000, $800,000 and $1.4 million in damages for the plaintiff.  This is typically where the “damage analysis” ends with most consultants… but what should counsel do with these numbers?   If opposing counsel subsequently offers a settlement in the case for $800,000, how do the data from our hypothetical mock trial inform counsel?

Tuholski Litigation Consulting has developed a more effective way to examine damages data, based on Bayesian statistics.  In a nutshell, the purpose of Bayesian analyses is not to predict any one data point (for example, what a jury would award in your case), but rather a probabalistic range of possible outcomes.  By collecting some additional data and applying proprietary algorithms, we are able to turn the simplistic data above, into a much more rich and informative analysis as illustrated below:

These data can also be captured in tabular form, such as below:

Verdict In Thousands

Percent Over

$716.68

90

$805.79

80

$925.27

60

$1026.52

40

$1146.00

20

$1235.10

10

Let’s reconsider the question that was posed earlier, if opposing counsel offered an $800,000 settlement, what should your client do?  According to our new analysis, it is clear that this settlement is undervalued because it’s likely that approximately 80% of the time a jury would come back with a verdict higher than approximately $800,000.  As such, we should seriously consider accepting the settlement offer.  Conversely, if opposing counsel proffered a $1.1 million settlement offer, we should seriously consider rejecting that offer, because according to our analysis there is only a 20 percent chance that a jury would return a verdict for that amount or higher.

Our approach also let’s us model and simulate various scenarios that capture the effect of what we consider a bad venire as well as what to expect if particularly bad jurors are seated.  For example, by adjusting certain weights in our algorithms, we can simulate what jurors in a particularly bad venire might do with our case.  Again, these simulations are based on the exact same data as we discussed above.   

Verdict In Thousands

Percent Over

$832.22

90

$920.48

80

$1038.84

60

$1139.14

40

$1257.49

20

$1345.76

10

Using the same data set as before, we’re now able to gain a better understanding of the effect of a trying our case in a particularly bad venue.  Clearly, there has been a shift to the side of a larger verdict, and there is also more variability in the data.  If we could reasonably assess that we have a bad jury and were able to make a settlement offer for $1 million, for example, these data demonstrate that would be a good deal for us.

However, we can go one step further.  What if we knew that we have several bad jurors on our panel, perhaps because we we not afforded the opportunity to strike them?  We can also simulate these effects, and again, these simulations come from the exact same data set as we’ve used throughout this example.

Verdict in Thousands

Percent Over

$1122.84

90

$1163.64

80

$1218.35

60

$1264.72

40

$1319.43

20

$1360.23

10

Suddenly, that $1.1 million settlement offer looks pretty good.

The Damage Simulator developed by Tuholski Litigation Consulting has a unique value in the trial consulting field, as it allows clients and those working within a litigation risk-analysis environment to have greater understanding of the true risk of taking their case to a jury, which ultimately allows clients to make more informed settlement decisions.

 

Tuholski Litigation Consulting, LLC is a full service nationwide trial consulting firm with offices in Oklahoma City and Dallas. 

 

 

 

 

 

 

 

 

 

 

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