In yesterday’s post, we described a scenario involving a simple traffic accident, asking you to estimate the average exposure at trial.



What is the average exposure at trial in this case, based on your counsel’s estimates of these various possible outcomes?

  1. $1.4 million
  2. $3.3 million
  3. $5.5 million
  4. $8.1 million

When presented with this problem at seminars attended by highly experienced litigators and insurance claims professionals, the most common answers are (b) and (c).

Remarkably, there is a “right” answer to this question: it is about $1.4 million.

The other answers would mean you either overpaid by millions of dollars (from Company’s standpoint) or took on a foolish risk (if the Plaintiff or her litigation financier turned down a $1.4 million offer).

Now ask yourself this: if presented with 10 more problems like this one, and the levels of fault and damages awards varied constantly, how confident would you be to avoid the million-dollar mistake every time? And even if you are feeling lucky, does your client or internal client feel the same way? Doubtful.

Not One, But Two Problems

Here’s why this is so difficult for even experienced claims evaluators. There are actually two problems:

  1. Correctly assessing the range of answers on a verdict form
  2. Understanding all of the ways these options could combine to produce a result.

Experienced counsel are extremely good at the first part. Good trial lawyers know the difference between a good case and a terrible case, and the difference between what might impress a jury and what might insult them. They can’t tell you exactly what a jury will do: nobody can (including us). But good trial lawyers do know the difference between a $500,000 case and a $5 million case, and that is half the battle.

The trouble is in the rest of the battle: understanding how all these verdict possibilities combine together into a final exposure number. This is no longer a strictly legal problem but now also a combinatorics problem. (This may sound scary to lawyers who went to law school under the premise that “no math was required.”)

Even worse, combinatorics is uniquely challenging for human beings to estimate. Distinguishing the $500,000 case from the $5 million case is one thing, but what about the $3 million case versus the $7 million case? Or the case with multiple defendants and multiple interlocking claims? Good luck.

Consider the simple traffic accident problem from yesterday. The legal issues include understanding that the verdict will be combination of both sides’ fault, that the net combination of both sides’ fault is a multiplier of the potential damages, and that modified comparative fault means that the Plaintiff can get $0 even if Company bears some fault. A good trial lawyer catches these things. But then somehow all of these combinations need to be further combined to understand how they might affect the final damages award. Whether that number of likely combinations is 50, 500, or 5000, there is no reliable way for a human being to do this consistently. We need help.

How MagnitudeSM Got the Right Answer

This is where MagnitudeSM comes in. MagnitudeSM is a Monte Carlo simulation system, created by a Schiff Hardin trial lawyer, to tackle this valuation problem.

MagnitudeSM works with responsible counsel to take what, in their judgment, might happen and translate possibilities into probabilities. MagnitudeSM simulates millions of jury verdicts to discover the good, the bad, and the ugly.  The final blend of potential outcomes —defense verdicts, plaintiff verdicts, and runaway verdicts —taken together gives the exposure (and thus the settlement value) of the case. It is similar in theory to what lawyers have always tried to do, except that a computer is much faster, is much better at finding combinations, doesn’t lose track of what it has already done, doesn’t make math mistakes, and doesn’t get tired or distracted. MagnitudeSM is still legal advice, but it is legal advice enhanced with analytics tools.

MagnitudeSM is what provided the correct answer to our sample problem. After simulating five million jury verdicts, based on the information provided by trusted counsel, MagnitudeSM finds that the lowest possible award is $0 (a complete defense verdict), and that the largest potential verdict for the Plaintiff is about $20 million. The Plaintiff’s verdict, when she wins, is always at least $7.5 million and her average verdict when she wins is just under $14 million. But accounting for all of those $0 verdicts, and there are a lot of them under this fact pattern, the average verdict —and thus the average exposure — is only $1.4 million.

While individuals are often misled by large numbers like those thrown around in the hypothetical, MagnitudeSM is not misled: it cares only about the facts as your counsel reports them to you and to us. MagnitudeSM works in torts cases, contracts cases, intellectual property cases, and any other claims scenario that presents a lot of moving parts.

In sum, MagnitudeSM helps clients know when they are overpaying or giving somebody a deal. Risk managers can rely on MagnitudeSM to translate outside counsel’s advice into value, and financial departments can finally have a sense of “where these valuations are coming from.” Of course, no one can truly predict the future, and MagnitudeSM can only rely upon the information it is actually given. But if you are going to pay for and rely upon outside legal services, then you should also extract as much value as possible from those services.

If MagnitudeSM sounds like it could improve your bottom line, contact Jonathan Judge for a demonstration or to talk through potential claims.

In future posts, we will explain how MagnitudeSM can reduce stress for outside counsel, help companies optimize their portfolio of risks, and provide other related benefits.