“Prediction is very difficult, especially if it is about the future.” ~Niels Bohr, Nobel Prize-winning physicist
Predicting case outcomes is vital to the litigation process:
- Prediction forms the basis of the initial attorney/client relationship (i.e., “How good is my case?”)
- Prediction maintains the attorney/client relationship (“I think this fact will be very important and we need to stay strong . . .”)
- Prediction drives case strategy (What do we need to emphasize/downplay to win?)
- Prediction controls litigation efficiency (Should we try to settle or should we go to trial?)
Clients hire attorneys to make these exact predictions.
The very livelihood of an attorney/firm rests on the ability to make good outcome predictions (i.e., What cases are worth our time?; How many resources do we commit?).
Ethical and malpractice complaints frequently arise from poor predictions (“She told me this case was worth $50 million!”).
So how good are you all at predicting outcomes? (Warning: bad news ahead)
- In a study* of 481 attorneys in 44 states, attorneys rated their probability of winning (“winning” was self-defined by the attorney prior to the resolution of the case) at about 65%-70%;
- However, 44% of the time the case did not meet the attorney’s self-defined minimum to be called a “win”
- Only 32% of the time did the case meet the self-defined minimum standard for a “win”.
- Only 24% of cases exceeded predictions.
- The higher the confidence ratings attorneys gave before the resolution of the case the lower the accuracy of predicted outcomes. When attorneys rated their chances of winning at 65% or above, the case was much more likely to fall into the 44% that did not meet the definition of a win.
Does this mean that you should not make predictions?
Should you lower your predictions/expectations?
Should you show less confidence?
No, no, and no.
Showing confidence to your client, the judge, the opposition, and the jury is an important persuasive tool. But, it is just that—a tool. Your objectivity about the strengths and weaknesses of your case has to come from outside feedback sources, from a third party. Those sources include:
- Hire an attorney to consult with you,
- Hire a trial consultant to do focus groups or mock trials,
- Seek out an arbitrator, mediator, or early case resolution program to get some input as to probable outcomes.
Attorneys work in the only performance profession I know where the only feedback they get is AFTER it is too late—when the verdict is read. Other performance professions have rich sources of feedback all along the way so that the performer can make real time adjustments. Athletes have coaches and statistics and photos and video. Actors have audience laughter, applause, and tears. It is only attorneys who are deprived of these real time sources of feedback, creating the need for pre-trial research to generate case feedback for making predictions and adjusting strategies.
The most critical variable in making accurate case predictions is simple: listen to and believe in the feedback. No matter how the feedback might upset you or your client, no matter how the feedback might deflate your expectations for early retirement, no matter how the feedback might bruise your ego, listen to it, learn from it, and adjust your presentation based on it.
Albert Einstein said, “If we knew what we were doing, it wouldn’t be called Research.” Einstein would never make a prediction without data upon which to make that prediction. No good “prognosticator” does. Even street-corner bookies review statistics in detail before setting a point spread and taking a bet. Can you imagine a bookie saying, “I think Silver Sage will win in the 5th race because she smiled at me when I walked through the paddock?” Never. So, what do Einstein and Guido know that we don’t know? They know that data have no emotions and that the best predictions are based on good data.
I predict you will like the end product of your pre-trial research.
*Goodman-Delahunty, Granhag, Hartwig & Loftus; Psychology, Public Policy, and the Law, American Psychological Association, 2010.
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