Commercial litigation specialists Ascendion Law rely on Palisade’s PrecisionTree software to create detailed decision trees for mapping out the numerous probabilities at play in a commercial legal dispute. Managing Partner Chilwen Cheng uses these tree models to calculate estimates for clients regarding the risks and rewards of a case, forecast case budgets, understand investigation areas that warrant greater effort, and help focus settlement negotiations with opposing sides.
Based in Vancouver, Ascendion Law handles shareholder disagreements, contract disputes, white-collar defense, and other commercial issues. Every litigation has decision points that a judge weighs which determine the outcome of the case. For example, in contract cases, a judge must decide many questions, such as:
- Proof that an offer was made
- Proof that an acceptance was made
- Proof that something of value was transferred between two parties
- Worth of contract
These multiple decision points each have different likelihoods regarding the judge’s decision. Estimating the chances of winning these complex cases presents a challenge for lawyers.
Using PrecisionTree Helps to Estimate the Chances of Winning Complex Legal Cases
Cheng uses PrecisionTree to develop precise and realistic estimations about commercial cases. “These cases lend themselves towards a decision tree,” he explains. For a contract case, he would begin to map out the percentage of a ‘yes’ or a ‘no’ for each decision point listed above. The percentages are derived from inputs consisting of professional judgement based off case law; Cheng’s team does a deep dive into pre-existing cases to determine how previous judges decided, and can assign a number percentage to the likelihood of a ‘yes’ or a ‘no.’
“After mapping that out in PrecisionTree, we’re then able to say that the likelihood of losing is X percent and winning is Y percent,” says Cheng.
Cheng and his team can get even more detailed in their predictions, with enough data points to plot graphs that display the range of possibilities. “Many lawyers will say ‘on average this case is worth $60,000,’” Cheng says. “What they won’t tell you is it has a one-percent chance of winning a million dollars, and a one-percent chance of winning none.”
At Ascendion Law, Chang and his colleagues give their clients the full picture, showing them the full range of percentages of certain amounts a case could win. “We like to make sure they know that they may have a ten-percent chance of winning a million, but also a ninety-percent chance of winning nothing,” says Cheng. “That’s much more informative than telling them the average amount of money they might win.” Ascendion Law does just that by plotting data points into a graph to show clients where the clusters of higher probability lie in terms of amount of money won.
Managing Partner, Ascendion Law
PrecisionTree Promises Smoother Negotiations
Cheng and his team also use PrecisionTree when negotiating settlements with the opposing side. “In one case, we were able to get eighty percent of what the client asked for,” says Cheng. “We literally sent the tree to the other side, and they then saw exactly where we were coming from and our rationale for our decision. We were able to have a rational conversation—with PrecisionTree, you’re not just horse trading anymore in these negotiations.”
With this powerful tool at their disposal, Cheng and his team have been able to give clients sophisticated estimates of case outcomes that other firms simply can’t provide. “A lawyer who can provide detailed, comprehensive, and defensible positions is vastly superior to one who rests his judgment on vague intuition and luck.”
Cheng’s favorite features of the software include sensitivity analysis and Monte Carlo simulations. Sensitivity analysis allows Cheng and his team to model which variables in a case drive the final outcome, therefore warranting more work. Monte Carlo simulations help create more robust risk models for the client and allow Cheng and his team to understand which aspects of a case require more development to narrow the scope for variability.