Improving Legal Case Outcomes with @RISK and PrecisionTree, Part IV

Forecasting Damages Using Monte Carlo Simulation In our last post, we discussed using @RISK software to navigate decision analysis challenges and determine fair market value of intellectual property. This final post will continue exploring ways to enhance your litigation strategy by using @RISK to forecast damages. A common first step in litigation strategy is to …

Improving Legal Case Outcomes with @RISK and PrecisionTree, Part III

Calculating Unassailable Fair Market Value of Intellectual Property using Monte Carlo Simulation Previously we discussed the importance of crafting decision trees in litigation strategy and why patent litigation is an expensive, time-consuming process. In part three, we will be focusing on how to leverage Palisade‚Äôs @RISK software to overcome decision analysis challenges and calculate probabilities …

Improving Legal Case Outcomes with @RISK and PrecisionTree, Part ll

Decision Trees Explained In our first post, we discussed how presenting objective, realistic models that show all possible scenarios helps manage expectations early in the litigation process, setting the stage for productive settlement discussions. In this post, we will be delving into why patent litigation is a particularly expensive process and walk through an example …

Improving Legal Case Outcomes with @RISK and PrecisionTree, Part I

Quantitatively Optimize Your Negotiation Strategy with Decision Trees In litigation, you often get stuck in inefficient negotiations. Between 95-97% of patent lawsuits settle before trial, but not before amassing an average of more than $2 million in expenses, according James C. Yoon, partner at Wilson Sonsini Goodrich & Rosati. If a long negotiation is disadvantageous …