Choose Your Own Adventure

And you may ask yourself, “Well, how did I get here?”  And you may ask yourself, “Where does that highway go to?” And you may ask yourself, “Am I right? Am I wrong?” – Talking Heads[i].

Oftentimes it feels as if disputes, whether in the commercial setting or through litigated matters, find us (in-house counsel, risk managers, outside counsel, company principals and decision makers) without having any say or choice in how the dispute arose (how did I get here?).  However, once the dispute is before us, a series a mini-adventures commence on the road to resolution (either through compromise, trial or arbitration).  The immediate reaction is to determine how the dispute arose; however, at the same time you must ascertain where the dispute is heading (where does that highway go to?).  Along the way, parties encounter mileposts where decisions must be made as to which direction to take on the road to resolution (am I right?  am I wrong?)

Sometimes the terrain is familiar.  Other times it may seem you are in unchartered territory.  The only consistencies are 1) each dispute (i.e., the adventure) will be different from the last, and 2) forks in the road will appear where a combination of information and experience will dictate which path to take.  When the forks appear, parties are wise to not just look backward to inform their decision; instead, equal effort should be invested in looking at all angles and vantages of the dispute to better gauge not only the potential risks and outcomes, but also what effect or impact the decision will have upon the others involved.  Think of a Rubik’s Cube, and the need to examine all sides and squares before turning or twisting the cube.

Over the past twenty-four months, the authors have noted a subtle change in how parties (clients and attorneys) approach disputes and their resolution.  When evaluating matters, those participating have displayed more introspection and self-evaluation, while also taking the time to better understand their opponent on a deeper level than in years past.  Perhaps this is a passing fad; or, its here to stay just like Zoom depositions.

Through this article, we hope you will come away with some new perspectives on evaluating disputes.

Risk Evaluation on the Road to Resolution

Risk has many faces.  While it can be a threat, it can also be an opportunity.  It can be known or unknown, predictable or unforeseeable, quantifiable or simply subject to intuition.  No matter the shape or form it takes, risk must be accepted, accounted for and addressed.

Risk evaluation requires a proactive (as opposed to reactive) approach. However, it is a complex, inexact science.  An off-the-shelf formula does not exist to measure or quantify risk.  Instead, experience and the human factor comprise this equation.

Risk assessment has three goals:

  • Uncovering known risks, those which can be identified and understood because they have been experienced in the past.
  • Making the known risks transparent and easy for those involved to see and comprehend.
  • Understanding and identifying unknown and unanticipated risks a company has not experienced before.[i]

For each identified risk, a potential loss is associated with it.  In other words, money.  Part and parcel of risk assessment is estimating the likely occurrence of potential losses, and the scope of those losses.[ii] 

When evaluating risk, parties must have an honest understanding of their appetite for risk, and look at risk in a strategic fashion.  Emotional bias (evidenced by gut instincts and haphazard decision-making) may lead to positive results.  However, the better approach is to carefully assess the risk in a thoughtful, honest manner.  When done correctly (and honestly), parties can better ensure the identified risks are aligned with the party’s risk tolerance.[iii] 

More importantly, because risk is not stagnant, risk assessment is not a “one and done” exercise.  With each passing day, events inside and outside a party’s orbit arise which can modify or increase the risks that must be addressed.  Those risks must be assessed and cross-checked against the party’s risk tolerance and overall goals.  Consequently, even the most robust risk management practices will have their limitations.  An organization would be mistaken if it does not periodically review its risk management practices, even on a project-by-project basis.  Underscoring this is the reality that after a claim is resolved or a potential risk averted, those involved gain additional experience that can help identify, assess and contain risk going forward. 

Although it may sound dramatic, there is great value when a culture of risk management is instilled in a company.  A culture of risk management will help avoid losses; however, it will also encourage individuals to pay greater attention and consideration to the consequences of their actions.[iv]

Instilling a risk management culture is especially important for growing companies.  As an organization expands, the company must ensure new employees and managers are onboarded in a matter that underscores the company’s values and risk management culture.  Otherwise, the company may find itself with a culture in contravention with its vision and mission.

Equally important is having many voices at the table when evaluating risk.  Risks can and often do intersect.  And sometimes those intersections are not obvious if only one individual is charged with assessing risk, viewing the situation and circumstances through a singular lens.[v]  While you want to avoid paralysis by analysis, risk evaluation should be approached broadly, with eyes and ears wide open.  One method that captures many voicers and points of view is the concept of enterprise risk management.

While still new on the scene, enterprise risk management assesses risk across the entire organization, not just one area or department.  Not only does enterprise risk management assist in evaluating risks, it also can identify opportunities.[vi]  Recently, increased attention has been paid to the evolving standards of enterprise risk management.  As  technology has advanced, modeling of risks is more commonplace and innovation across a variety of industries has developed new ways to mitigate risk and identify opportunities.[vii]    

Under enterprise risk management, those who lead organizations should take a broad perspective on risks and manage them within the company’s risk appetite.  This is accomplished by providing reasonable assurance to management and the board concerning the organization’s strategic objectives. From this perspective, everyone within the organization has risk management responsibilities.[viii] 

A top-down approach to enterprise risk management occurs at the highest levels of a company’s management and might look at the primary risks to an organization. In comparison, a bottom-up approach involves a comprehensive identification of all important risks at the level of risk ownership, which are then evaluated for impact and likelihood, and mitigation measures developed and prioritized accordingly. Arguably, combining the two approaches can provide a thorough evaluation of a company’s risks and opportunities.[ix]  

The Decision Tree

There is some debate as to who coined the term “Decision Tree” or who first applied the concept as a risk management tool.  By way of example, in 1964 the decision tree was praised as an analytical means to clarify the risks, objectives, gains and needs.[x]   

Decision trees assist decision-makers in evaluating choices in a logical fashion.  Decision trees can be as simple or complex as the need (or desire), depending upon the complexity of the issues involved.  Some contend decision tree analysis is a core component of competent lawyering.[xi]  While that may be an overstatement, decisions trees can assist clients and their lawyers with evaluating a variety of potentialities arising from a given dispute or claim.  Regardless of what tools are used, many implications springboard from predicting case outcomes.  Some may have consequences outside the instant matter, requiring risk evaluation from an enterprise level.

Decision trees can provide a variety of benefits:

  • Supplementing attorney intuition (providing a check to a lawyer’s “gut calculator”);
  • Transparency and improved client communication;
  • Evaluating risks more holistically;
  • Slowing down and obviating the need to react prematurely; and
  • Separating the emotional from the analytical.[xii]

While there are no guarantees evaluating claims or disputes through a decision tree will yield bullet-proof results, the process provides another way of evaluating the road ahead.

By way of example, the following steps can be used to construct a decision tree:[xiii]

  • Identify the areas of uncertainty or points of disagreement (elements of a cause of action or claim, whether summary judgment will be successful) and apply probabilities or estimates to each item.
  • Create a tree/flow chart that flows logically (and optically).
  • Set up the tree from the perspective of which party carries the burden of proof.
  • Place the points of uncertainty/disagreement on the decision tree (with their respective probabilities or estimates).
  • “Solve the tree” by applying the probabilities/estimates to the items at issue.

Applied to the litigated setting, a simple decision tree could provide the following evaluation:[xiv]

  • Probability of plaintiff surviving summary judgment 80%
  • Likelihood of prevailing at trial with a liability verdict in favor of plaintiff 60%
  • Likelihood of a defense verdict 40%
  • Cumulative probability of a damages award at trial 48% (80% x 60% = 48%)

Needless to say, a decision tree is only as reliable as the information inserted (taking into consideration a variety of factors outside the four corners of the claim or complaint).  Decision trees also involve subjective estimates of probabilities and outcomes, injecting an element of inexactness.  Further, decision trees can assist with “big picture” decisions (do we settle or litigate?), but can also be employed when making tactical decisions during the life of a claim.[xv]

Those building decision trees must protect against overconfidence and optimistic/inflated views of themselves and their claims (or defenses).  Those egocentric biases may lead to skewed results.[xvi]  A related phenomenon is optimism bias which stems from a person’s belief they are less likely to experience a negative event than others.[xvii]  Examples of optimism bias include:

  • Status quo bias. People have a tendency to prefer the way things are and avid change.
  • Overconfidence bias. A party believes its experience, knowledge or skills give her or him an edge. 
  • Confirmation bias. The risk assessor sees what they want to see and drives the risk assessment to a desired end (ignoring the objective, actual risks).
  • Loss-aversion bias. Individuals view the pain of loss up to twice as much as the happiness of gain, placing too much weight on the risk of loss as opposed to the potential upside of the situation.[xviii]

Another influencer is the “anchoring effect” which can occur when parties hold onto the first number they hear or see.  To avoid this, the better approach is to evaluate possible outcomes (both favorable and unfavorable) before attaching any numbers (either percentages of success or dollar amounts).[xix] 

Regardless, decision trees can provide another tool for evaluating disputes when implemented properly.  Sometimes parties need to view a dispute from many angles before the totality of the situation sinks in and informed, rational decisions can be made.

Moneyball in the Boardroom and the Courtroom

In 2004, author Michael Lewis introduced the world to the term “Moneyball” and the world of analytics in Major League Baseball.[xx]  Moneyball revealed how the Oakland Athletics relied upon analytical gauges of player performance to field a team that could compete against big market teams.  Ultimately, the team demonstrated how on-base percentage and slugging percentage were the best indicators of offensive success (offending conventional baseball beliefs held sacred by the baseball establishment).  Since that time, virtually every professional sport has relied upon some element of analytics in an effort to gain an edge over the competition.  Analytics are now becoming part of the lexicon of attorneys and their clients.

Predictive Analytics

Slowly but surely, analytics have worked their way into the practice of law.  For instance, virtually everyone is familiar with any number of document management systems that provide for effective and efficient document review.  This is a form of predictive analytics or predictive coding (also called computer-or technology-assisted review).[xxi]  In Moore v. Publicis Groupe (S.D.N.Y. 2012) 287 F.R.D. 182, 192, adopted sub nom. Moore v. Publicis Groupe SA (S.D.N.Y., Apr. 26, 2012, No. 11 CIV. 1279 ALC AJP),  2012 WL 1446534, Magistrate Judge Andrew Peck described computer-assisted review in e-discovery as “an acceptable way to search for relevant [electronically stored information].”  “Computer-assisted coding” was defined as a tool that uses “sophisticated algorithms to enable the computer to determine relevance, based on interaction with a human reviewer.” 

Millions of hours of attorney time have been saved using predictive coding as opposed to reviewing and organizing documents in a manual, linear manner.  However, the goal of discovery is not to simply plow through the documents, data and materials; rather, the goal is to mine the facts underlying the dispute.

In one instance, a law firm representing a corporate client being sued by a former employee in a whistleblower suit targeted the data most likely to identify the facts and applied advanced analytics to 675,000 documents.  This allowed the attorneys to know with a high degree of confidence the allegations were baseless, leading to a nuisance value settlement (without conducting any formal discovery and saving tens of thousands, if not hundreds of thousands, of dollars for the client).[xxii] 

In the courtroom, analytics has already changed jury selection.  Numerous databases and predictive tools have assisted litigants in selecting jurors they hope will be favorable of them or skeptical of their opponent.[xxiii]  Other examples where advanced analytics can play a role are:

  • Internal or regulatory investigations; and
  • Mergers and acquisitions
    • During the due diligence period, and
    • Post-closing when evaluating potential indemnity claims.

Moving forward, we can expect to see more and more instances where analytics play a role in business and the practice of law.

Predicting the Future

While no longer in its infancy, companies are employing analytics to understand consumer behavior patterns, for example (what we buy, what we do, our demographic characteristics).   Some companies are using analytics to help prevent litigation by identifying particular behaviors that have historically led to litigation or claims, and implementing training to mitigate those behaviors.[xxiv]

Using analytics, algorithms have been built to identify signs of misconduct as they are happening (rather than wait for an issue or claim to develop).  What the results revealed is there are patterns in individuals’ misconduct, allowing companies to be proactive in ferreting out bad actors and compliance risks rather than react when a claim, investigation or other disruption occurs.[xxv] 

Lawyers who understand how to use analytics can partner with their clients proactively to mitigate certain internal and external risks.  At the same time, caution must be employed to not abuse or misuse the information learned from analytics. 

The Endowment Effect

When facing a claim, it is wise to evaluate the matter from all angles (particularly from the view of the claimant). 


The claimant (usually a plaintiff) owns the claim (and all of the potential hopes, justice, emotion, and fairness the claim carries, coupled with the time, energy, etc., that has been invested physically, emotionally and/or financially leading up to the present).[xxvi] 

Which begs the question . . . why does that matter?  Because anything that is personal carries great value to the individual.[xxvii]  And the longer “it” (e.g., the claim, lawsuit) is held, the more valuable it becomes.  Think of compounding interest.

In 1980, economist Richard H. Thaler coined the term “endowment effect” and conducted experiments to prove his thesis, namely that people will often overvalue or demand a higher price for something they possess than they would be willing to pay to sell it.  One experiment involved coffee mugs. Individuals randomly assigned a coffee mug were tasked with selling their mug, while another group played the role of buyers.[xxviii] 

The result:  Those holding the mugs were only willing to sell at prices substantially higher than the prices individuals without a mug were willing to pay.

Why? The mug belonged to them!  It was special and had value.  It may not be logical or make sense (objectively, financially or otherwise), but it is a reality that must be plugged into the calculus anytime you evaluate claims and lawsuits.  This also explains why defendants or pre-litigation targets often feel they end up paying a premium to resolve claims.[xxix]


When and how a claim, either affirmative or defensive, will arise can be difficult to predict.  Being proactive and anticipatory can reduce some of those risks, and allow parties to make informed decisions on how to respond.  This requires advanced planning and a sound, disciplined risk management plan and approach.  When successfully implemented, a company’s attention can be focused on its business as opposed to diverting resources unnecessarily to solving problems.  At the same time, when claims arise, approaching the situation in a holistic manner may lead to efficient and creative resolution


[i] Coleman, Thomas S., A Practical Guide to Risk Management (2011). 

[ii] Williams, et al., Management of Risk and Uncertainty in Systems Acquisitions, Proceedings of the 1983 Defense Risk and Uncertainty Workshop, Fort Belvoir, VA.

[iii] Michael Berman, The Upside of Risk (2021), p. 20-28, 49.

[iv] Michael Berman, The Upside of Risk (2021), p. 94.

[v] Michael Berman, The Upside of Risk (2021), p. 182.

[vi] Michael Berman, The Upside of Risk (2021), p. 28.

[vii] Stephen M. Bainbridge, Caremark and Enterprise Risk Management (2009) 34 J. Corp. L. 967, 969.

[viii] William G. Shenkir, CPA, Ph.D. And Paul L. Walker, CPA, Ph.D., Enterprise Risk Management And The Strategy-Risk-Focused Organization, Cost Management May/June 2006 WL 8080497.

[ix] A. Verona Dorch, Successful Partnering Between Inside and Outside Counsel, Enterprise risk management—ERM program development, 2 § 25B:16.

[x] Magee, John F., Decision Trees for Decision Making, Harv. Bus. Rev., July-Aug. 1964, at 126-38.

[xi] Katrina Lee, Decision Tree Analysis for Law Practice (2020) 35 Ohio St. J. on Disp. Resol. 405, 410–411.

[xii] Katrina Lee, Decision Tree Analysis for Law Practice (2020) 35 Ohio St. J. on Disp. Resol. 405, 411-416.

[xiii] Barbara A. Reeves, Uprooting the Decision Tree, Advocate, August 2018.

[xiv] Barbara A. Reeves, Uprooting the Decision Tree, Advocate, August 2018, 405, 423.

[xv] Craig B. Glidden, Laura M. Robertson, and Marc B. Victor, § 12:26. Analysis of risk, cost and value—Cost-benefit analysis using sensitivity analyses, 1 Successful Partnering Between Inside and Outside Counsel § 12:26.

[xvi] Katrina Lee, Decision Tree Analysis for Law Practice (2020) 35 Ohio St. J. on Disp. Resol. 405, 429.

[xvii] Michael Berman, The Upside of Risk (2021), p. 126.

[xviii] Michael Berman, The Upside of Risk (2021), p. 126-127.

[xix] Katrina Lee, Decision Tree Analysis for Law Practice (2020) 35 Ohio St. J. on Disp. Resol. 405, 430.

[xx] Lewis, Michael. 2004. Moneyball. New York, NY: WW Norton.

[xxi] Bennett B. Borden, Amy Ramsey Marcos, Lawyering in the Information Age Leveraging Analytics to Be A Better Attorney, ABA SciTech Law., Winter 2016, at 12, 13.

[xxii] Bennett B. Borden, Amy Ramsey Marcos, Lawyering in the Information Age Leveraging Analytics to Be A Better Attorney, ABA SciTech Law., Winter 2016, at 12, 14.

[xxiii] Jason Kreag, Prosecutorial Analytics (2017) 94 Wash. U. L. Rev. 771, 805.

[xxiv] Gregory Stern, The Evolution of Data Analytics and Litigation Management, ACC Docket, May 2019, at 26, 28.

[xxv] Bennett B. Borden, Amy Ramsey Marcos, Lawyering in the Information Age Leveraging Analytics to Be A Better Attorney, ABA SciTech Law., Winter 2016, at 12, 14–15.

[xxvi] Barbara A. Reeves, Uprooting the Decision Tree, Advocate, August 2018.

[xxvii] While this may have more application to individual claimants or plaintiffs, keep in mind the decision makers for any size entity are also individuals who are moved, persuaded and influenced by the same factors.

[xxviii] Daniel Kahneman, Jack L. Knetsch & Richard H. Thaler, Experimental Tests of the Endowment Effect and the Coase Theorem, 98 J. POL. ECON. 1325-48 (1990).

[xxix] Elizabeth M. Bailey, Behavioral Economics: Implications for Antitrust Practitioners (2010) 9 Antitrust Source 1, 7.