The presenter is Joshua E. Fruchter, Esq., a mediator and litigator with over twenty five years of experience settling disputes in litigation and family business environments.

Among other topics, attendees will learn:

• Why familiarity with psychological traps and cognitive biases can spell the difference between success and failure in settlement negotiations and mediations.
• How falling victim to confirmation bias cost one insurance company over $7 million in damages.
• What buying chocolate bars from Boy Scouts has to do with breaking impasses in negotiations and mediations.
• The psychological principle behind why “bracketing” works in mediation.

Click here for further details and to register.

We hope you can join us.

The post Free Webinar for Litigators and Mediators: July 21: The Top 7 Psychological Traps to Watch Out For in Litigation and Mediation appeared first on Merge Mediation Group Blog.

However, it’s only when the “whittling down” results from misuse of the rules of probability that such criticism is warranted. A properly constructed decision tree that follows these rules will reveal risks that legitimately reduce the value of a plaintiff’s case. This blog post will explain how to correctly assign probabilities to the branches of a decision tree in a manner that avoids “garbage in, garbage out.”

Basics of Decision Tree Analysis

To recap for any readers who did not attend the webinar or are otherwise unfamiliar with the subject — decisions trees are graphical representations of the various uncertainties that comprise a lawsuit, and the probabilities of how each of those uncertainties will resolve.

For example, in a negligence case, given the evidence, the law, and the known leanings of the jury pool, what is the likelihood that the jury will find the defendant was negligent? And even if the jury finds the defendant was negligent, what is the probability that the jury will find plaintiff’s comparative fault exceeded a threshold barring recovery? And even if the jury finds that plaintiff’s comparative fault did not exceed that threshold, what percentage fault will the jury assign to the plaintiff?

After determining the probabilities for how each of the material uncertainties in a lawsuit is likely to resolve, and entering them into a decision tree, it becomes possible to calculate the overall likelihood that each path through the tree will occur using what is known as the multiplication rule of probability (“Multiplication Rule”). That is, the probabilities along each specific path through the tree are multiplied (e.g., 60% chance that defendant will be found negligent x 75% chance that plaintiff is less than 50% at fault x 25% chance of assigning 40% fault to the plaintiff) to calculate the cumulative probability of each particular outcome.

For example, here is the decision tree for the lawsuit discussed in our recent webinar. See, for instance, the cumulative probability of the top branch — 0.60 x 0.95 x 0.10 x 0.75 = 4.3%.

Or to use a much simpler illustration, here’s a decision tree illustrating multiplication of the probabilities of flipping a fair coin two times in a row:

The process of multiplying probabilities, however, can be abused, and such abuse has unfortunately led some to question the utility of decision tree analysis. For example, a defendant might argue that there’s a 50/50 chance they’ll prevail on their motion to dismiss, and even if they don’t, there’s a 50/50 chance they’ll prevail on their motion for summary judgment. A 50% chance of winning the case at the motion to dismiss stage, plus a 50% chance of winning the case at summary judgment (which is 50% of the remaining 50% after a loss on the motion to dismiss, or 25%), results in a 75% chance of the defendant winning even before getting to trial, and only a 25% chance that the plaintiff will even reach trial (which 25% will be further whittled down by additional uncertainties at trial). Sounds like the plaintiff is starting out behind the eight ball.

Here’s a visual of the defendant’s line of reasoning:

But of course, what’s good for the goose is good for the gander. The plaintiff can play this game too, arguing that there’s a 50/50 chance that defendant’s winning motion to dismiss will be reversed on appeal, and should the defendant lose its motion to dismiss, but prevail on summary judgment, there’s also a 50/50 chance that the summary judgment decision will be reversed. This turns the tables on defendant and whittles its chances of avoiding trial back down to 37.5%. Touché!

So is decision tree analysis just goofing around with numbers? Absolutely not. While the math in the above example is technically correct, both the defendant and plaintiff are misusing the Multiplication Rule. Or to put it differently, decision tree analysis is a highly effective risk management tool, but only in competent hands, and if a user puts “garbage in,” they’ll get “garbage out.” A big part of properly using decision tree analysis is understanding how the Multiplication Rule works. Let us now delve into that subject.

The Two Versions of the Multiplication Rule of Probability

Laymen who haven’t studied mathematics typically understand the multiplication rule of probability to state that the joint probability that both “A” and “B” will occur is the probability that “A” will occur times the probability that “B” will occur. Or in mathematical notation: P(A & B) = P(A) x P(B) (where “P” stands for probability).

But as Professor James Brook (formerly of New York Law School) observes in his highly recommended “A Lawyer’s Guide to Probability and Statistics,” this special form of the multiplication rule only applies if events A and B are independent.

In the parlance of probability, independence is a situation where the occurrence or non-occurrence of event A has no influence on the probability that event B will occur or not occur (and vice versa). This accurately describes the probability of two tosses of a fair coin. The probability that the second toss will land on heads is independent of the outcome of the first toss. That is, whether the first toss was heads or tails has no influence on whether the second toss will be heads or tails (i.e., for both tosses, the odds are 50/50 heads or tails).

But let’s look at a second illustration. A deck of cards contains 52 cards of which there are 13 spades, 13 hearts, 13 clubs, and 13 diamonds. What is the probability that I will pick a spade from a deck of cards? The answer is 13/52, or 25%. What’s the probability that my second selection will also be a spade?

Careful. There are two scenarios here. If I return the first selection to the deck and reshuffle, the probability of choosing a spade on the second selection remains 13/52 because there are still 52 cards and 13 spades in the deck. The two selections are independent because the card I chose for the first selection was returned to the deck and therefore has no influence on the card I choose for the second selection. I am starting from scratch.

But what if I don’t replace the first card selected. The probability of selecting a spade on the second selection then depends, or is conditional, on what card I selected on the first choice.

If I first selected a spade and removed it from the deck, then the chance of choosing a spade on the second selection is 12/51 because now there are only 12 spades in a deck of 51. But if my first selection was not a spade and I removed it from the deck, then the chance of choosing a spade on the second selection is 13/51, because while there are still 13 spades in the deck, the deck now only has 51 cards. Thus, the probability of choosing a spade on the second selection depends on, or is conditional on whether the first card removed was a spade or not. More generally, dependence exists where the outcome of the first event affects the probability of the second event.

When the outcome of one event depends on the outcome of an earlier event, the Multiplication Rule changes and the probability that both A and B will occur is the probability that A will occur times the probability that B will occur given that A has already occurred. This is what is known as a conditional probability. The mathematical notation is: P(A & B) = P(B|A) x P(A) with P(B|A) being read as the probability of B given A.

As Professor Brook explains, what the modified version of the Multiplication Rule above teaches us is that when events are dependent “attention must be paid to conditional probabilities.” This means we need to consider what the probability of the second event is given that the first event has already occurred (which will be different than the probability of the second event if the first event never occurred).

Misuse of the Multiplication Rule in Litigation

The failure to properly apply the Multiplication Rule in situations involving conditional probabilities has led to some interesting decisions shooting down attempts by one party to string together a series of unlikely events to demonstrate the improbability of its adversary’s narrative. For example, in Yassin by Yassin v. Certified Grocers of Illinois, Inc., 502 N.E.2d 315 (1986), a lawsuit was commenced on behalf of a three-year-old child who was severely injured when she placed her left hand in an operating commercial meat tenderizer. Among other defendants, the plaintiff sued the grocery store where the accident occurred (which happened to be owned by her father and uncle); the manufacturer of the meat tenderizer; and the laboratory that tested a model of the meat tenderizer.

The case went to trial, and the jury found that the meat tenderizer was not unreasonably dangerous, and therefore found the manufacturer and laboratory were not liable. However, the jury found the grocer was negligent and awarded $300,000 in damages. Plaintiff appealed the verdict in favor of the manufacturer and the laboratory on the ground that she was denied a fair trial.

One of the issues on appeal was whether the trial court had erred in allowing the testimony of an engineering professor that the probability of plaintiff’s accident was one in a billion. Specifically, the professor assigned probabilities to the following sequence of events:

(1) that an infant would wander away from its mother

(2) that the doors to the rear area of a store would be left open

(3) that boxes would be available for children to climb

(4) that a child would climb onto the boxes

(5) that a broken switch on a meat tenderizer would not be repaired

(6) that a meat tenderizer would be left running and unattended.

Multiplying the probabilities of each of these events, he concluded that the likelihood of this “bizarre string of circumstances” converging was on the order of one in a billion, and certainly not predictable by the engineers who designed the meat tenderizer.

The appellate court found this expert testimony objectionable on two grounds. First, the expert did not supply any evidentiary basis for the probabilities he assigned to each event; instead, the percentages appear to have been taken out of “thin air.” As the court explained, “no studies were presented of the number of grocery stores with doors broken, or with boxes available to be climbed; thus, [the] assignment of probabilities of these events was completely arbitrary, and an expert’s conclusions cannot be based on pure conjecture or speculation.”

Second, the court observed that the expert had misapplied the Multiplication Rule when he multiplied the probabilities he assigned to each individual event without proof of independence. As the court explained, “for this so-called ‘product rule’ to be utilized, the predicted events must be independent.”  That was clearly “not the case here, because the likelihood that a child would climb on boxes depends directly on whether those boxes were available, and it is more likely that a meat tenderizer will be left running unattended if it has a broken switch.”

In other words, the expert multiplied the probabilities of the events as if they were independent when, in fact, the probability of certain events was affected by the fact that certain other events had already occurred. For example, the expert treated the likelihood that a three-year old child would wander away from its mother as an independent event when clearly the likelihood of such a child wandering away from its mother is much higher when a box on which the child can climb is visible. Young children like climbing on boxes!

Yassin is not the first decision to have flagged abuse of the Multiplication Rule. See, e.g., People v. Collins, 438 P.2d 33, 38 (1968) (“the specific technique presented through the mathematician’s testimony and advanced by the prosecutor to measure the probabilities in question suffered from two basic and pervasive defects—an inadequate evidentiary foundation and an inadequate proof of statistical independence.”).

There are two relevant takeaways from Yassin and like decisions relevant to our discussion of decision tree analysis.

#1: Grounding Probabilities in a Decision Tree in the Evidence, the Law and Any Intangibles

The probabilities for how each uncertainty in a decision tree is likely to resolve need to be strongly grounded in the available evidence and applicable law (and any known intangible factors). To that end, during our recent webinar, we explained that this requires a group effort among attorneys knowledgeable about the case to develop and thoroughly weigh a list of reasons for why a particular uncertainty might resolve one way or the other (ideally considering the “bad” evidence and law first to mitigate confirmation bias).

For example, in the case we discussed during the webinar (Am. Guarantee & Liab. Ins. Co. v. ACE Am. Ins. Co., 413 F. Supp. 3d 583 (S.D. Tex. 2019), aff’d, 990 F.3d 842 (5th Cir. 2021)), defendants might be found negligent because there was deposition testimony from the driver that it was dangerous to park where he did, evidence that the driver stopped short, and a host of intangible factors — the plaintiffs were highly sympathetic, the plaintiffs’ attorney was highly capable, and the case was being tried before a pro-plaintiff judge and jury. On the other hand, the driver did not receive a ticket for parking where he did.

In sum, considered analysis by a team of attorneys of all of the reasons why an uncertainty may resolve in certain ways addresses the need (absent in Yassin) for an evidentiary basis for the probabilities assigned. It also illustrates why any attempt by a defendant to minimize the probability of a plaintiff’s success with a string of speculative probabilities is flawed. Instead, the defendant needs to explain the basis for its confidence in prevailing on a motion to dismiss and/or a motion for summary judgment. For example, on the former, what key allegations are missing from the complaint that render plaintiff’s claims inadequately plead? And with respect to summary judgment, on what key elements of plaintiff’s claim and/or defendant’s affirmative defenses are there likely to be no disputes of material fact? Concerning the latter, it is typically extremely difficult to reliably predict one’s chances of winning summary judgment without the benefit of discovery, and thus there’s often little evidentiary basis for estimating the probability of prevailing on a motion for summary judgment before discovery concludes.

#2: Evaluating Independence of Probabilities

When constructing a decision tree, parties and any neutrals must consider conditional probabilities. For example, in the case we discussed during the webinar (Am. Guarantee & Liab. Ins. Co., supra), a prominent Houston-area attorney had advised counsel at one of the insurance companies that a Harris County jury would never find that the deceased was more than 50% at fault (thus barring recovery) after finding that the defendant was negligent. This anecdotal evidence (which should obviously be confirmed with other experienced attorneys) indicates that the probability that a jury will find that the deceased’s comparative fault exceeds 50% depends upon whether the jury finds that the defendant was negligent.

Of course, as a matter of sequence, the jury only reaches the question of comparative fault after finding that the defendants was negligent (since absent negligence, defendants win). But we are speaking here of statistical dependence, and therefore the point is that when the jury deliberates, the probability of how a jury decides the issue of comparative fault is heavily influenced by (i.e,. not statistically independent of) the finding of negligence (whereas the issue of comparative fault might be decided very differently if considered in complete isolation from the question of negligence).

This makes sense. Once a jury finds that a defendant was negligent, it means the jury believes that the defendant somehow acted improperly, and thus will be less inclined to deny a plaintiff any recovery (albeit, in less plaintiff-friendly counties, this linkage may be less of an issue). Couple this inclination with other evidence tending to show that plaintiff was less than 50% at fault, the likelihood of defendants getting off the hook based on comparative fault is slim.

The principle of conditional probabilities thus yields a second objection to any attempt to string together speculative probabilities as part of a decision tree analysis. Specifically, a decision on a defendant’s motion for summary judgment will necessarily be rendered well after a decision on any motion to dismiss. That earlier decision will often provide insight into the judge’s thinking about the case that will influence the probability of prevailing on a motion for summary judgment. Thus, it would likely be speculative to estimate the probability for prevailing on a motion for summary judgment without first reviewing the decision on an earlier motion to dismiss.

To be sure, as part of an early case assessment, a defendant might persuasively argue that it has independent grounds to prevail on both a motion to dismiss (certain key allegations are missing from the complaint) and a motion for summary judgment (certain material facts will definitely not be in dispute). In which case, it might be acceptable to multiple the probabilities of prevailing on both. But that is only because the defendant satisfied the two requirements necessary to apply the special form of the Multiplication Rule (i.e., P(A) x P(B) rather than P(B|A) x P(A)): an adequate evidentiary foundation and adequate proof of statistical independence.

In sum, to avoid “garbage in, garbage out,” users of decision trees need to properly apply the Multiplication Rule. If you think a particular decision tree misuses that rule, challenge the probabilities.

If you missed our June 23 webinar on decision tree analysis, you can download a replay here.

We also invite readers to join our Decision Tree Analysis group on LinkedIn.

The post Misuse of Probability in Decision Tree Analysis: Avoiding Garbage In, Garbage Out appeared first on Merge Mediation Group Blog.

At our June 23, 2021 webinar on decision tree analysis, we examined how to calculate the expected value (EV) of a lawsuit using a decision tree in connection with a mediation or settlement negotiations. We also discussed that once an EV is calculated, plaintiffs should subtract from EV the anticipated future costs of continuing to litigate (e.g., attorney and expert fees), while defendants should add anticipated future costs to the EV. We noted, however, that past, or sunk costs are irrelevant. Several attendees inquired into the basis for distinguishing between past and future costs. Let’s look at some hypotheticals.

Assume that during mediation of a commercial litigation, the mediator reaches a consensus with the parties on the structure of a decision tree showing the remaining material uncertainties to be resolved at trial with respect to liability and damages. Of course, both sides will almost certainly disagree concerning the probabilities of how these uncertainties will resolve.

Let’s say that using the agreed upon decision tree, the plaintiff concludes that the EV of the lawsuit is approximately $2M if the case were to go to trial. The plaintiff also anticipates it would spend another $300K on attorney and expert fees through trial. The plaintiff would then subtract $300K from the $2M to generate an adjusted EV of $1.7M (since it would cost plaintiff $300K to secure the $2M, leaving a net expected recovery of $1.7M).

Further assume that defendant calculates the EV a bit lower (say $1.8M), but anticipates it would spend another $400K in fees through trial. The defendant would add $400K to the $1.8M to generate an adjusted EV of $2.2M (since defendant would pay an additional $400K beyond the $1.8M for which it can expect to be liable to plaintiff after a trial).

Without adjusting EV for future costs there can be no settlement since plaintiff would not accept anything less than $2M while defendant would not pay anything more than $1.8M. However, adjusting the EV for future costs that are avoidable if the case settles — i.e., costs that neither party would have to pay if they settled — creates a bargaining zone of $500K within which the parties should settle with the help of the mediator (since the plaintiff should now be willing to settle for any amount over $1.7M, while the defendant should now be willing to settle for any amount below $2.2M).  That is, since any number between $1.7M and $2.2M represents a sure outcome that is worth more than the gamble that either party would take by going to trial, then unless either party elects to act in a risky manner (i.e., choose a gamble that is worth less than a sure outcome), the mediator should be able to settle this case.

But why only consider future avoidable costs? Why aren’t past costs (a/k/a “sunk” costs), also relevant to a decision tree analysis? The simple answer is that “sunk” costs are, by definition, not recoverable regardless of whether the parties decide to settle or continue litigating, and thus as a matter of simple math have zero impact on the decision about whether to settle or continue litigating. In contrast, future costs can be avoided if a party choses to settle, and thus (as per above) have an impact on the decision to settle (costs not paid) versus continuing to litigate (costs paid).

Let’s unpack that with the following additional hypothetical. A plaintiff spends $600K on attorney’s fees (which it cannot recover since there is no fee shifting), and then gets an offer to settle the case for $400K prior to trial. The plaintiff wants to reject the offer on the ground that it has already spent $600K on fees and won’t settle for less than $600K so it can at least break even.

Further assume, however, that a rigorous decision tree analysis of the value of the case indicates that the adjusted EV for the plaintiff is only $300K (e.g., the EV of the probabilities of how all the material uncertainties may resolve through trial is $325K, minus anticipated future costs of $25K).

So $400K is actually a good deal given the current value of the case. If the plaintiff accepts, its loss on the case will only be $200K ($400K sure recovery minus $600K fees). But if it rejects, its expected loss on the case is $300K ($300K EV of gamble minus $600K fees) — $100K greater than the loss from settling. In effect, because the past fees cannot be recovered regardless of the choice made, they cancel out on each side of the equation, and the plaintiff is left with $400K settle > $300K litigate. So it’s economically rational to ignore sunk costs, accept the offer, cut losses, and stop throwing good money after bad (or to quote other maxims — “let bygones be bygones;” “don’t cry over spilt milk,” and “it’s water under the bridge.”).

Of course, we don’t know what the outcome of continuing to litigate would be. The plaintiff could be surprised and recover far more than $400K even after accounting for future costs. But the plaintiff could also recover $0. That’s the whole point of a decision tree analysis — decision making under conditions of uncertainty that takes into account the probabilities of all of the potential outcomes of taking the gamble, and calculates the average of all those possible outcomes (in this case, $300K after adjusting for costs). That is to say, neither lawyers nor their clients are prophets who can predict the future; the best we can do is undertake a disciplined risk analysis that weighs the probabilities of all the possible outcomes and see what is shows.

As a result, if the plaintiff rejects the $400K offer and continues litigating, it’s acting in a “risky” manner — i.e., rejecting a sure outcome ($400K) worth more than the gamble ($300K) just because it’s annoyed at having already spent $600K on fees on what turned out to be a bad case. That’s an emotional response, not a rational response; a psychological trap referred to as the “sunk cost” fallacy that causes bad decision making.

Decision tree analysis is a risk-neutral, objective method designed to remove emotion like that from the analysis and facilitate good decision making by showing a party when it’s economically rational to settle at a certain point in time (of course, we discussed at the webinar that certain (typically “wealthy”) parties may decide to act in a “risky” manner and pursue gambles worth less than sure outcomes for completely legitimate reasons, but doing so solely because a party is annoyed at all the money it has already spent on legal fees is not a legitimate reason).

In closing, to accentuate the point, let’s consider a common “everyday” hypothetical. You pay $100 for movie tickets, decide the movie is horrible, but force yourself (and your family) to watch until the end because you already paid for the tickets, and there are no refunds. But that’s irrational. Instead, the logical choice would be to leave early and engage in a family activity that is more enjoyable than suffering through a terrible movie. The idea is to cut your losses once it’s apparent the value isn’t what you expected.

Same thing with sunk costs. A litigant involved in a case where settling is now clearly worth more than the gamble of continuing to litigate should logically choose to cut losses rather than increasing them (absent other legitimate considerations that logically support “risky” behavior).

We hope the above explanation is helpful; we encourage comments below.

For those who missed the June 23 webinar on decision tree analysis, click here to register to watch a recorded replay (PDF of slides available upon request).

We also invite readers to join our Decision Tree Analysis group on LinkedIn.

The post Why Sunk Costs Are Irrelevant to Decision Tree Analysis in Mediation appeared first on Merge Mediation Group Blog.

An application for NYCLE-accreditation for one (1) credit in the area of Professional Practice is currently pending.

The presenter is Joshua E. Fruchter, Esq., a mediator and litigator with over twenty five years of experience settling disputes in litigation and family business environments.

Among other topics, attendees will learn:

• The difference between qualitative vs. quantitative approaches for valuing a lawsuit, and why the former creates confusion and the latter provides clarity.
• How to value a lawsuit using decision tree analysis by assigning probabilities, calculating expected values, and incorporating other variables such as litigation costs and risk aversion.
• How to apply decision tree analysis to a reported wrongful death case.

Click here for further details and to register.

We hope you can join us.

The post Free Webinar for Litigators and Mediators: June 23: Using Decision Tree Analysis To Value Lawsuits and Negotiate Settlements appeared first on Merge Mediation Group Blog.

The webinar is NYCLE-accredited for one (1) credit in the area of Professional Practice.

The presenter is Joshua E. Fruchter, Esq., a mediator and litigator with over twenty five years of experience settling disputes in litigation and family business environments.

Among other topics, Josh will be discussing:

• key wealth transfer trends that will increase the incidence of estate planning disputes in coming years.
• ethical pitfalls attorneys need to avoid when disputes begin brewing, such as simultaneously representing different family members with adverse interests.
• strategies to prevent estate planning disputes from escalating into litigation using real-life case studies.

Click here for further details and to register.

We hope you can join us.

The post NYCLE-Accredited Webinar: November 17: How Mediation Can Add Value to the Estate Planning Process appeared first on Merge Mediation Group Blog.

Readers have asked us to consolidate these psychological principles into a single post and create a glossary of sorts. Below is a list of six key psychological principles that we have previously discussed. Obviously, the list is not exhaustive and we welcome comments from readers highlighting additional concepts that we have not mentioned.

As you review these principles, bear in mind that they do not exist in isolation; all may be operating simultaneously to a greater or lesser degree in a given mediation. Capitalizing on them to drive resolution is more art than science. A skilled mediator will note their presence or absence, and orchestrate negotiations accordingly to bring the mediation to a successful conclusion.

#1: Confirmation Bias 

As defined by the Farnam Street website, confirmation bias is the “tendency to cherry-pick information that confirms our existing beliefs or ideas.” In other words, after making a decision or reaching a conclusion in which we have a vested interest, we tend to interpret new evidence in a manner that validates our choice, while distinguishing or ignoring facts that contradict or undermine it. The upshot is that confirmation bias can cloud our judgment, and lead us to continue pursuing erroneous courses of action in the face of evidence that our position is mistaken.

Research indicates that attorneys are especially prone to confirmation bias. This finding makes sense since attorneys are trained to zealously advocate for their clients’ position. However, while zealous advocacy is commendable, the same research shows that confirmation bias can lead attorneys to overrate strengths and underrate weaknesses in their cases, and as a result, reject reasonable settlement offers they should accept.

How should mediators deal with confirmation bias? When caucusing, a mediator can play devil’s advocate by pointing out the weaknesses in each side’s case, and the strengths of the adversary’s positions. Originating from a neutral without a stake in the outcome, a mediator’s evaluations come across as more credible and thus may persuade parties to rethink their positions.

Because confirmation bias is a strong tendency, however, it is important for mediators to remain patient and not give up prematurely. As mediator Stephen Hochman writes, “unrealistic expectations must be lowered gradually.” Thus, confirmation bias is best combated by breaking down a dispute into components and reaching agreement on a series of small points sequentially.

If unable to fully bridge the gap between two parties committed to certain positions, a mediator might resort to a mediator’s proposal, or propose a “contingent contract” that allows parties to maintain their positions while hedging their bets against an adverse outcome.

#2: Endowment Effects

The “endowment effect” refers to our tendency to overvalue objects that we own. This psychological phenomenon was demonstrated empirically by Professors Daniel Kahneman, Jack Knetsch and Richard Thaler in their famous “mug” experiment. Half the participants were given a free mug, while the remaining participants were not. The participants who received a mug were then asked how much they would request to sell the mug, while the participants who did not receive a mug were asked how much they would be willing to pay to buy one.

The mug owners placed a significantly higher value on the mugs than the participants who did not own a mug, and were only willing to sell their mugs for a median price of $7.12, while the buyers were only willing to pay a mediation price of $2.87.

In another experiment, participants who received a chocolate bar were generally unwilling to trade it for a coffee mug of equal value, whereas participants given a coffee mug were generally unwilling to trade it for the chocolate bar.

An application of the endowment effect in retail sales is the famous “test drive” offered by many car dealerships. Giving a potential buyer the opportunity to “test drive” a new car creates a feeling of ownership, which makes the potential buyer more willing to buy the car after the “test drive.” Creating a feeling of “ownership” also motivates clothing retailers to allow prospective purchasers to try on outfits that they like in the store.

The endowment effect operates in mediations. Most obviously, as the “owner” of a claim, the plaintiff will always have built-in tendency to overvalue the claim relative to the defendant who is effectively being asked to “buy” the claim with a payment. A mediator who is not constrained by such biases can serve as an agent of reality by employing a tool such as decision tree analysis to objectively assess the “market” value of the claim.

As decision tree pioneer Marc Victor has suggested, a mediator best fulfills that role when — rather than asking the parties to exchange numbers from which they may be reluctant to move due to endowment effects — he or she instead engages the parties in a discussion of the relevant legal and factual uncertainties in the case, the probabilities of their resolution, and the range of potential damages if liability is found. Such discussions are likely to produce a more objective “market” value for the claim that can then provide the basis for further negotiation (such as with bracketing around a reasonable range).

The endowment effect also means that, in general, it is always going to be easier for a mediator to persuade a party to abandon a request for something new they want to acquire rather than to surrender something they already own (or “feel” they own). As an example, in estate planning disputes, if there are siblings who have been involved in running a family business, and other siblings who have not been involved, a solution that lets the former acquire full ownership of the business in exchange for surrendering claims to other family assets outside the business is going to be an easier sell.

Similarly, in a divorce mediation, proposing that each spouse keep assets with respect to which they have “feelings” of ownership in exchange for surrendering claims to assets with respect to which they do not, is more likely to succeed than compromises that ask spouses to surrender assets they “feel” they own.

Finally, in the transactional mediation context, Professor Scott Peppet argues that endowment effects make lawyers more resistant to modifying default contractual provisions that they have drafted and reused multiple times even in transactions where those provisions are not a good fit. Mediators not subject to such biases can break contracting impasses in the transactional context by proposing new customized provisions that better address the nuances of the deal at hand.

#3: Cognitive Dissonance 

Cognitive dissonance is the mental discomfort we feel when our conduct contradicts our beliefs. To eliminate the tension, we can either change our conduct or change our beliefs.

For example, a smoker may subconsciously feel torn between a behavior (smoking) and a belief (smoking causes lung cancer). The smoker can easily eliminate this discomfort by quitting smoking. But since it is often difficult for people to abandon longstanding behaviors that give them pleasure, a smoker may elect to change his belief (e.g., by arguing that the evidence linking smoking to cancer is biased or flawed).

How can a mediator capitalize on cognitive dissonance during mediation? When parties enter into mediation they often perceive their adversaries negatively — they’ll use adjectives such as stubborn, unreasonable, and unrealistic. The mediator’s job is to change those beliefs by encouraging conduct that is inconsistent with those perceptions.

One tool for changing perceptions is bracketing, which involves asking the parties to make reciprocal moves from their original positions. For example, a mediator might ask the defendant, “if I can persuade the plaintiff to come down to $2 million, would you be willing to come up to $500,000?” The objective is to pin down a mutually agreeable settlement range within which the parties can continue negotiating.

Because making reciprocal moves is inconsistent with being stubborn and unrealistic, one of the values of bracketing is that it helps each side to start viewing its adversary as flexible and serious about settling the case. In other words, when the conduct of another person is inconsistent with our beliefs about that person, the inconsistency can cause us to reassess those beliefs.

Making concessions also generates goodwill because of the Ben Franklin effect, a phenomenon attributed to cognitive dissonance which maintains that performing favors for someone whom you dislike increases your positive feelings towards that person (because typically you only do favors for people you like). As Franklin wrote in his autobiography concerning how he turned a rival legislator into a friend:

Having heard that he had in his library a certain very scarce and curious book, I wrote a note to him, expressing my desire of perusing that book, and requesting he would do me the favour of lending it to me for a few days. He sent it immediately, and I return’d it in about a week with another note, expressing strongly my sense of the favour. When we next met in the House, he spoke to me (which he had never done before), and with great civility; and he ever after manifested a readiness to serve me on all occasions, so that we became great friends, and our friendship continued to his death.

The Ben Franklin effect also signals the importance of promoting civility during joint sessions (because we devalue people to whom we speak rudely, and think highly of people to whom we speak courteously).

#4: Reciprocation Bias

Reciprocation bias is the obligation people feel to return favors. In other words, it is human nature to feel that a person who does a favor for me is entitled to a return action.

Mediators can capitalize on reciprocation bias during mediation by encouraging small reciprocal concessions (such as bracketing, as described above). That is, to the extent one party retreats slightly from a position, the other side will feel obligated to reciprocate. In turn, a reciprocal concession encourages further compromise by the other party. This is how negotiations build steam. 

#5: Reactive Devaluation

Reactive devaluation represents the tendency to dismiss an objectively fair proposal merely because it was suggested by an adversary. As Professor Scott Peppet explains:

Imagine that a disputant is considering two possible agreements that would resolve her dispute: Solution A and Solution B. If the disputant knows nothing about the origin of the two solutions, and does not know which solution her opponent favors, she would, all things considered, prefer Solution A. It meets her interests more completely than Solution B. Now imagine that the disputant discovers that Solution A is in fact the offer proposed by her opponent. Research shows that this information about the offer’s origin will often taint a disputant’s evaluation of the merits of the two proposals. She may no longer prefer Solution A, merely because the other side proposed it.

Mediators can neutralize the effects of “reactive devaluation” by presenting a proposal from one side to the other party, but without telling the other party that the proposal originated with its adversary. Instead, the mediator should present the proposal as his or her own idea to increase the likelihood of its acceptance.

#6: Hanlon’s Razor

There is a tendency to attribute to malice conduct that might just as plausibly be explained by more benign causes. As an example, Professor Scott Peppet cites a person who cuts you off in traffic. Studies show you are more likely to think “they are driving that way because they are inconsiderate” rather than “they may be driving that way because they are late to their child’s medical appointment.” Hanlon’s razor encourages us to give people the benefit of the doubt and assume more charitable explanations for conduct we find problematic.

Mediators should be attuned to parties assigning malicious motives to their adversaries, especially in mediations where there is a strong emotional component such as in workplace, family business and estate planning disputes. In response, mediators should encourage parties to see the dispute from their adversary’s perspective, and consider whether there are more innocent explanations for conduct they deemed objectionable. Suggesting alternative narratives helps promote reconciliation.

The post Six Key Psychological Principles at Play in Mediations appeared first on Merge Mediation Group Blog.

About a year ago, a colleague introduced me to the world of “cooperative” board games, which stress cooperation over competition. There are no individual losers or winners. Instead, players work together as a group to achieve the objective of the game. If the group succeeds in attaining their common goal, everyone wins, and if the group fails, everyone loses.

I was hooked, and discovered there are cooperative games for all ages. For my youngest daughter, I purchased The Dinosaur Escape Game and Race to the Treasure. And to play with my twenty five year-old daughter and son-in-law during a visit, I bought Pandemic — a cooperative game in which players are members of a team tasked with preventing outbreaks and developing cures before several deadly diseases wipe out humanity.

Given current events, you can now appreciate why I cited Oscar Wilde’s quote at the outset of this blog post. But as life imitates art, art — or in this case, cooperative games — can also teach us important lessons for life, especially in times of crisis.

Pandemic is a complicated game with a very complex set of rules. It took all three of us quite some time to figure it out. Each player assumes a role on the team, and each role has special capabilities. For example, in one game I served as a Quarantine Specialist, which gave me the ability to prevent outbreaks in the city in which I was located, and all cities connected to that city.

During a turn, each player can take certain cooperative actions such as driving or flying to different cities, building a research station, or sharing knowledge. Players also draw cards, which they need to deploy strategically in consultation with other team members.

As should now be evident, succeeding in Pandemic requires careful coordination between players. Easier said than done, and we lost the first game. But we gradually got the hang of things, and collaborated successfully to win the second game by discovering cures to all four diseases in the nick of time.

Playing Pandemic was an enjoyable, but also instructive experience. As kids, most of us probably grew up playing only competitive games in which there were always winners and losers. Unfortunately, for many of us, this paradigm carried over into our adult lives, and we are predisposed to see every confrontation through a competitive lens — a zero sum game in which your gain is my loss.

There is a name for that type of thinking — zero sum bias — which describes the human tendency to perceive situations as zero-sum, even when that is not the case. Such thinking often arises in resource-scarce environments, where zero sum bias reduces people’s willingness to assist others whom they perceive as competing with them for the same resources. Cooperative games seek to change that dynamic.

Fast forward to the present, and the world is confronting a global epidemic. I was speaking with my daughter recently, and we were astonished at how what had just been a game last year was now reality.

Yes, Pandemic is certainly no longer just a game. Lives are at stake. Certain resources are scarce. People’s livelihoods and savings are on the line. So what is required of each of us? I submit it is to resist our inclination to compete, and instead embrace cooperation. To realize that we are all in this together, and though we all fear what the future holds, to collaborate instead of confronting; to share instead of hoarding.

Cynics who only see the worst in humanity will argue this is a pipe dream, and predict that individuals will soon start looking out only for themselves and their families. Indeed, in a 2011 film about a global epidemic, Contagion, there are several scenes in which a mob mentality prevails as desperate residents fight over food and medicines.

But we are better than that. And a scene I witnessed yesterday at a local Walmart gave me reason for hope. A woman and her daughter had apparently found the last two bottles of anti-bacterial soap available in the store. While waiting in line, they were approached by another woman who asked them to direct her to the aisle where the bottles were located. They informed her that there were no more left, but offered to let her take one of the bottles they had planned to purchase. She was extremely grateful. A small gesture, but it proves that while certain physical resources are scarce, there’s no reason we can’t have an abundance of kindness. To paraphrase Viktor Frankl in Man’s Search for Meaning:

Even under the most difficult circumstances, any man can still decide what shall become of him – mentally and spiritually. Whether he will remain brave, dignifi­ed and unselfi­sh. Or in the bitter fi­ght for self-preservation, forget his human dignity and become no more than an animal.

There is a Talmudic dictum, “either friendship or death.” It’s a dramatic statement, but an eternal truth. When we compete, even the winner is a loser because in vanquishing his opponent, he has lost a bit of his humanity. But when we cooperate, and invest in fellowship, we preserve our dignity, and gain much more than we gave up.

There are undoubtedly some difficult times ahead. But if we can all maintain a mindset of cooperation and collaboration, we will find that the crisis brought out the best in each of us.

The post Coronavirus and Collaboration: Cooperating in a Time of Crisis appeared first on Merge Mediation Group Blog.

The plaintiff (Mr. Long) had purchased a property insurance policy from American Family Mutual Insurance Company that provided $224,100 for dwelling coverage and $224,100 for personal property coverage. After a fire caused significant damage to Mr. Long’s home and personal property, he made a claim for the policy limits. American Family tendered payment for property damage to the house, but denied coverage for Mr. Long’s personal property on the basis that Mr. Long lied on his policy application by failing to disclose that he had a 20-year-old conviction for marijuana possession. American Family also asserted other policy exclusions. Mr. Long sued for breach of contract.

The parties scheduled a mediation, prior to which the mediator reminded them that attendees must have settlement authority, as per Local Rule 16.3 for the District of Kansas, which provides in relevant part:

Attendance by a party or its representative with settlement authority at the mediation is mandatory, unless the court orders otherwise. The purpose of this requirement is to have the party or representative who can settle the case present at the mediation . . . The parties’ attorney(s) responsible for resolution of the case must also be present.

The same rule authorizes the court to sanction a party that does not comply with these requirements.

Mr. Long personally attended the mediation with his counsel, but American Family was represented solely by its attorney. Mr. Long demanded $320,000, but defense counsel only had authority to settle for $20,000. After the mediation concluded, Mr. Long moved for sanctions and the scheduling of a second mediation on the ground that American Family’s counsel lacked settlement authority. American Family responded that its attorney had full settlement authority because $20,000 represented significantly more than the value of the case in light of its various defenses.

The court cited a prior Kansas District Court decision holding that a person does not have settlement authority when he has to pick up the phone to call someone else to find out whether he can go any higher or lower in response to a demand at the mediation. Instead, a person with settlement authority is someone who has the ability to make settlement decisions at a mediation without first having to check with someone else.

The court further held that having settlement authority does not necessarily mean that an attendee must have authority to meet its adversary’s demand. The court,  however, then qualified that principle:

[A]uthority to meet the other party’s demand could be a relevant factor in an appropriate case. But a plaintiff seeking sanctions on the basis of the party representative having inadequate settlement authority must, at a minimum, demonstrate that the plaintiff’s settlement demand was reasonable and that the defendant’s settlement offer was unreasonable. Here, Mr. Long has not presented any evidence suggesting that his $320,000 demand was reasonable or that American Family’s $20,000 offer was unreasonable. (emphasis in original).

Ultimately, however, the court awarded sanctions and ordered a second mediation because it found that American Family’s participation in the mediation solely through its attorney did not satisfy the Local Rule. It noted that the purpose of mediation is to engage both the parties and their attorneys and that delegating full authority to the attorney frustrates this purpose by insulating the party from the mediator’s counsel and advice.

The standard embraced by the court seems sensible in most respects. The notion that settlement authority means having the power to make a decision without first having to check with someone else is reasonable (although parties are certainly free to agree with the mediator that individuals with full authority will be available by telephone). See Dvorak v. Shibata, 123 F.R.D. 608, 609 (D. Neb. 1988) (dynamic of mediation is lost “if the only person with authority to negotiate is located away from the courthouse and can be reached only by telephone.”).

It is also makes sense to permit a party to limit the settlement authority of its representative at a particular mediation session to a specific bottom line. See G. Heileman Brewing Co. v. Joseph Oat Corp., 871 F.2d 648, 653 (7th Cir. 1989) (“In our view, “authority to settle,” when used in the context of this case, means that the “corporate representative” attending the pretrial conference was required to hold a position within the corporate entity allowing him to speak definitively and to commit the corporation to a particular position in the litigation. We do not view “authority to settle” as a requirement that corporate representatives must come to court willing to settle on someone else’s terms, but only that they come to court in order to consider the possibility of settlement.”).

But the court’s proposition that an attendee may be deemed to have insufficient settlement authority because it sticks to a bottom line that the court finds unreasonable seems highly dubious. A party may take certain positions at a mediation for many different reasons; indeed, taking seemingly “unreasonable” positions may be part of its negotiating strategy (of course, certain bottom lines – like offering $500 in a multi-million dollar case – might properly be deemed bad faith by any measure).

In sum, it seems, so long as the attendees from each side have the authority to reject or accept demands within a predetermined range without having to pick up the phone (unless otherwise agreed between the parties and the mediator), a court should not involve itself in evaluating the reasonableness of the positions taken at the mediation. Because otherwise it is, in effect, passing judgment on the parties’ negotiating tactics.

We invite readers to share their thoughts.

For an insightful discussion of further authorities on this issue and helpful practice pointers, see “Mediation and the Thorny Issue of Settlement Authority” on Law360 (subscription required).

The post What Does it Mean to Have “Settlement Authority” at a Mediation? appeared first on Merge Mediation Group Blog.

If the initial complaint itself does not disclose grounds for removal, 28 U.S.C § 1446(b)(3) provides that a case may still become removable upon disclosure “through service or otherwise” of grounds for removal in a subsequent pleading, motion or “other paper from which it may first be ascertained that the case is one which is or has become removable.” Upon disclosure of grounds for removal, a defendant has thirty days to seek removal; after the 30-day window closes, a request to remove will be denied as untimely.

The question thus arises — if the plaintiff and defendant engage in mediation after commencement of the class action, and plaintiff provides confidential materials to defendant during the mediation that indicate the case meets the requirements for removal, does the 30-day clock start ticking? That is, can confidential mediation materials be used to establish removability under federal law?

In a recent case, Ali v. Setton Pistachio of Terra Bella, Inc., 2019 WL 6112772 (E.D. Cal. Nov. 18, 2019), the plaintiff commenced a class action against the defendant in California state court on April 27, 2016, alleging wage violations under California state law. On July 12, 2019, defendant filed a notice of removal to California federal court under CAFA. Plaintiff alleged the notice was untimely because a damages model revealing that the amount in controversy exceeded $5 million was disclosed to the defendant during a mediation on June 28, 2017. Defendant denied having ever received the damages model.

The court noted that the term “other paper” in 28 U.S.C § 1446(b)(3) had been defined broadly to include, among other forms of written disclosure, a settlement letter sent in advance of a mediation. Therefore, assuming a written damages model alleging damages in excess of $5 million had been provided to the defendant during the mediation, it would have constituted notice of grounds for removal (the court later found, however, that there was a dispute as to whether the plaintiff had ever actually provided the damages model to the defendant).

But wait a second. Aren’t documents disclosed during mediation supposed to remain strictly confidential and protected against disclosure in a litigation? This argument was apparently not raised in Ali, but was raised in an earlier 2015 California federal court decision, Tetravue, Inc. v. St. Paul Fire & Marine Ins. Co., 2015 WL 13828630 (S.D. Cal. Apr. 8, 2015).

Tetravue was not a class action, but filed as a state lawsuit seeking to enforce an insurer’s defense obligation. The insurer sought removal based on a confidential mediation brief demonstrating that the amount in controversy requirement ($75,000 in diversity cases) was satisfied. Plaintiffs sought remand on the ground that defendant could not rely on a confidential mediation brief to establish removability because doing so violated Section 1119 of the California Evidence Code (which protects written mediation-related documents from disclosure in civil litigation).

The court ruled that the permissibility of using the confidential mediation brief to establish the amount in controversy was governed by federal law (which establishes the requirements for removal), and not state law privileges (which only apply with respect to elements of substantive claims and defenses governed by state law). Since the confidential mediation brief was admissible under federal law, it could be used to establish the amount in controversy for purposes of seeking removal.

The ruling in Tetravue relied in part on the Ninth Circuit’s decision in Babasa v. LensCrafters, Inc., 498 F.3d 972 (9th Cir. 2007), which held that the plaintiff’s pre-mediation settlement letter constituted disclosure of grounds for removal.

In Babasa, however, the Ninth Circuit noted that the defendant had failed to argue that the letter was protected by a federal mediation privilege, or that the Ninth Circuit should incorporate the California mediation privilege into the federal common law of privileges. Therefore, it did not consider whether a federal mediation privilege exists to bar use of confidential mediation materials for purposes of demonstrating removability, or whether it may be appropriate in some cases to defer to state law evidentiary privileges out of comity and respect for state policies.

In a later case involving enforcement of a settlement reached during mediation, the Ninth Circuit held that the federal law of privilege applies to federal claims, but did not address the existence or scope of a federal mediation privilege. See In re TFT-LCD (Flat Panel) Antitrust Litig., 835 F.3d 1155 (9th Cir. 2016). But in Circuits like the Second Circuit that have recognized a federal mediation privilege (see In re Teligent, Inc., 640 F.3d 53 (2d Cir. 2011)), a strong argument can be made that confidential mediation materials may not be used to establish grounds for removability, and thus (in a class action) do not start the 30-day clock ticking under CAFA.

The post Can Confidential Mediation Materials Start the 30-Day Clock Ticking for Removability Under the Class Action Fairness Act? appeared first on Merge Mediation Group Blog.

Our Psychological Attachment to Objects We Own

There is a ritual law that prohibits carrying objects in a public domain on the Sabbath (readers involved with First Amendment litigation may be familiar with this law from cases addressing the construction of an eruv, or symbolic enclosure, around neighborhoods to enable residents to carry objects outside their homes on the Sabbath; see, e.g., Tenafly Eruv Ass’n, Inc. v. Borough of Tenafly, 309 F.3d 144 (3d Cir. 2002)).

In connection with the above law, the Talmudic Sages developed rules to address situations where individuals carrying an object in a public domain will not have sufficient time to return home with the object before the Sabbath commences at sundown. Interestingly, the relevant rules are more lenient with respect to objects that an individual already owns than with respect to lost objects that an individual has found.

The medieval commentator, Rabbi Shlomo Yitzchaki (more commonly known by his acronym, Rashi) suggests that the greater leniency with respect to owned (versus found) objects is based on human nature. Specifically, a person will be more psychologically attached to an object that he acquired (using money that he earned) than an object that he found fortuitously through a stroke of good fortune. This greater psychological attachment will, in turn, make individuals more inclined to violate the Sabbath to bring an owned object home rather than abandon it in a public domain if they cannot get home in time before the Sabbath commences. Recognizing this, the Talmudic Sages legislated certain leniencies for individuals carrying owned objects that they did not authorize for individuals carrying found objects.

The Endowment Effect

Rashi’s insight that individuals are more psychologically attached to objects that they own finds a modern counterpart in the “endowment effect,” a principle referring to our tendency to overvalue objects that we own.

This psychological phenomenon was demonstrated empirically by Professors Daniel Kahneman, Jack Knetsch and Richard Thaler in their famous “mug” experiment. Half the participants were given a free mug, while the remaining participants were not. The participants who received a mug were then asked how much they would request to sell the mug, while the participants who did not receive a mug were asked how much they would be willing to pay to buy one.

The mug owners placed a significantly higher value on the mugs than the participants who did not own a mug, and were only willing to sell their mugs for a median price of $7.12, while the buyers were only willing to pay a mediation price of $2.87.

In another experiment, participants who received a chocolate bar were generally unwilling to trade it for a coffee mug of equal value, whereas participants given a coffee mug were generally unwilling to trade it for the chocolate bar.

An application of the endowment effect in retail sales is the famous “test drive” offered by many car dealerships. Giving a potential buyer the opportunity to “test drive” a new car creates a feeling of ownership, which makes the potential buyer more willing to buy the car after the “test drive.” Creating a feeling of “ownership” also motivates clothing retailers to allow prospective purchasers to try on outfits that they like in the store.

Endowment Effects in Mediation 

The endowment effect operates in mediations as well. Most obviously, as the “owner” of a claim, the plaintiff will always have built-in tendency to overvalue the claim relative to the defendant who is effectively being asked to “buy” the claim with a payment. A mediator who is not constrained by such biases can serve as an agent of reality by employing a tool such as decision tree analysis to objectively assess the “market” value of the claim.

As decision tree pioneer Marc Victor has suggested, a mediator best fulfills that role when — rather than asking the parties to exchange numbers from which they may be reluctant to move due to endowment effects — he or she instead engages the parties in a discussion of the relevant legal and factual uncertainties in the case, the probabilities of their resolution, and the range of potential damages if liability is found. Such discussions are likely to produce a more objective “market” value for the claim that can then provide the basis for further negotiation (such as with bracketing around a reasonable range).

By analogy, in the coffee mug experiment, a mediator might break the impasse between the sellers and the buyers by referencing the prices of similar coffee mugs online.

The endowment effect also means that, in general, it is always going to be easier for a mediator to persuade a party to abandon a request for something new they want to acquire rather than to surrender something they already own (or “feel” they own). As an example, in estate planning disputes, if there are siblings who have been involved in running a family business, and other siblings who have not been involved, a solution that lets the former acquire full ownership of the business in exchange for surrendering claims to other family assets outside the business is going to be an easier sell.

Similarly, in a divorce mediation, proposing that each spouse keep assets with respect to which they have “feelings” of ownership in exchange for surrendering claims to assets with respect to which they do not, is more likely to succeed than compromises that ask spouses to surrender assets they “feel” they own.

Finally, in the transactional mediation context, Professor Scott Peppet argues that endowment effects make lawyers more resistant to modifying default contractual provisions that they have drafted and reused multiple times even in transactions where those provisions are not a good fit. Mediators not subject to such biases can break contracting impasses in the transactional context by proposing new customized provisions that better address the nuances of the deal at hand.

We invite readers to offer other illustrations of endowment effects at play in mediation.

The post Mediation Lessons from the Talmud: The Endowment Effect and Its Impact on Settlement Negotiations appeared first on Merge Mediation Group Blog.