In my first article on this topic, I stressed the importance of the lawyer-as-doctor role when it comes to working with the mediator and the client to diagnose the client’s case. After a clinical, medical-grade assessment of the patient (the case), the client has the best information possible to make an informed decision about whether to settle the case and at what value. This is the first of what I consider to be two essential tools for a successful settlement analysis. The second, after we learn to think like a doctor, is to learn to think like a robot.

Unlike us, robots do not carry around those pesky emotions. And, unlike robots, there is no such thing as a human decision that is completely separated from emotion. There is an emotional element hiding behind the smallest of decisions. It is why we take a few seconds lingering in front of our dresser to decide which pair of socks we “feel” like putting on that morning, or why we stand for twenty minutes in Best Buy staring at two virtually identical television screens side-by-side trying to figure out whether to spend the extra $30 on the fancier name brand, despite the two TVs being essentially the same exact thing. Robots do not suffer like we do. They would never stand in that Best Buy aisle for twenty minutes. Instead, they would roll into the store, take a look at the two televisions, and be wheeling out the TV that costs $30 less in a nanosecond, not just because they never saw the commercial for the fancier sounding brand, but if they did, they simply did not care about it, because the two TVs have the same features that do the same thing. The presumption underlying this illustration is that this robot is logical and understands how money works—that it is better to keep $30 that does not have to be spent versus spending $30 for illogical reasons—in this case because a brand makes someone “feel” a certain way. This leads to a concept I introduce litigants and counsel to at the outset of every mediation, which I like to call “robot math.”

On the heels of explaining what mediation and lawyers have to do with doctors, I ask litigants and their counsel to imagine that we assign a robot to solve the following problem, with the sole directive (aside from the first law of robotics to refrain from harming humans) being to net as much money as possible:

You, robot, are a plaintiff suing a defendant. Assume that you have a 100% chance of winning the lawsuit. Assume that the most you are entitled to, based on a 100% win, is $14.00. Your attorney tells you that the cost to get the case to a win will be $11.00, and that in this case, there is no legal avenue to recover your attorneys’ fees. If the defendant offers you $4.00 today in exchange for your dropping the case and a full release, what will you do?

Any robot will instantly run the computation and say: “Take the $4.00.” Why? Because $4.00 now is $1.00 more than the $3.00 the robot will otherwise net if the robot were to take the case all the way to a win (and that’s before taking into account that a $3.00 award a few years down the line after a trial is worth less then than it would be today). It is a simple illustration designed to strip this aspect of a settlement analysis of its complexity—Even a scenario where there is a 100% chance of a win (which of course doesn’t exist) is not as good as settling the case if the net financial outcome is better through a settlement than it would be through a win. Of course, most times, the robot is free to test the waters and see whether more than $4.00 might be on the table, but the robot knows that every dollar over $3.00 makes the settlement worth that much more than the value of an actual win. So, if it came down to taking $4.00 or carrying on the fight from the robot’s perspective, the math compels the decision to settle.

The robot math also works from the direction of the defense. To the robot defendant, I would offer the following instruction: Imagine you did nothing wrong, but you are being sued anyway. Imagine you have a 100% chance of ultimately winning (again, a non-existent scenario), but your lawyer says it will cost you $24.00 to ultimately convince the court to throw the case out and you cannot recover your attorneys’ fees. You have been told the plaintiff will go away if you pay $18.00 today. For the robot defendant, there is no decision to make. Pay the $18.00 and call it a day, and the robot will have “earned” the $6.00 the robot would otherwise have spent to defend the case to a win. Another term for this scenario is paying what is called nuisance value to end a case—where the cost of a settlement equals less than the cost of defending the case to a win.

Most of you reading this would likely initially react by thinking, particularly from the robot defendant’s perspective, that such an outcome is not fair. You would be right. It is not. But it is economical. And like any other business-making decision, if the factors giving rise to the decision are not broken down analytically and unemotionally, then you are far more likely to make a bad decision (one with ultimately greater adverse consequences) than the decision that logic, the data, and the math tell you that you need to make, even if at the time making the logical, data-based decision “feels” unfair.

To that point, consider that in most cases having financial implications, the client/decisionmaker is often acting as a fiduciary—either for a company, or, in the case of an individual—for themselves. In either instance, the obligation one owes to one’s company, or oneself, is to do everything reasonably and legally possible to minimize financial losses and maximize and preserve financial gains. In the case of a business owner, if one allows fairness, or pride, or principle, or revenge, or their sense of justice, to move one to make a decision in a manner that runs contrary to that fiduciary duty—to reject a logical economic settlement because it feels unfair—one must have a legally valid basis to disregard that duty. Otherwise, a company owner could be personally on the hook for making an economic decision against the best interests of the company. In the case of an individual eschewing the best net economic outcome for themselves in the name of catering to one of those emotions (for example, refusing to settle based on pride or because the other guy will get a windfall), well, there is no other way to put it than they are just hurting themselves—by literally, and unnecessarily, adding economic insult to whatever was their injury that got them into litigation in the first place. That would be a particularly unfair ending.

Of course, there are instances where non-financial considerations rightfully militate against taking the “logical” robot-math-based outcome. For example, an employer may not want to pay a claim to an employee who brings a lawsuit, even if for nuisance value, because that will signal to other employees that suing will result in a fast payout. Or, there may be business reasons to dig in on a lawsuit if it means dissuading a competitor from trying to engage in future repeat litigations.

In that respect, I will always remind the parties and their counsel that they are completely free to disregard the “medical” diagnosis of their case and/ or the robot math that we ran to help them understand their likely net economic outcomes. Once the clients have employed these analyses, it is their decision. Just as a patient can turn down a medication that is proven to resolve a medical condition in favor of taking herbal tea, a litigant can turn away from the mediator’s and their lawyer’s (“doctor’s”) honest assessment of a case or reject the results of a robot math exercise and choose not to settle. We can only lead them to the proverbial water.

But to help their decision making along, what I frequently also advise the parties to keep front-of-mind when they mediate is what is in their own best self-interest? Most of the time, when we have helped the clients to walk a few steps in the shoes of doctors and robots in analyzing their case, the clients come to realize that what is in their own self-interest is aligned with what the doctor and robot analyses are telling them. Ultimately, what these doctor and robot concepts boil down to is a user-friendly way to help to walk the client through a cost-benefit analysis—to help the client understand (with the mediator and lawyer working as co-practitioners) that their case has these strengths and these weaknesses, that the odds of winning are X or Y, and that the costs of the fight are Z. When you plug in these data points, you can realistically come up with a settlement value, net of costs and properly accounting for case risks, so that the client can make the best decision about what a case is worth and whether to settle.

The beauty of utilizing the doctor/ robot concepts is that employing them gets cases to settlement, because the exercise necessarily keeps everyone tethered to reality. No one is going to be able to credibly take a settlement position that is not supported by the data, the odds, and the actual likely value of the case net of costs, because everyone will have had the benefit of objectively diagnosing the case and figuring out its net value. When we employ these concepts, the case is almost always going to settle because the clients come to understand and to recognize when the outcome in settlement will likely present a better alternative than litigating to the end—which is usually the case.

I have found that when we start off the mediation by offering clients and counsel these conceptual lenses through which to view the day, everyone tends to adopt these metaphors as quick shorthand references throughout the day (what would a robot do now?) which in turn helps keep the focus on objectively assessing and valuing the case, for all parties’ own self-interests. Feel free to give them a try. I hope they prove useful in your negotiations and I am always glad to lend a hand if the client could use a second opinion, or an extra robot technician.