When An Expert Deviates
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Here is a little inside baseball for a Monday afternoon. No, not this kind of inside baseball – this kind. Its not really an ERISA story, at least not in any direct sense, but it is important to ERISA litigation nonetheless, for reasons I will get to in a moment. What I am referring to is this decision out of the First Circuit on the use of experts in a case that one of my colleagues, Robert La Hait, won the other day. Although it involves a dispute over an accidental death and dismemberment policy, a coverage some people obtain through their employers, the decision isn’t about ERISA rights or remedies, but rather about the extent to which an expert can testify at trial under the federal rules in a manner that deviates from the expert’s written report. Now, you have to remember that the rules themselves seem to suggest that, if something isn’t in an expert’s report, it can’t be said at trial, and there are certainly some district court judges who make clear that, at least in general principle, that is how they see it (I am not going to name names to protect the innocent, namely me). But the First Circuit ruling holds that there is some room for an expert to deviate from the written report disclosed to the other side, within reason and subject to the limits laid out in the decision. Its certainly worth a read, under any circumstance, for anyone who litigates expert intensive cases in the federal courts.
Beyond that, though, there is one specific hook in this case, that links it right back to ERISA litigation. Many areas of ERISA litigation raise significant issues that have to be addressed through expert testimony, including, for instance, financial expertise in breach of fiduciary duty cases involving investment selections, fees, and the like. The scope, accuracy and admissibility of expert testimony can become key, even outcome determinative at times, in ERISA cases, particularly breach of fiduciary duty cases. Several years ago, for instance, I was representing a third-party administrator charged by a plan sponsor with poor performance, and the case didn’t turn my client’s way until the eve of trial, when the court began seriously entertaining our challenges to the admissibility of the expert testimony proffered by the plan sponsor; it was the undercutting of that testimony that effectively ended the case. I tell this story for a reason, which is this: while the legal arguments about fiduciary standards and the like are important, it is equally important to pay attention in an ERISA case to the mechanical, nuts and bolts details of litigation (such as the admissibility of expert testimony) that lies at the heart of all federal court litigation. You can win or lose an ERISA case by falling down on either one of those points. This First Circuit ruling is a good example of one of the litigation details that cannot be missed while arguing over the complicated legal issues inherent in an ERISA case.
Lies, Damn Lies, Baseball Statistics and Wal-Mart
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I don’t know, maybe I had something rattling around in my brain about statistics in light of the then still pending Wal-Mart case when I wrote my last post, ostensibly about the use (and misuse) of statistics in baseball analysis, and less ostensibly about the use (and misuse) of statistics in litigation. I certainly wasn’t conscious of any concern on my part about the Supreme Court and Wal-Mart when I wrote that post, but the post now seems to have an air of precognition to it, at least in hindsight (one wonders whether it is possible to have precognition in hindsight, given the dictionary definitions of those words, but nonetheless). I particularly wasn’t thinking about Wal-Mart when I wrote that post because, like most casual observers of that case, I had long ago come to think it of as a case about class certification and class action requirements, and not about issues such as the proper role of statistics in litigation.
Regardless, one of the most interesting things right off the bat to me about the Court’s ruling in Wal-Mart is the extent to which its rejection of the statistical evidence at issue mimics the views of statistics in litigation that permeate my post on baseball statistics. As both the Court’s decision and that post suggest, there is no legitimate basis to rely on statistics when they do not, in fact, establish factually a specific point that could not otherwise be proven in a different manner of presenting evidence. This is another way of saying that statistical analysis does not belong in a court case, at any stage, if it does not illuminate – and do so accurately - a point that could not otherwise be shown.
Lies, Damn Lies and Baseball Statistics
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I am going to take a flyer, because after all this is my blog, and post a digression that really has nothing to do with the subjects of this blog, other than the fact that it relates to the significance of statistics and their impact on litigation, including financial litigation involving ERISA plans. I have talked before about the extent to which the role of statistics in this area – as in all of litigation, frankly – can quickly move the parties into the netherworld of half-truths, inaccurate modeling, and misleading statistic-based assumptions that spawned the well-worn phrase “lies, damn lies and statistics.” The phrase, for those of you not that familiar with it, basically reflects the idea that statistics, used for evil rather than good, can be used to try to show to be true something that is, in fact, not so, and that absent the cover of statistical analysis and complexity, would be seen quickly as either a lie or a damn lie.
This problem permeates litigation, whenever one moves into areas that require extrapolating from a small set of examples, such as determining damages across an entire class based on the data relevant to a limited number of class members or, in another type of scenario, determining contractual rates of performance by extrapolating from a defendant’s performance in a subset of cases. Cases built around such statistical approaches can run off the tracks, if one side or the other’s statistician applies suspect methodology. Of most fun to me, methodological errors, if the lawyers on the other side are astute enough to recognize them, can invalidate one side’s expert testimony and preclude its submission to a jury.
The extent to which statistics can be used or misused in this type of way to either illuminate or instead obfuscate what would otherwise be discernable to the observer has never been so well-illustrated as it has been in recent years by the explosion in the use of statistical analysis in major league baseball, a point both illustrated by and discussed in this article, from the new, overtly literate sports website Grantland (something I see as an attempt by ESPN to expand its tentacles to swallow up those few of us remaining sports fans who don’t think talking heads on a television screen yelling at each other about sports is all that interesting). Statistical analysis has devoured the front offices of baseball teams, replacing, in many instances, career observers and students of baseball, like a Pat Gillick, with laptop cradling, statistics-obsessed graduates of top-flight universities who, absent this opportunity to use math to grab central roles in baseball front offices, would have taken their math skills to Wall Street, or become well-paid actuaries.
However, what is getting lost in the shuffle here, and perhaps more than that in the smoke, mirrors and obfuscation that statistical analysis, when not properly placed in context, can generate, is that the statistical analysis being provided by the new, younger generation of baseball executives is not a “new” way of looking at baseball at all, but is simply the art of reducing observed reality to data that anyone with an understanding of the math can grasp and apply. What the data and their crunchers are doing is reducing the events that make up baseball games to numbers, so that people without vast experience observing the game and its myriad variations can understand and act on the game’s nuances. These analysts are not, however, doing anything more than illuminating facts that astute observers, after observing thousands of games and the variations inherent in them, have previously mastered based only on decades of watching the game and its possible outcomes in different circumstances, without ever reducing that knowledge to mere numbers and statistical formula. In essence, astute and experienced people who have seen enough baseball can tell you the same thing, and make the same judgment calls about which players are good at what, how to use players, what tactical decisions to make, and what players to sign, without ever needing the crutch of statistical analysis to do so. This, however, takes not just perception – something that not every baseball insider has – but also the decades of experience needed to see enough variation in the game, its players and its outcomes to be able to forecast outcomes. It is neither a coincidence nor an indicia of youthful expertise and comfort with math that the statistical revolution, such that it is, in baseball has resulted in ever younger baseball executives replacing much older, experienced warhorses. Rather, it is because turning the reality of baseball into numbers that can be analyzed independent of actual experience with the sport allows anyone astute enough to manipulate statistics to become an expert of a sort on baseball, without the need to first observe however many tens of thousands of hours of the sport that the old guard, without access to such data, had to see first hand before they could make the same evaluations and reach the same conclusions.
Want proof? You can find it right here in this article on Moneyball on Grantland, with its discussion of fielding being undervalued statistically, and the use of that fact by some teams to improve their ballclubs by focusing their spending on buying fielding. But there is nothing new about the idea that defense wins and that you can win by putting excellent fielders out there; all that is new is the reduction of that maxim to data points. Earl Weaver, whose expertise was developed by a lifetime spent watching baseball games, and who by doing so collected in his head – whether he realized it or not, although I think he did – all of the same data points that the new egghead baseball thinkers collate obsessively and then reduce to formulas on their laptops, always emphasized the importance of defense, yet he retired when most of the current generation of young baseball executives were in elementary school, assuming they were even born yet. Want more? Before the current statistical obsession turned to proving the role and importance of fielding, the baseball stat people were obsessed with demonstrating the lack of importance of bunting, hit and runs, and anything else that gave up outs and at-bats for free, in comparison to the importance of taking advantage of those opportunities at the plate; that whole idea is nothing more than the reduction to numbers of the Earl of Baltimore’s well-known hatred of bunting and the hit and run (something which some observers, incidentally, still think cost his team the 1979 World Series).
The point of this is not to belittle the new generation of baseball experts, who interpret baseball reality by what numbers tell them, but to illustrate a fact which too often gets missed: that statistics in baseball are not a new way of looking at the game, but are instead merely the reduction to numbers of a reality that others were already able to see. It has always troubled me that this simple fact has long been ignored in the glorification of the new baseball statistics, and in the idea that the older generation of baseball experts - people like Jack McKeon who somehow, despite not running SPSS packages for fun at night, still won a championship - suffered from a blind spot and did not know what the numbers showed.
And I suppose if I have to tie it back into the subject of this blog, and to my own professional preoccupations – which include the need to communicate clearly to juries and to understand when expert analysis is only interfering with doing that – I would point out that this is the perfect illustration of exactly how statistics, misused, can misrepresent reality in the courtroom. It is always important to grasp the extent to which statistics are clearly demonstrating a reality that cannot otherwise be seen, and when they are instead simply illustrating what could be seen without statistics and instead with careful observation. If you think about it, under the rules of evidence, statistical evidence doesn’t belong in a case in the latter instance, but can be truly illuminating in the former. The use of statistics in baseball, and how we think of them, is a perfect representation of this distinction.
On Disclosure and Conflicts of Interest
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In my life as a trial lawyer, I have found myself in a recurrent situation, in which a judge or an arbitrator eventually looks at me in an argument over discovery and asks if I really want the information I am after, as it could run against me. I always answer the same way, to the effect that I am comfortable with facts, believe that more information is more likely to lead to the just result in the case, that I will trust the facts to show us which way to go, and that I am more than willing to let the facts come out in the open and drive the case. Now, the truth is that, before ever seeking the discovery that is at issue, I will have long since thought through the subject and become convinced that the evidence in question, once brought out, is far more likely to help my case than to harm it; the reality, from a tactical perspective is that, otherwise, I would not have pressed the point in the first place, with me going so far as to ask a court or arbitration panel to order production of the witness, or documents, or whatever else is in question. That said though, my response - to the effect that I favor the facts coming to light - is a true sentiment. Facts are stubborn things, in the classic formulation, and they decide cases; I am more than happy to have them see the light of day. Heck, I would certainly like to know of them while I can do something about them, even if they are bad for my case, than have them just show up for the first time out of some witness’ mouth on the stand in the middle of a trial.
I thought of this when I read this investment manager’s discussion of the Department of Labor’s expansion of the term fiduciary, which I discussed in my last post, and of the Department’s various initiatives related to fee disclosure, in particular his discussion of lobbying against those actions. Like facts in a lawsuit, the facts of revenue sharing, fees, and the like belong in the open, and can do nothing at the end of the day but improve outcomes for participants, plan sponsors, fiduciaries and the better advisors. What’s wrong with a little sunshine, a little transparency, and a lot of disclosure in this context? Frankly speaking, probably nothing. Participants will eventually end up with better outcomes, while plan sponsors and fiduciaries will have the information needed to best do their jobs, which will - if they use the information right - make them far less likely to get sued or, if sued, be held liable for fiduciary breaches. Meanwhile, we all know that advisors get paid fees, as of course they should; the only change is that everyone involved in the decision making will know who is getting paid what and for what exact services. Under that - possibly excessively rosy - view of the world, the end result should just be that the better advisors, who are providing better products and services at better prices, will get more of the business. What’s wrong with that, from a forest eye view?
Percentage Players Die Broke Too
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I have always wanted to write another blog about trial tactics and litigation strategy, and call it Percentage Players Die Broke Too, after the famous line by Paul Newman in the world’s finest film, The Hustler (that’s the first one, mind you, not the embarrassing sequel they did with Tom Cruise many decades later). For now, though, I am going to settle on adding a new subheading to the digressions section of this blog, titled “Percentage Players Die Broke Too: Notes on Litigation and Trial Tactics.”
And the very first entry in that section is a link to this excellent post here, by North Carolina business litigator Mack Sperling, about upcoming changes to the federal rules that are intended to end one of my favorite pieces of federal court gamesmanship, the discovery of communications between experts and the lawyers who retain them, as well as of draft versions of expert reports. For awhile there, before everyone caught on, you could get ahold of such material, which could often be of great help in impeaching an opposing expert, simply because opposing lawyers mistakenly believed that they could engage in such communications and have drafts of reports revised under the cloak of privilege. They could not do so, in fact, and nothing was more fun that seeing the face of opposing counsel when they learned this.
In truth, over the last few years, it has become rarer and rarer to find opposing counsel who walked into this trap, and it was more a question of whether a particular expert prepared drafts that contradicted his or her final report without realizing the earlier draft might be discoverable.
Nonetheless, as the author points out, those days are gone forever. I should just let them go.