Pretty much everything was a counterintuitive curveball.
In April of 2006, more than 15 years ago, I wrote a memo to file that would go on to exert a disproportionately large impact on my thinking and career, albeit many of the lessons took years to come into focus and were far from what I expected.
The topic was Moneyball as applied to law firm associates—in essence, sketching out the data and methodology necessary to identify under and overvalued attributes of law firm associates, akin to the selection methods used by Oakland Athletics in the famous book by Michael Lewis.
This essay tells the story of how I came to write the Moneyball memo and what happened afterward, including what I learned about the market for associate-level talent, how law firms responded, and the status of law firm Moneyball today. Back in 2006, I naively thought that the counterintuitive insights went one level deep, thus potentially revealing an arbitrage strategy for entry-level talent. In fact, the counterintuitive insights were layered one on top of one another several layers deep, revealing much about the nature of law firms, lawyer motivation and psychology, and why the status quo in law is so enduring.
The stories that follow share 15 years of hard-earned wisdom. Read them if you want to laugh, partially at me, partially at your fellow lawyers, and partially at the growing pains of a wealthy industry that is reluctantly learning to embrace the power and value of data.
Moneyball comes to the legal academy
To a substantial degree, my memo was inspired by an article on Moneyball written by Paul Caron and Rafael Gely. See Caron & Gely, “Book Review Essay: What Law Schools Can Learn from Billy Beane and the Oakland Athletics,” 82 Tex L Rev 1483 (2004). Although nominally a book review, it was in fact a first-pass attempt at applying Moneyball principles to law school faculty hiring.
The Caron-Gely premise was simple: In the hiring of entry-level professors, law schools may be under and overvaluing certain objective attributes and thus missing out on junior talent that goes on to produce highly cited scholarship. To test their hypothesis, Caron and Gely assembled a data set for the fifty young scholars identified by Brian Leiter and a control group of fifty other scholars who entered law teaching during this same period, matching them by entering school and year.
After assessing various measures of productivity (citations, number of articles published, the rank of placements, and number of books, etc), which documented the vast difference in output between the two groups, Carol and Gely tested whether the various objective markers were more or less prevalent among the high-performing scholars.
Suffice to say, the results were contrary to the conventional wisdom: The rank of law school attended had no bearing on productivity, nor did membership on law review, a judicial clerkship, or a second advanced degree—basically every heuristic used by hiring committees in their first-pass review through AALS’s Faculty Appointments Register (FAR). In contrast, two factors were predictive of future productivity: publishing a student note while in law school and the number of articles published prior to the scholar’s first tenure-track job. See id. at 1544 at Table 5.*
* For a more comprehensive assessment of the profound insularity of law school hiring practices, see Tracey E. George & Albert Yoon, “The Labor Market for New Law Practices,” 11 J Empirical Leg Studies 1 (2014) (finding that “law schools appear open to nontraditional candidates in the early phases of the hiring process but when it comes to the ultimate decision – hiring – they focus on candidates who look like current law professors”).
As someone who studied legal education and law firms (i.e., legal labor markets), it was obvious to me that similar results would likely flow from any serious study of law firm hiring practices.
Such a project, however, was too speculative and unconventional to lead to publishable research, at least in the short term. Thus, my memo to file was a type of intellectual placeholder for something I could pursue after clearing the tenure hurdle, which was still 2.5 years off.
The Bi-Modal distribution
During the summer of 2007, I was fortunate to be in the room when Jim Leipold, the Executive Director of NALP, made his report to the ABA Section on Legal Education and Admission to Bar.
Hot off the press was an extraordinary graphic that showed the distribution of starting salaries for the class of 2006.
What makes this graphic so interesting?
In statistics, there are three measures of central tendency that, in most cases, tend to converge: the mean (or average), the median (50th percentile), and the mode (the most frequently occurring observation).
In a normal distribution, which is depicted by the classic bell curve, the mean, median, and mode tend to equal the same value. The above graphic, however, has two modes: one at ~$40,000 per year, and a second at ~$140,000. This makes the mean and median misleading and unreliable summaries of the market. Cf Greg Mankiw, “Bimodality,” Greg Mankiw’s Blog, July 10, 2008 (famous Harvard economist commenting on unusual bi-modal distribution in law).
In contrast, we can be relatively sure that legal ability or potential, no matter how we define it, is going to be normally distributed. Thus, if entry-level salaries have a bi-model distribution, some combination of two things are happening: (1) employers are overpaying for entry-level talent, and (2) significant amounts of high-quality talent are available at bargain prices.
In early September of 2007, I wrote a post on the bi-modal distribution that is perhaps my most widely read commentary. See Bill Henderson, “Distribution of 2006 Starting Salaries: Best Graphic Chart of the Year,” ELS Blog, Sept 4, 2007. Its key observation was that the market for so-called “elite” talent was overheating, with large law firm demand outstripping supply:
The second mode keep moving to the right because too many law firms refuse to reconsider their business model in light of a continuing surge in demand for corporate legal services. All these firms want Harvard, Columbia, Chicago graduates, etc. and, if necessary, Illinois (top 25%), Indiana (top 15%), Marquette (top 10%), etc. If legal education worked like any other market, Northwestern would be merging with Cardozo, exploiting Cardozo’s capacity and location and leveraging Northwestern’s brand. But law schools are maximizing prestige, not output or profit … .
At the time I did not fully appreciate the practical difficulty of changing a century-old business model. When a strategy has worked for several generations, the relationship between corporate law firms and elite law school grads becomes part of the natural order of how an industry operates—something that can be safely ignored, like air, water, or the law of gravity.
But even more importantly, I overlooked the possibility that elite identity may, at the margins, be more important to law firm partners than higher profits or better service to clients.
Moneyball at law firms
For the next couple of years, and as the opportunity presented itself, I’d occasionally come across law firm partners with a passion for law firm strategy and economics. Thus, with their encouragement, I’d re-caption my memo to file and send it for their review.
The first firm to receive my memo was a litigation powerhouse that perennially ranked in the AmLaw 25. My internal champions were younger partners who graduated from schools outside the T-14 yet had access to senior management due to their own strong performance. Unfortunately, my request to conduct a Moneyball study was rebuffed by the higher-ups. Yet, through this process, an amusing anecdote came to light.
A few years earlier, a group of partners involved in hiring conducted a crude, informal study of the firm’s most prominent partners. None of the traditional academic measures (rank of school, law firm, clerkships, etc) carried any weight. Instead, the factor that appeared to have the most predictive power was whether a partner’s father “worked with his hands.” Suffice to say, the results did not change the firm’s hiring practices.
A short time later, I had the opportunity to pitch the Moneyball concept to the chairman of another AmLaw 25 firm. After sharing the memo and receiving an enthusiastic response, we arranged for a call with the partner in charge of firmwide hiring. Again, things did not go well.
Hiring partner: “So what you are saying is that it is possible that a graduate of Hofstra may, under some conditions, be a better bet than a graduate of Harvard?”
Henderson: “Well, yes, that’s a plausible finding. The goal is the follow the data.”
Hiring partner: “Many of our partners won’t like that.”
Some might view the hiring partner’s perspective as biased and parochial. And I certainly did at the time. But in hindsight, I grudgingly came to see its wisdom, as law firm leaders have a relatively small and finite supply of political capital—so why spend it here? A few years later, that same hiring partner would be promoted to Global Chair and enjoy a tenure of staggering profitability that continues to this day.
That said, the idea of Moneyball appeared to be gaining traction elsewhere. In the fall of 2008, Kerma Partners, a consulting firm that was positioning itself as the McKinsey for legal, published a short study titled “Moneyball Indeed!” The study was done in collaboration with Redwood Think Tank, which was a small group of law firm leaders exploring new types of data analysis under the guidance of Redwood Analytics, a software company focused on law firm financial performance.
Though short on specific details and methodology, the authors reported a sample of 1,300 associate timekeepers at an AmLaw 25 firm. In terms of results, the researchers claimed to identified 12 “success factors,” separate and apart from grades and law school attended, that predicted greater productivity (higher billable hours) and a longer tenure at the firm. In addition, the authors observed that “Harvard attorneys do not perform any better than those at the 30th-ranked law school.” See Debra Cassen Weiss, “School Rank and GPA Aren’t the Best Predictors of BigLaw Success,” ABA Journal, Oct 16, 2008.
What were some of the success factors? We don’t know, as the point of publishing the study was to communicate the presence of significant inefficiency in the market for associate-level talent. If law firms wanted to know more, they could contact Kerma Partners or Redwood.
Founding of Lawyer Metrics
The publication of Moneyball Indeed! was both discouraging and validating. I was discouraged because I felt I had been scooped. Yet, I also felt validated because at least one large firm was taking these ideas seriously.
That said, since the authoring of the original Moneyball memo, my perspective on the legal services market continued to evolve. By the spring of 2008, with my tenure file largely complete, I used an invitation to the annual Georgetown Law Firm Symposium to write a working paper titled, “Are We Selling Results or Résumés?: The Underexplored Linkage Between Human Resource Strategy and Firm-Specific Capital,” Indiana Legal Studies, Research Paper No. 105 (April 2008). Drawing upon the emergence of the bi-modal distribution, which suggested that the demand for elite law schools graduate was outstripping the supply, I argued that eventually, some proportion of the large firms would need to bow out of the salary wars and re-examine their business model.
Yet, Result or Résumés also offered some prescriptive advice. The bi-modal distribution suggested that high-quality talent was available at a bargain price. Further, I noted the provocative findings of Robert Kelley’s Bell Labs study, which suggested that superior performance among gold collar workers was uncorrelated with IQ and various personal and social attributes but was, instead, the product of nine behavioral attributes. Even more intriguing, through a randomized controlled experiment conducted at Bell Labs, Kelley showed that the key behaviors were teachable, with women and minority engineers tending to benefit the most. See id at 15-19 (citing See Robert Kelley & Janet Caplan, “How Bell Labs Creates Star Performers,” Harv Bus Rev, July-Aug. 1993; Robert E. Kelley, How to be Star at Work (1998)).
Relatively confident that I had identified both an important problem and a set of viable solutions, I began discussing these ideas with several IU Law alums. Eventually, with the encouragement of my dean, those meetings became a working group which in turn led to the creation of an applied research company, Lawyer Metrics, that would eventually receive funding from a group of IU alumni seeking a creative way to benefit the law school.
With the prospect of funding, I leveraged my network to locate a group of talented co-founders. I had recently gotten tenure. What could be so hard about running a data analytics company focused on legal talent?
Moneyball studies
The launching of Lawyer Metrics was significantly aided by a series of low-cost/no-profit pilot studies at several law firms, including some AmLaw 50 firms that were interested in a Moneyball approach to hiring.
Without getting overly technical, the design of every Moneyball study is a value judgment about what qualifies as success at the firm. Is the goal more hours, higher performance evaluations, lower attrition? All of these factors are relevant, but in our view, measures of associate behavior and performance by partners were undoubtedly the best, as they were sure to correlate with other desirable outcomes. In addition, the value of any statistical study is necessarily a function of the underlying data. Unfortunately, at many law firms circa 2010, performance evaluations were viewed as relatively unreliable, as they were often used as a tool to manage associates out of the firm. Only a subset had a well-developed competency model that was used to evaluate associates on various dimensions of performance.
One of the first Moneyball studies with high-quality data resulted in a set of truly provocative findings. To convey their significance in a way that a nontechnical audience was sure to grasp, we developed a two-by-two matrix that plotted “what we think matters” in recruiting law firm associates against “what actually matters.” Below are some of the key results:
In brief, the top left box revealed that one common hiring heuristic was right—after controlling for a wide range of factors, law school grades were meaningfully correlated with midlevel associate performance. In contrast, the bottom left box reflected hiring criteria that were not predictive of future performance, including law school rank and judicial clerkships. Undergraduate honors and law review are in red because these factors were, in fact, negative predictors of associate performance. Regarding actual Moneyball factors that revealed potentially undervalued candidates, there were several, including a military background, blue-collar or pink-collar work experience, and publishing a student note while in law school.
I’ll never forget the meeting when we presented these findings to the hiring partner who had authorized the study. I was confident she would be pleased with the results, as they tended to collaborate some of her own intuitions. Yet, that’s not what happened. After enjoying roughly three seconds of satisfaction, her mind immediately turned to the topic of how these findings could be messaged to the partnership, which she soon concluded was impossible.
Thus, a Moneyball study with outstanding data and compelling results was dropped into the dustbin.
Insights on partnership and diversity
The Moneyball studies continued for a few more years, often yielding results that law firm partners were reluctant to use but, cumulatively, revealed important insights on how associates become successful in firms, including those with diverse backgrounds.
For example, in one study, we decomposed over 250,000 hours of workflow based on which associates were working with which partners. What we discovered was that associates who worked for partners who managed significant client work tended to have significantly higher ratings within the firm. Yet, we also observed very large gender- and race-based patterns (2x to 30x higher likelihoods) in which junior associates tended to gravitate toward supervisors who matched their own race and gender. This was problematic because, as a statistical matter, most of the developmentally rich work was controlled by powerful partners, who tended to be white males.
On the one hand, these findings seemed to corroborate a well-known article by David Wilkins and Mitu Gulati, which argued that “Training is the Royal Jelly of elite law firms. Those who receive it have a realistic chance of becoming ‘queens’ capable of supporting their own cadre of worker bees. Those who do not are destined to remain worker bees whose usefulness to the hive will eventually draw to an end.” David B. Wilkins & G. Mitu Gulati. “Why Are There So Few Black Lawyers In Corporate Law Firms? An Institutional Analysis,” 85 Cal L Rev 493, 542 (1996).
On the other hand, were the outcomes the product of “tracking and seeding” by law partners or, instead, a more entrenched free-market assignment system that let partners and associates form work relationships that felt comfortable and organic? Regardless of the motivation or mechanism, however, these workflows were almost certain to have a negative impact on diversity. We were hired to develop a clever hiring algorithm; yet, in the process of doing a thorough job, we were opening Pandora’s box.
In 2011, a peer-reviewed study in the American Sociological Review provided compelling evidence that the quality of an associate’s early career work assignments was the single most important predictor for longevity and eventual promotion at the firm. See Forrest Briscoe & Katherine C. Kellogg, “The Initial Assignment Effect: Local Employer Practices and Positive Career Outcomes for Work-Family Program Users,” 76 Am Socio Rev 291 (2011). Furthermore, after controlling for these initial assignments, factors such as race, gender, law school grades, and law school rank were largely irrelevant to the likelihood of advancement.
Ironically, the Briscoe-Kellogg study was designed to identify the various circumstances that would enable a knowledge worker (typically a female, but not always) to take advantage of family leave policies without derailing their career. Thus, the 1,000-lawyer AmLaw 20 firm that supplied them with ten years of associate evaluation and work-assignment data was primarily a sample of convenience. Yet, in the process, Briscoe and Kellogg learned that if an associate worked for powerful partners during their early days at the firm, they were largely inoculated against the negative effects of utilizing the firm’s family leave policy—an extraordinarily important finding that reveals so much about the nature of lawyer development.
In 2015, I mentioned some of this research to Norm Mullock, who was one of the founders of Redwood Analytics (of the Moneyball Indeed! study). In response, Norm regaled me with some of the findings of the Redwood Think Tank, including how the analysts were able to use first-year billing records to accurately identify associates who would be promoted to partner. Norm remarked, “It became a kind of parlor trick we used to astonish the law firms.” Unfortunately, after Redwood was acquired by LexisNexis in 2008, the Think Tank initiative faded away.
That same year, we sold Lawyer Metrics. A year later, still digesting all that I had learned, I hung up my Moneyball spikes and returned to full-time teaching and research.
Interesting and important questions, hard human answers
One of my biggest takeaways from doing law firm Moneyball studies is that sometimes there is a lag—measured in years or even decades—between our willingness to ask interesting and potentially important questions and our ability to truly receive, accept, and understand honest answers.
Thus, it is possible to assemble a dataset that can explore the validity and importance of various hiring criteria. In theory, the more counterintuitive the findings, the larger the opportunity to deploy a winning recruitment strategy. Yet, law firms are not baseball teams. And in hindsight, higher firmwide profits are not necessarily “winning,” especially after netting out the psychic cost of learning that one’s elite credentials are not a valid marker of ability and potential.
Early indications of this insight showed up in February of 2011 when a 30-year lawyer, having read a story about our Moneyball work in The American Lawyer, see Aric Press, “A New Look at the Conventional Wisdom,” AmLaw Daily, Nov 2, 2010, sent me a long email detailing his experience as a member of the firmwide hiring committee as a partner at a major west coast firm circa 2002. Prior to attending law school, the partner had worked as a research economist at a consulting firm and thus had a working knowledge of quantitative research methods.
On his own initiative, he built the requisite dataset to explore the attributes of who was succeeding at the firm. The result was an internal study, which the partner was now passing along to me. The partner wrote:
The study came to some perhaps counter-intuitive (and unpopular) conclusions– (i) that former summer associates were the weakest group of attorneys at the firm (although this varied somewhat depending on whether they were litigation or transactional attorneys), and (ii) that graduates from top 10 law schools were not as strong as those from schools ranked 11- 30.
If Moneyball is threatening to the self-image of law firm partners, just like statistical algorithms were threatening to old-school baseball scouts, the best way to preserve the status quo is to ignore the data and simply deflect any attempt at debate.
In the above case, our west coast partner reported that the study was “not well-received by firm management” and, as such, its findings were “promptly buried and never used for policy purposes.” Cf Post 110 (Randy Kiser experiencing a rebellion among managing partners when presenting empirical evidence that chafed against the conventional wisdom).
Managing internal competition to get excellent external results
Over time, I have gradually come to the conclusion that burying counterintuitive statistical results is sometimes wise law firm management, particularly in the short to medium term.
Selling Moneyball studies to law firms presumes that law firm partners are interested in an edge that will increase the firm’s profitability. And as a general matter, they are.
Yet, unlike other large businesses, the vast majority of law firms are collections of highly skilled legal specialists who are each charged with building their own successful practice—these are the ABCs (acquire, bill, collect) of partnership. Further, in a very real sense, they are in competition with one another for originating client work and recruiting the best internal talent to their practice. See Post 188 (reviewing various data points on the internal dynamics of law firms). The more effectively law firm leaders referee this competition, the better the firm’s external results. Cf. Post 223 (Yvonne Nath referencing the David Maister profitability framework that requires balancing the needs of talent against the needs of clients).
Some of the complexities of internal competition first came to light in a Moneyball study that had truly excellent data on associate performance, with several subscores that tracked the firm’s associate development model.
Curious to better understand the relative importance of each subscore, we ran a simple regression model that used the subscores as predictors for associates’ overall ratings. What we discovered was the overall rating was largely a function of factors that were helping individual partners optimize their practice. Factors such as judgment (I can leave you alone with clients), expertise (you know stuff I don’t know), and project management (you can manage others so I don’t have to) were driving the results. In contrast, factors that were arguably crucial to the long-term vitality of the firm (interpersonal skills, organizational commitment, professionalism, entrepreneurship, etc) were essentially irrelevant. Boiling it all down, the short-term reward system for partners was thwarting the long-term goals of a remarkably thoughtful system for associate development.
At another AmLaw 200 firm, the partner in charge of hiring told me that he routinely compiled binders of partner reviews of associates in preparation for an annual review of performance. Yet, ahead of the meeting, several partners would always request early access. What was their goal? To identify strong performing associates they could recruit to their practice, thus drafting off the training and experience provided by other partners.
Does the typical law firm leader have the time, power, and resources to fix such internal incentive problems while also maintaining partner expectations regarding overall profit? Law firm leaders are managing “elevator assets” and thus have to pick their battles. In the current market climate, it is far from clear why the fairness and efficiency of associate recruitment and development would rank as a top priority.† As Randy Kiser might argue, several immediate steps related to leadership and culture are likely warranted. See, e.g., Post 111 (Kiser on leadership).
† These are, in fact, serious structural problems that are the root cause of the legal profession’s dismal record on diversity. Toward the end of my Lawyers Metrics journey, I faithfully wrote out everything I had learned regarding law firm diversity. See Henderson, “Solving the Legal Profession’s Diversity Problem,” PD Quarterly (Feb. 2016). It is my hope that, eventually, we can follow the data and fix this very fixable problem.
A gym membership, not a fitness pill
In a very direct way, Legal Evolution is the outgrowth of Moneyball studies and my time at Lawyer Metrics, as I discovered diffusion theory as a useful tool for reducing a very long and expensive sales cycle See Post 004 (briefly making the connection).
As regular readers will recall, an innovative product or solution is much more likely to be adopted when it scores relatively well on five key attributes: (1) relative advantage, (2) cultural compatibility, (3) simplicity of use (or lack of complexity), (4) trialability, and (5) observability. See Post 008 (discussing core diffusion theory model); Post 098 (worksheet for scoring innovation).
In hindsight, it is obvious that Moneyball studies receive a low score in all five categories. Yet the factor that is most relevant to the eventual uptake of data analytics in the legal industry is cultural compatibility. Simply stated, many lawyers are uncomfortable with numbers and math—so much so they enrolled in law school to ensure a career where they had a comparative advantage. Cf. Henderson, “Underestimate Harvard’s New Admissions Strategy at Your Own Risk,” Law.com, Mar 30, 2017 (discussing lopsided nature of quantitative and verbal reasoning scores on the GRE based on science versus humanities majors and noting the long-term advantage of an elite school that can recruit both).
Sure, lawyers are competitive and love to win. But for a large percentage, a strategy based on quantitative analysis is far outside their comfort zone. Thus, in the early days of the data analytics movement in law, which I’ve lived through, it is accurate to say that our modal customer viewed Moneyball as a potential fitness pill. Indeed, some believed that a single slide from one of our presentations was all that was needed to get a competitive edge. That was clearly wrong, as partners would bat away anything that was counterintuitive, threatening, or not immediately useful to their practice. But more importantly, the value of data is the opportunity to see and connect more dots—i.e., to improve one’s thinking—which in turn improves both strategy and execution.
Thus, in hindsight, I would characterize data analytics in law as a gym membership, with the desired benefits only accruing after years of discipline, sacrifice, and focus. The willingness to make the investment is going to vary widely, but it’s doubtful that the legal industry will entirely ignore the power and benefits of data.
Indeed, this metaphor is backed up by the evolution of data in baseball. Circa 2003, when Moneyball was published, the state of the art was stocking up on players with low salary requirements but high on-base percentages. 15 years later, sportswriter Ben Reiter would publish Astroball, which chronicled the remarkable ascent of the Houston Astros through the use of analytics that went well beyond the playing field, quantifying the performance value of clubhouse leadership and team chemistry.
One of the greatest innovations was the off-season use of data feedback loops for both pitchers and batters. For those players who refined their mechanics by sticking with the program, the impact on their careers was often dramatic. The idea that a mediocre player could become great through the assiduous application of data is fundamentally at odds with traditional baseball lore as well as the original Moneyball story of Billy Beane and the Oakland A’s. Yet it is also profoundly hopeful and a testament to untapped human drive and potential.
No diffusion or slow diffusion?
Because the change process moves so slowly in law, it is tempting to assume that, at least in some cases, the status quo is permanent and plan accordingly. See, e.g., Post 231 (discussing the possibility of shifts in the legal market that will take multiple decades to play out); Post 246 (Dan Rodriguez, in the last of a four-part series on bar federalism, discussing the many arduous steps on the road to market liberalization, most of which are highly improbable).
Thus, perhaps this is how we should view the uptake of serious data analytics in law. Yet, I have contrary information from the front lines.
The Moneyball work that was done at Lawyer Metrics circa 2010 to 2016 is now being carried on by Evan Parker of Parker Analytics, who served as our Director of Analytics. During the early days, we tended to assume that Moneyball would be a tool of large but less elite law firms that were looking for an edge and that the law firm equivalent of the Yankees or Red Sox would ignore the opportunity. But that turned out to be wrong.
In the summer of 2019, through a series of improbable events, Evan and his work were featured on an episode of Revisionist History, a very popular podcast produced by Malcolm Gladwell. See “The Tortoise and the Hare,” Revisionist History, Season 4, June 27, 2019. Afterward, Evan started receiving several inbound calls from major US law firms, including some of the Wall Street elite (the Yankees). In turn, this resulted in a large-scale study Moneyball study after a single meeting with a firm’s chairman. A sales cycle that ordinarily took 6 to 18 months was reduced to 45 minutes. Overall, I am told, everything started moving faster, with Evan adding several other large firm clients for large data-focused projects.
So, what exactly changed? Evan attributes it to three factors.
First, as always, ambitious data projects require an innovator or early adopter leader at the helm.
Second, the drumbeat of data in the broader economy and culture continues to grow, making even rich and sophisticated lawyers feel vulnerable. Likewise, the imprimatur of Malcolm Gladwell certainly did not hurt. This gives the innovator and early adopter leader more latitude to push.
Third, and relatedly, generational leadership is beginning to turn over at major law firms, and leaders in their early 40s can safely and rationally make data part of their change agenda. In addition, this cohort is too smart and savvy to believe in fitness pills. To the extent that Evan Parker is offering a gym membership for a few curious people at the top of major law firms, the next generation, with most of their career still ahead, has a strong incentive to get on board. Gradually they will bring along the rest of the firm.
All of these stories were collected because of my rather naive impulse over 15 years ago to write a memo to file on the topic of Moneyball. I learned a lot; just not what I intended. Enjoy your Sunday.