Category Archives: Building a Business

A startup culture poses unique ethical challenges

In the WSJ, Kirk O. Hanson writes that “Startup culture poses a host of temptations—and resistance is hard.”  He asked a panel of Silicon Valley entrepreneurs and venture capitalists to identify the greatest pressures and temptations they’ve faced, and where they think some entrepreneurs frequently fall short.

There are unavoidable ethical dilemmas in every profession and industry, of course, but the dilemmas entrepreneurs face are more formidable and more difficult to manage. Some entrepreneurs stay the ethical course. But they seem at times to be the exceptions. Startups generally have no infrastructure to address ethical challenges, and frankly, entrepreneurs have little time or focus for monitoring their own behavior. Their energies are elsewhere.

4 of the 10 questions addressed by the panel dealt with honesty:  do we lie to (1) the funders to get cash, (2) the customers to get revenue, (3) the public investors for a higher IPO valuation, or (4) to hit our numbers. Of course the answers in all four cases – each with its own color of temptation – is ‘No.’

We’ve often touched on this subject ourselves.  From Observing Honesty in Business:

You can’t always count on oreos to let you know if someone’s telling the truth

In our business dealings (as opposed to a poker table) we put a premium on transparency, as it’s easier to remember the importance of being honest when everyone involved in a business relationship can observe how decisions are being made.

This research gives us an opportunity to revisit the subject of when business promotes honesty.  Three years ago we cited this article from The Independent Institute, which argues that businessmen are more honest (or less dishonest) in their dealings than preachers, politicians, and professors.

Business promotes honesty, we argued, because of the importance of long-term relationships:

In our experience, the business case for honesty (the moral case is another discussion) can often be based on the fact that many businesses rely on repeat business.  So although dishonesty may improve the profit or advantage in a single transaction it would result in less success over the long term.

In that same post we quote Will Harrell of CapCo Asset Management:

The upside from being perceived as a reliable, consistent, trustworthy, &etc. vendor of certain kinds of goods and services is simply huge.  Costco’s CEO has a line I love: “No easy hits on the customer.”  Honesty is just a sub-category of this thesis, which in many cases has more to do with product quality or user experience than honesty per se:  McDonald’s consistency, the taste of a Hershey bar, etc.  It’s also not limited to customers – similar considerations apply to suppliers, capital sources, and employees.

We once wrote on this subject in a quarterly letter, On Being a Good Partner: “But however great or small a company’s advantages, it is our observation that their durability is usually directly related to how good a partner the company is to those with whom it does business.”

It may strike some as corny and simple, yet is exactly what game theory predicts will transpire between participants in repetitive transactions.  What’s surprising is that the effect is not more dominant, and that trustworthy players don’t completely squeeze out untrustworthy ones.

By the way, we mention above that the moral case for honesty is another discussion, and it is.  But we don’t want to leave the impression that the case for ethical behavior is purely a practical one.  We also try our best to act with honesty and integrity both within our firm at BPV and with our entrepreneur partners because we believe deeply that it is the right thing to do.  And we look to partner with entrepreneurs who share that view.  That approach may not always lead to a tangible win in business terms, but it defines who we are as people and allows us to sleep at night.

PDMS-BPV relationship featured at Florida Venture Forum Boot Camp

fvf faber brownYesterday at the Florida Venture Forum Boot camp event at the Citrus Club in Orlando, Josh Brown (PowerDMS CEO), Cathy McKenna (PowerDMS’s auditor for Vestal and Wiler), Jeremy Sloane (PowerDMS’s counsel from law firm Sloane and Johnson), and I had a chance to do a panel discussion moderated by Steve Castino of Vestal and Wiler on the topic of Ballast Point’s investment in PowerDMS in April of 2014 and lessons learned thereafter.

To no one’s surprise, Josh did a great job in laying out the reasons for his company’s success to date and his rationale for choosing Ballast Point as an investment partner.  Josh focused on issues of team-building and empowering employees, even mentioning the famous line from the Founders’ Dilemma as he said that he had to make the decision “Do I want to be rich or king?”  He made the point that he could have tried to build a lifestyle business where he could have been “king,” but he saw the market opportunity and the company’s positioning and made the conscious decision to build an exciting, high-growth company.

To do that, he needed to invest in his team in a big way and bring on a trusted investment partner who could really help him on the team-building and network side.  He had to relinquish some control in order to accomplish these goals of building an exciting, venture-backed company, but he was able to get comfortable with this decision by making a conscious effort on the relationship side to hire people with the highest ethical standards and choose an investment partner that he knew would support the company in good times and in bad.

Josh has let his talented employees flourish in a way that has driven PowerDMS’s growth beyond what he could have accomplished on his own, and that growth has once again landed PowerDMS on the Inc. 5000 list of fastest-growing private companies.  We at Ballast Point are thankful that Josh and the team at PowerDMS chose us as his investment partner, as we have joined them on this exciting journey to build a high-growth, SAAS company in central Florida.

The Ultimate October Blueprint

Our regular readers know that we often cogitate over the roles both skill and luck play in sports and business.  The eve of the baseball postseason feels like a good time to revisit the subject.

Especially since we’ve found new data, even in an admittedly a small sample size.

In The Ultimate October Blueprint, David Schoenfield studies the past 5 post seasons (“when the strike zone started increasing in size and offense began to decline“) and draws a few tentative conclusions:

  • Don’t strike out – even though you’re facing better pitching!
  • Contact trumps power, although “the weird thing is that home runs in the playoffs have matched the frequency of home runs in the regular season.”    But none of the teams who led all playoff teams in HRs – in either league – have won the World Series in the past 5 seasons.
  • Use your bullpen, early and often.  Starting pitchers don’t fare as well as they start going through the lineup a second and third time, so don’t let them lose a game in the middle innings.  “Go to the bullpen. Hope they do the job.”

However… all of the past 10 World Series teams had a starter step up in the postseason:

The thing is, sometimes that starter is a Bumgarner or Verlander or Lincecum, but sometimes it’s an untested rookie like Wacha, a veteran having a so-so season like Lester (he had a 3.75 ERA in 2013) or a mid-rotation starter like Vogelsong. And sometimes it’s Colby Lewis…

The last team to lead the majors in starters’ ERA during the regular season and win the World Series? The 1995 Braves. In other words, having a season’s worth of gems from your rotation guarantees nothing in October — maybe bad news for all five NL playoff teams, who rank 1-5 in the majors in rotation ERA.

But here’s an indicator that may help: In looking for which pitchers may come up big in October, it appears a strong finish is important.

The data also suggest that velocity is overrated.  “Maybe when the chips are down, it’s those crafty veterans throwing in the low 90s and situational relievers who win you World Series.”

Schoenfield summarizes advice for when the contest isn’t long enough for the Moneyball math to work:

[The playoffs are unpredictable but] there are a few strategies that seem to work: Battle pitchers with two strikes and put the ball in play; turn the game over to your bullpen in those middle innings; rely on one starting pitcher if you have to; get some big home runs from unlikely heroes along the way. And maybe hope you have a starting pitcher who can throw five innings of relief on two days’ rest in Game 7 of the World Series.  [As Madison Bumgarner did for last year’s Giants. – ed]

The fan inside us is fascinated by the prospect of advantages gained in the short term, but over the long term our conclusion remains the same:

While big data may help make accurate predictions or guide knotty optimization choices or help avoid common biases, it doesn’t control events and can be undone by cluster luckModels are useful in predicting things we cannot control, but for those in the midst of the game – players or entrepreneurs – the results have to be achieved, not just predicted.

 

Related stories:

Introverted traits are undervalued in the business world

In “Do I put off a human vibe to you?” (January 2014) we wrote that while the “extrovert ideal” may capture the public imagination, our experience with quiet and cerebral entrepreneurs has demonstrated that one doesn’t have to be an extroverted leader in order to run a successful high-growth company.

dilbert-introvertsWriting in yesterday’s Wall Street Journal, Elizabeth Bernstein makes the same argument, in longer form, citing unique skills that introverts offer:

– a propensity for balanced and critical thinking
– a knack for quietly empowering others and less interest in personal glory
– the ability to focus for long periods and to use solitude to think originally and create something out of nothing
– a more focused mindset to their leadership style
– better at dealing with setbacks (because they need less external validation)
– more realistic when listening to feedback or analyzing information (because they do less public promotion of themselves)

Bernstein then argues that the different styles work under different circumstances. From “Why Introverts Make Great Entrepreneurs“:

An introvert’s desire to put the spotlight on others and really listen—and to model this skill for others—will be a huge advantage to his or her company, in sales, management, partnering and just about any other aspect of the business, Ms. Buelow says. “The best businesspeople aren’t necessarily the best talkers, but the best listeners, the people who ask the right questions,” she says.

That was borne out in a study reported in the Harvard Business Review in December 2010. Adam Grant, a professor at the University of Pennsylvania’s Wharton School , and his colleagues found that when employees were proactive, introverted leaders generated better performance and higher profits than extroverted leaders did.

Why? Extroverts are better at leading passive employees who need a lot of direction, says Dr. Helgoe. “But if you have a very creative, self-motivated staff, introverts are better at channeling that talent and staying out of the way—listening, taking in ideas, helping employees shine.”

This article from last month’s WSJ makes a similar point about “ambiverts,” those with both introverted and extroverted traits, neither dominant, who adapt their individual leadership styles to the situation:

[Ambiverts] have more balanced, or nuanced, personalities [and can] move between being social or being solitary, speaking up or listening carefully with greater ease than either extroverts or introverts. “It is like they’re bilingual,” saysDaniel Pink, a business book author and host of Crowd Control, a TV series on human behavior, who has studied ambiversion. “They have a wider range of skills and can connect with a wider range of people in the same way someone who speaks English and Spanish can.”

In practice we need each other.  The best teams typically will have some of both who play to each other’s strengths.  But it doesn’t have to be the extrovert in the entrepreneur- CEO’s chair.  Here’s how Bernstein closes her piece:

Of course, introverts do have some qualities that aren’t that well-suited for entrepreneurship: They can be too internally focused and sometimes shun networking. Extroverts are natural networkers and certainly know how to rally the troops.

But it’s time to recognize that introvert traits have long been undervalued in the business world—and it may be time for extroverts to try and be more like introverts.

The roles of skill and luck in sports and business

The 2015 baseball season is demonstrating that when it comes to untangling the roles skill and luck play in sports and business, luck may play a greater role than we’d like to think.

With technology and best practices so widely and easily articulated and disseminated, the difference between the best competitors and the worst is less than in the past.  So a hot stretch of cluster luck can make the difference.

Case in point:  so many teams currently hover close to .500, in contention for the 10 playoff births, that the trade market has been slow to develop.  Teams can think in terms of limping into the playoffs and then getting hot, and so take longer to choose whether they’re buying or selling assets.

The pre-season projected standings predicted such parity, with only 23 projected wins separating the leaders from the laggards entering this season and only 2 teams projected to finish with 90+ wins.  Welcome to MLB’s 2015 Projected Standings, Where Everyone (and No One) Is a Winner:

Projection systems tend to forecast more conservative winning percentages than we’re used to seeing in the final standings. That’s because projected win totals reflect the most common outcomes of thousands or even millions of simulations, whereas a single season, with its wild fluctuations in luck, offers ample opportunity for teams to significantly exceed or fall far short of their true talent levels…  As Phil Birnbaum and Neil Paine have noted, there’s an absolute limit to the accuracy of baseball projections. Even if we were omniscient when it came to team talent levels, we wouldn’t be able to predict luck. And luck has large effects: As Birnbaum wrote, “On average, nine teams per season will be lucky by six wins or more.”

It’s not only harder to separate yourself from the pack, there’s also less incentive to do so:

Last August, Birnbaum wrote that in a rational market, an expanded playoff field should make bad teams more willing than before to spend on free agents, and good teams more willing to tighten their belts. “With more teams qualifying for the post-season, there’s less point making yourself into a 98-win team when a 93-win team will probably be good enough,” Birnbaum wrote. “And, even an average team has a shot at a wild card, if they get lucky, so why not spend a few bucks to raise your talent from 79 games to (say) 83 games, like maybe the Blue Jays did last year?” That’s exactly what we’ve seen. … (However) as soon as it sinks in that not all “postseason” spots have equal value, teams might start prioritizing division titles over coin-flip wild-card games and aiming, once again, for greatness instead of good-enough-ness.

Somewhat ironically, the team suffering the most from bad luck so far this season is the very same team who invented “Moneyball.”

Billy Beane actually built a competitive team, but one that’s had an absolutely brutal run of luck. By BaseRuns, the A’s have played .596 baseball, good for a 51-34 record that would make them the second-best team in baseball. In reality, though, the A’s are a wildly frustrating 38-47 (.447), leaving them a whopping 13 games behind their expected record. No other team in baseball is more than five games below its BaseRuns-expected record. Oakland is 6-21 in one-run games; that .222 winning percentage would be the worst figure over a full season in 80 years.

The A’s will have more luck in one-run games. And they’ll play more like the .596 team than the .447 team over the rest of the season. If anybody in baseball has faith in trusting that longer view of performance, it’s Beane. The problem, of course, is that they may be buried too far in the standings to catch up.

Power Score – Your Formula for Leadership Success

I don’t typically read “business books” on vacation, but I made an exception for “Power Score – Your Formula for Leadership Success”.

Power Score is the new book by Geoff Smart and Randy Street, the authors of “Who: The A Method for Hiring” (with an assist this time from their colleague Alan Foster).  “Who” has been required reading in our shop for several years and informs a lot of the questions we ask (and how we ask them) in our “people due diligence” when we are considering partnering with an entrepreneur or helping one of our portfolio companies hire a new senior executive.

So I was excited to read Power Score, which utilizes the data from 15,000 management interviews over twenty years that the authors and their team have done on behalf of corporations and private equity firms at their consulting company, ghSMART.  I love data, and I was impressed with how they mined their unique database to come up with a formula that facilitates successful leadership.

As it turns out, successful leaders get three things right:

1) Priorities – ensuring that they have priorities that are correct, clear and connected to their mission,

2) Who – making sure they have diagnosed their teams strengths and risks, deployed their people against the right priorities, and continually developed their people, and

3) Relationships – working to make sure that their culture and incentive structures support teams that are coordinated, committed and challenged and promote strong relationships with both employees and external constituencies.

The formula seems fairly simple (simple is good on vacation), but the execution is very hard, and very few leaders operate at consistently high levels in all three areas.

The authors offer a scoring system that challenges leaders and their teams to rate themselves on a 1-10 scale in each of the three areas and then multiply the scores (PxWxR) to see how they compare with the best proven leaders in the ghSMART database. (Hint:  500+ is pretty good but 9x9x9 = 729 is the Holy Grail!)  More importantly, they describe how to increase your Power Score by continuously improving in each area, and they also offer a lot of helpful real world examples of how great leaders do it.

The book is written in an easy to digest question and answer format and it won’t take long to finish, though I found myself rereading various sections throughout the book and applying them to companies I have been involved with over the years.  Much like they do in “Who” for identifying and recruiting outstanding talents, the authors offer a process that can’t help but enhance leadership success if executed faithfully.  And, again, unlike most business books it’s backed up by a lot of great data and research on what makes for a strong leader.

I highly recommend the book and plan to send copies to our entrepreneur partners at Ballast Point Ventures, all of whom are looking for that extra leadership edge in their quest to build great companies.  We’ve added it to “The Library in St. Pete” for books we highly recommend.  You don’t have to take Power Score on your next vacation, but then again haven’t you watched enough movies on your iPad during those long flights?

 

Just waves of confirmation bias?

We recently came across another excellent article on data, decision-making, and cognitive biases.  It’s a story about Kristaps Porzingis , a 7’1″ 19-year-old, playing in Liga ACB, perhaps the second-best basketball league in the world.  He’s “the type of prospect that has historically torn coaching staffs and front offices apart” as they try to assess his NBA bona fides before the draft.

All draft picks are crapshoots, but some feel like crappier shots than others. It’s uncouth to plainly say, “I have a bad feeling about this guy,” so we do our best to justify our vague inklings. The stronger our distaste, the stronger our effort. So of course it’s the foreigner with the spindly frame and the funny name who has people [grasping for answers]. … What is the draft if not complete pseudoscience?  …

He’s like a young Robin trying on Batman’s utility belt — the tools are there, and they’re incredible. They just don’t fit yet, and you can’t be too sure that they ever will. His issues on defense are the same most players his age experience. He bites on pump fakes, he gets caught ball-watching, and he can be a step slow recovering to his man. But there is a chance that, five years down the line, he’ll be doing things that only a handful of NBA big men can do at a high level.

Maybe all of that hokey pseudoscience will prove prescient. Drafting isn’t an art, and it isn’t a science, but if you squint hard enough, it can look like a happy medium. It’s all just waves of confirmation bias on both ends of the spectrum posing as data points, right? It can tell you anything you want it to if you wait long enough. But it can’t, at the very moment, tell you the fate of Kristaps Porzingis. And so, like any other year, we’ll go on trying to find some illuminating detail that will solve the puzzle once and for all, blissfully ignorant to the fact that there’s only one person with the final pieces.

As with the NFL draft, pre-draft metrics have only some predictive power.  The data don’t predict a player’s ceiling, can’t account for what kind of system a player will enter, the talent he’ll have around him, the luck he’ll have with injuries, or the intangibles he possesses.

If you’re looking for a bellwether of NBA success, look to the NCAA tournament.  Its pressure-packed contests featuring the best college players in the country in front of gigantic audiences turns out to be a meaningful simulation of NBA conditions.  Even though it’s a very small sample size – for most players just a game or two – the data show that players who move up the draft board as a result of their performance in March Madness deserve it.

The crucial distinction to remember on this topic is that Big Data has limitsWhile it may help make accurate predictions or guide knotty optimization choices or help avoid common biases, it doesn’t control eventsModels can predict the rainfall and days of sunshine on a given farm in central Iowa but can’t change the weather.  A top draft pick may or may not develop based on the system, surrounding talent, &etc.

In our experience the best results often come from a combination of deliberation and intuition.  Too much data can lead to analysis paralysis, common sense can be a shockingly unreliable guide, and those who rely on intuition alone tend to overestimate its effectiveness.

The answer for Porzingis is obvious:  enroll him in an American D-I hoops powerhouse – we’d recommend a school in the Southeast or Texas – and hope that school enjoys a deep run next March.

Board dynamics that could suppress contrarian advice

Four years ago, on the sesquicentennial of the first shots fired in the Civil War, we cited a piece from The Wall Street Journal that described how the dynamics of General Lee’s staff undermined the accomplished leader, who, at Gettysburg, failed to sense his team’s growing doubts.

The lesson remains relevant for entrepreneurs so we revisit it this week – the sesquicentennial of Lee’s surrender at Appomattox Courthouse.

Lee’s generals knew that modern weapons and a determined enemy would turn the charge into a disaster.  But who among them would step forward to question the supremely confident general known as the “marble man”?  Lee would have been surprised to discover that his generals had doubts, because he considered himself open to their opinions. But his own stature and idea of himself created a barrier that only the trauma of failure could overcome.

It’s easy to imagine (Lee’s) staff struggling to effectively press their contrarian advice.  Any number of factors could cause one not to risk a career “Pickett’s Charge”:  the leader’s force of personality, the high stakes involved, the constrictions of time, the subtle team dynamics of consensus building, or even an over-reliance on formal procedures.  And what’s true for a strong general is true elsewhere – including CEOs and their boards of directors.

Owners of private companies get to pick both their investors and their board members, and therefore have an opportunity to create an environment of mutual accountability in which team members trust and challenge each other.

Entrepreneurs are almost always surprised how much value a good board can bring to their companies.  In our experience, boards work best when members’ informal modus operandi animate the formal framework of decision-making and the relationships strong enough to foster open dissent and compensate for the all-too-human tendency to learn only after it’s too late.

March Madness and the availability heurisitic

(Editor’s note:  This is a slightly modified re-print of a popular piece we published in April 2013.  Our readers enjoy the subject of how to improve their decision making skills, especially when sports can provide the context.)

Decision making and cognitive biases are common themes here at NVSE.  We’ve written about good board decisions, how the popularity of the Mona Lisa is based on circumstance rather than inherent artistic qualities, how the design of the decision-making process affects the decision, and how managers can undermine their decision making by over-relying on common sense, rationalizing instead of being rational, or making unconscious choices.

The availability heuristic refers to placing too much emphasis on data that is quick and easy to gather.  However in this particular instance – clutch performance during March Madness – it just might be more of a reliable bellwether than a problematic bias.

In Method to the Madness Peter Keating explains “why NBA GMs should go mad for the breakout stars of March.”

NBA teams scout hundreds of players across the country, tracking their every move for months on end, and put dozens of prospects through extensive workouts. Yet when it comes to draft night, clubs routinely rely on the same measure the rest of the country uses: NBA GMs, it turns out, favor players who had surprising success in the postseason. And the even bigger shocker? They’re right to do so.

Economists Casey Ichniowski of Columbia and Anne Preston of Haverford studied March Madness because they wanted to investigate whether employers often overweigh recent and vivid information when making decisions. Earlier research had shown that when we make judgments, we rely on data that’s accessible — the quickest and easiest stuff to gather — even when we know it’s important to be objective. Social scientists call this the “availability heuristic,” and it explains why Americans wrongly believe tornadoes kill more people than asthma: A spectacular catastrophe is easier to recall, so we overestimate its likelihood…

On average, a player who scores four points per game above expectations on a team that wins one more game than projected in the tournament will boost his draft position by 4.7 slots, according to Ichniowski and Preston. Now, here’s the thing: Players who get March Madness bumps deserve them. Ichniowski and Preston also examined what happened to players after their draft days… In every case, the group that got draft boosts from the NCAA tournament played better than those who didn’t. If anything, teams undervalue March Madness as a predictor of future success and stardom.

I usually repeat “sample size, sample size, sample size” about as often as and in the same tone that Jan Brady wailed “Marcia, Marcia, Marcia,” so I was shocked by these results. For most players, March Madness lasts only a game or two, yet it sends a signal powerful enough to last entire careers.

“I’m thinking of showing my sports class a clip of Michael Jordan beating the Cavaliers and asking if you could have ever predicted this, so that maybe you take MJ at No. 1 instead of No. 3,” Ichniowski says. “Then I’d like to show his NCAA shot [winning the national championship for North Carolina] and move to the question of how much to weight March Madness performance.” The answer: At least as much as NBA GMs do now. The NCAA tournament, with its pressure-packed contests featuring the best college players in the country in front of gigantic audiences, is truly a meaningful simulation of NBA conditions.

UPDATE (6/14/15):

Same sport, different draft; same struggle, different bias:  a story about Kristaps Porzingis, a 7’1″ 19-year-old playing in Liga ACB, perhaps the second-best basketball league in the world.  He’s “the type of prospect that has historically torn coaching staffs and front offices apart” as they try to assess his NBA bona fides before the draft.

All draft picks are crapshoots, but some feel like crappier shots than others. It’s uncouth to plainly say, “I have a bad feeling about this guy,” so we do our best to justify our vague inklings. The stronger our distaste, the stronger our effort. So of course it’s the foreigner with the spindly frame and the funny name who has people [grasping for answers]. … What is the draft if not complete pseudoscience?  …

He’s like a young Robin trying on Batman’s utility belt — the tools are there, and they’re incredible. They just don’t fit yet, and you can’t be too sure that they ever will. His issues on defense are the same most players his age experience. He bites on pump fakes, he gets caught ball-watching, and he can be a step slow recovering to his man. But there is a chance that, five years down the line, he’ll be doing things that only a handful of NBA big men can do at a high level.

Maybe all of that hokey pseudoscience will prove prescient. Drafting isn’t an art, and it isn’t a science, but if you squint hard enough, it can look like a happy medium. It’s all just waves of confirmation bias on both ends of the spectrum posing as data points, right? It can tell you anything you want it to if you wait long enough. But it can’t, at the very moment, tell you the fate of Kristaps Porzingis. And so, like any other year, we’ll go on trying to find some illuminating detail that will solve the puzzle once and for all, blissfully ignorant to the fact that there’s only one person with the final pieces.

As with the NFL draft, pre-draft metrics have only some predictive power.  The data don’t predict a player’s ceiling, can’t account for what kind of system a player will enter, the talent he’ll have around him, the luck he’ll have with injuries, or the intangibles he possesses.

If you’re looking for a bellwether of NBA success, look to the NCAA tournament.  Its pressure-packed contests featuring the best college players in the country in front of gigantic audiences turns out to be a meaningful simulation of NBA conditions.  Even though it’s a very small sample size – for most players just a game or two – the data show that players who move up the draft board as a result of their performance in March Madness deserve it.

The crucial distinction to remember on this topic is that Big Data has limitsWhile it may help make accurate predictions or guide knotty optimization choices or help avoid common biases, it doesn’t control eventsModels can predict the rainfall and days of sunshine on a given farm in central Iowa but can’t change the weather.  A top draft pick may or may not develop based on the system, surrounding talent, &etc.

In our experience the best results often come from a combination of deliberation and intuition.  Too much data can lead to analysis paralysis, common sense can be a shockingly unreliable guide, and those who rely on intuition alone tend to overestimate its effectiveness.

Untangling skill and luck in sports and business, redux

We’ve come across another good piece on decision-making and the limits of decision models.  

In The Great Analytics Rankings, ESPN “unleashed (its) experts and an army of researchers” to look across the four major sports and assess each of the 122 professional teams on how much of their approach is predicated on analytics.

They ranked teams both within each sport and across the entire field of 122, and then took a look at the sport with the most developed methodologies – baseball – to ask, “do clubs that prioritize analytics win more?

Their conclusion:  there’s just a slight correlation between more analytics and more success.  It remains tough to eliminate the usefulness of having more money than other clubs, and with technology and best practices so widely disseminated and articulated (in baseball, at least) the early Moneyball advantages may have been arbitraged away.

All this isn’t to say analytics are a nonfactor. Of course they’re important. For one thing, you have to keep up with the rest of the sport, even if the advantages to be gained are small. A lot of small advantages can add up. Look at the Astros’ signing of Collin McHugh, a nondescript pitcher waived by the pitching-poor Rockies. The Astros studied the PITCHF/x data on McHugh and saw a curveball with a good spin rate and took a chance on him. As Business Week reported:

The Astros’ analysts noticed that McHugh had a world-class curveball. Most curves spin at about 1,500 times per minute; McHugh’s spins 2,000 times. The more spin, the more the ball moves during the pitch — and the more likely batters are to miss it. Houston snapped him up. “We identified him as someone whose surface statistics might not indicate his true value,” says David Stearns, the team’s 29-year-old assistant general manager.

It gets a little more interesting with sports earlier in the process than baseball; e.g., the NHL, in the midst of its own “analytical awakening,” with concepts such as “Corsi” and “Fenwick” bringing together schools old and new.  Only one NHL team cracked the Top 10 of ESPN’s rankings:  the Chicago Blackhawks.

While Joel Quenneville is an old-school coach, the Blackhawks use analytics to find players who might be undervalued elsewhere but fit exactly what Quenneville and the Blackhawks try to do on the ice systematically. It’s been a great combination, with Bowman and Quenneville teaming up to win two Stanley Cups.

“I don’t claim to have the answers — we have a formula that works for us,” Bowman said. “We’re always trying to expand and add a new component each year that we do a little more with.”

When it comes to untangling skill and luck in sports and businessbig data may help make accurate predictions or guide knotty optimization choices or help avoid common biases, but it doesn’t control events and can be undone by cluster luck.  Models are useful in predicting things we cannot control, but for those in the midst of the game – players or entrepreneurs – the results have to be achieved, not just predicted.

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