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Yearly Archives: 2014
Our hometown ball club traded away its ace at the deadline yesterday. In an attempt to cheer ourselves up we fabricated a sports excuse to discuss data and decision making. We have done this before…
- Untangling skill and luck in sports and business
- The greatest comeback ever and the limits of decision models
- March Madness and the availability heuristic
Back to the Rays: models predicted they’d win 88 games this year and contend. What happened? To provide an answer we start with an earlier post of ours on Moneyball:
No conversation on this topic would be complete without at least a quick reference to perhaps the most popular or ubiquitous example of the Data vs. Intuition debate: baseball’s sabermetrics, a.k.a. Moneyball. Returning to the McKinsey Quarterly article:
The notion that players could be evaluated by statistical models was not universally accepted. Players, in particular, insisted that performance couldn’t be reduced to figures. Statistics don’t capture the intangibles of the game, they argued, or grasp the subtle qualities that make players great. Of all the critics, none was more outspoken than Joe Morgan, a star player from the 1960s and 1970s. “I don’t think that statistics are what the game is about,” Morgan insisted. “I played the Game. I know what happens out there… Players win games. Not theories.”
Proponents of statistical analysis dismissed Joe Morgan as unwilling to accept the truth, but in fact he wasn’t entirely wrong. Models are useful in predicting things we cannot control, but for players—on the field and in the midst of a game—the reality is different. Players don’t predict performance; they have to achieve it. For that purpose, impartial and dispassionate analysis is insufficient.
Next, Exhibit B: an article from three weeks ago in which Grantland assessed the playoff chances of all 30 MLB teams. Our Rays were playing well but digging out from the huge hole they’d surprisingly dug for themselves before the All-Star break. The conclusion? If the season lasted 262 games they’d have time for the bad “cluster luck” to turn around:
(T)he Rays can trace much of their heartache to cluster luck. I’ve written about hit clustering a couple of times this year, but here’s a quick recap: Over the course of a week, month, or even an entire season, certain teams’ hitters will bunch their hits together better than others, while certain teams’ pitchers will scatter their hits apart better than others. The Rays have been, by far, the least lucky team in baseball when it comes to hit clustering. As of Friday’s FiveThirtyEight piece, the Rays had lost a staggering 54 runs simply through poor hit-clustering luck, a full 20 runs worse than the next-unluckiest team, the Astros. As Peta noted on Twitter, the Rays have turned double plays on less than 5 percent of the baserunners they’ve allowed, an abnormally low number that’s also the worst in baseball. Some of that is due to defensive slippage, as Ben Zobrist and especially Yunel Escobar are seeing their range start to tail off as they age. But most of it is likely a giant fluke.
Cluster luck also very likely explains their torrid streak since that article was published. One of the things baseball fans like to point out about their sport is that the length of the season tends to be a great leveller of performance. In this case, there is just too little time for the reversion to mean to accomplish a miracle (for Ray’s fans, including some of us.)
This fits well with what we’ve previously written about the role of luck in business, investing, and sports: it’s influence is greater than ever because technology and best practices are so widely disseminated and articulated.
The difference between the very best players and the average players is less today than it was in the past. If skill is more uniform, and luck stays the same, that means luck actually becomes more important in determining outcomes. It’s everywhere you look. But one area where you can see it very readily is in sports: In 1941, Ted Williams became Major League Baseball’s last player to hit over .400 in a single season. Why has no one been able to do that since? The answer is because skill is much more uniform today.
We’ve written frequently on the subject of cognitive biases and how to design decision making processes to account for them. A good process will entail astute management of the social, political and emotional aspects of decision making and address or at least understand the underlying biases of the participants.
We recently came across this piece in the archives at HBS Working Knowledge which introduces research on “fundamental attribution bias” (a.k.a. snap judgments), and how resistant that bias is to cures. Apparently it is so deeply rooted in our decision making processes that even highly trained people, warned explicitly of its dangers, remain susceptible.
People make snap judgments all the time. That woman in the sharp business suit must be intelligent and successful; the driver who just cut me off is a rude jerk.
These instant assessments, when we attribute a person’s behavior to innate characteristics rather than external circumstances, happen so frequently that psychologists have a name for them: “fundamental attribution errors.” Unable to know every aspect of a stranger’s back-story, yet still needing to make a primal designation between friend and foe, we watch for surface cues: expensive pants—friend; aggressive driving—foe.
The research looks at highly trained professionals – college admissions officers and hiring managers – and finds “how difficult it was to counteract the fundamental attribution error, and, particularly, how strongly its effects could be seen in these records.”
The first study asked professional university admissions officers to evaluate nine fictional applicants, whose high schools were reportedly uniform in quality and selectivity. Only one major point of variance existed between the schools: grading standards, which ranged from lenient to harsh. Predictably, students from “lenient” schools had higher GPAs than students from “harsh” schools—and, just as predictably, those fictional applicants got accepted at much higher rates than their peers.”We see that admissions officers tend to pick a candidate who performed well on easy tasks rather than a candidate who performed less well at difficult tasks,” says Gino, noting that even seasoned professionals discount information about the candidate’s situation, attributing behavior to innate ability.
Similar results can be seen for the second study, in which the researchers asked business executives to evaluate twelve fictional candidates for promotion. In this scenario, certain candidates had performed well at an easier job (managing a relatively calm airport), while others had performed less well at a harder job (managing an unruly airport).
As with the admissions officers, the executives consistently favored employees whose performance had benefited from the easier situation—which, while fortuitous for those lucky employees, can be disastrous on a company-wide scale. When executives promote employees based primarily on their performance in a specific environment, a drop in that employee’s success can be expected once they begin working under different conditions, Gino explains…
“We thought that experts might not be as likely to engage in this type of error, and we also thought that in situations where we were very, very clear about [varying external circumstances], that there would be less susceptibility to the bias,” she says. “Instead, we found that expertise doesn’t help, and having the information right in front of your eyes is not as helpful.”
The researchers do not yet have recommendations to offer as it relates to hiring, but we might have one in The Library at St. Pete: Who: The A Method for Hiring by Geoff Smart and Randy Street. The book outlines a hiring process that reduces the risk of making a bad hire – the costs of which can be great.
Today marks the 45th anniversary of the Apollo 11 landing and the first steps by humanity on another world. In honor of the man who took those first steps, we’d like to reprint the 8/28/12 piece we wrote on the occasion of his passing.
Astronaut Neil Armstrong passed away Saturday, and The Wall Street Journal reported something the pioneer once said about the success of the 1969 Apollo 11 mission – the odds of which he had placed at 50/50.
Mr. Armstrong described the required reliability of each component used in an Apollo mission – statistically speaking 0.99996, a mere 4 failures per 100,000 operations – and pointed out that such reliability would still yield roughly 1000 separate identifiable failures per flight. In reality, though, they experienced only 150 per flight. What explained the dramatic difference?
I can only attribute that to the fact that every guy in the project, every guy at the bench building something, every assembler, every inspector, every guy that’s setting up the tests, cranking the torque wrench, and so on, is saying, man or woman, “If anything goes wrong here, it’s not going to be my fault, because my part is going to be better than I have to make it.” And when you have hundreds of thousands of people all doing their job a little better than they have to, you get an improvement in performance. And that’s the only reason we could have pulled this whole thing off. . . .
When I was working here at the Johnson Space Center, then the Manned Spacecraft Center, you could stand across the street and you could not tell when quitting time was, because people didn’t leave at quitting time in those days. People just worked, and they worked until whatever their job was done, and if they had to be there until five o’clock or seven o’clock or nine-thirty or whatever it was, they were just there. They did it, and then they went home. So four o’clock or four-thirty, whenever the bell rings, you didn’t see anybody leaving. Everybody was still working.
The way that happens and the way that made it different from other sectors of the government to which some people are sometimes properly critical is that this was a project in which everybody involved was, one, interested, two, dedicated, and, three, fascinated by the job they were doing. And whenever you have those ingredients, whether it be government or private industry or a retail store, you’re going to win.
Interested, dedicated, fascinated by the job – Armstrong’s explanation could serve as an excellent description of the esprit de corps we find in good private growth companies. Not too long ago we quoted Ben Dyer, president of Techdrawl, about how entrepreneurs need to inspire all the members of their team to share the founder’s drive in the early stages of a company:
All those textbook methods of performance reviews, pay incentives, etc. will come in handy when you get to the 50th or 100th employee, but right now you’ve got to be the one out front – with inexhaustible energy, enthusiasm, creativity, and a clearly articulated vision.
Cohesion and esprit de corps are even more intangible. Where teamwork is built on the willingness of individual team members to subsume their own interests in favor of group interests, esprit de corps is built upon the willingness to sacrifice oneself, if needed, for the interests of the group. This is a level of commitment that few organizations in business achieve.
Mr. Armstrong described himself (with characteristic humility) as: “I am, and ever will be, a white-socks, pocket-protector, nerdy engineer.” Perhaps that, and a bit more, Sir. Godspeed.
James Pethokoukis at AEI makes a distinction between “efficiency innovation” and “empowering innovation.” The former can contribute to a polarized job market, while the latter is the necessary ingredient for a vibrant economy and improved living standards:
Not all innovation is alike. Incumbent firms replacing man with machine is a kind of innovation that may lift corporate profits and boost stock prices without necessarily broadly raising prosperity. Such technological advancement and efficiency is already contributing to polarized employment markets in advanced economies. Jobs are created at the top for high-creative workers and at the bottom for high-touch workers. But jobs in the middle— especially those involving routine, repetitive, and rules-based tasks—are automated away. In other words, the executives and janitors at a bank keep their jobs, but tellers get replaced by ATMs.
But there is another kind of innovation, termed “empowering” innovation by business consultant Clayton Christensen. This is the sort of innovation generated by fast-growing startups offering new products and services. Empowering innovation is a job creator, not a job destroyer—though some jobs may shift from uncompetitive incumbents to these aggressive new challengers.
Both sorts of innovation have their place, of course. But right now efficiency innovation may be destroying jobs faster than empowering innovation creates them. So what is the key to generating greater levels of empowering innovation? Competition—and the more the better. As economist Joseph Berliner once put it:
(T)he effect of competition is not only to motivate profit-seeking entrepreneurs to seek yet more profit but to jolt conservative enterprises into the adoption of new technology and the search for improved processes and products.
Vibrant economies need plenty of fast-growing startups to generate empowering innovation and to also push incumbents themselves to become more innovative.
And if incumbents can’t compete, government needs to let them fail. Free and frequent entry and exit of firms is critical. Government has to make sure tax, regulatory, and spending policy is neither impeding the creation of new startups nor giving incumbents an unfair advantage.
Some politicians think “innovation policy” means spending taxpayer money on promising young firms favored by bureaucrats. Rather, innovation policy means ensuring that the status quo is continuously challenged by upstart rivals and threat of failure. Those are the keys to the Schumpeterian “gales of creative destruction” that drive innovation, which in turn drives long-term economic growth and improvement in living standards.
National prosperity is generated by the start-ups who innovate and challenge entrenched incumbents. Anyone who’s worked for a large corporation – especially in an R&D department – would not rely primarily on that model for innovation. Anyone who’s worked for a large corporation – especially in a dying industry – would not rely primarily on that model for job growth. Yes, start-ups lack the economies of scale and R&D budgets of larger firms; but that’s the support venture capital provides. Those start-ups that do gain traction are able to raise capital, and, with hard work and a little luck, become large companies… and then face the next generation of innovators.
Back then we cited a joint study conducted by the NVCA and Dow Jones which outlined several factors that contribute to a good long-term partnership for long-term growth, and highlighted two data that we found insightful band mildly humorous:
Do you respect me or my money?
- 54% of VCs cite mentoring the CEO as a critical value-add; only 27% of CEOs see the value.
- 64% and 34% of CEOs see the ability to complete follow-on financings and facilitate exits as top value adds; VC numbers were 48% and 22% respectively.
The money will always be important. After all, entrepreneurs should pick a financial partner who can provide additional capital as needed as their companies grow. But the best (sadly, not all) venture partners provide much more than money – valuable contacts, “been there, done that” experience when facing tough business issues and a sympathetic sounding board for entrepreneurs working under great pressure.
As was the case with another contributor at a different publication, the author of the Entrepreneur piece is either subconsciously thinking mostly about early-stage venture financing or is perhaps painting with too broad a brush. But he still makes a few valuable points:
Ultimately, Gray’s [author of the 1992 book Men are from Mars, Women are from Venus – ed] advice for better relationships applies: If founders and capital providers invest the time to understand their objectives deeply, they will have a productive relationship. The key is to find activities where they can make the other party better off.
Or, if you prefer, as we once put it in The fate of control (also from 2009):
It’s more about chemistry than control. How you react during the inevitable challenges of building a business together will define the relationship. Over time you learn to play to each other’s strengths and make the concessions and adjustments that a given situation demands.
When a state’s manufacturing base is escaping, and its citizens are agitating to break up, that state is no stranger to bad news. AEI’s Carpe Diem blog reports: Texas has created one million more jobs than California since the end of the Great Recession.
What’s different about Texas and California that would explain why one state (Texas) has added more than one million net new jobs since 2007, while the other (California) has created almost no new net jobs over the last six and-a-half years? Let’s start by pointing out that one of those states — Texas — is pro-energy (i.e. fossil fuel energy), it’s a right-to-work state, it has no state income tax, its electricity prices are significantly lower because it doesn’t have a renewable energy mandate, and its regulatory burden on businesses is much lighter. In other words, Texas has created a pro-business and pro-growth environment that has helped to nurture the creation of more than one million jobs since December 2007. Meanwhile, California has created an increasingly anti-business climate with some of the highest state tax and regulatory burdens in the country, which along with sky-high industrial electricity prices (83% higher than in Texas), have stifled business and job creation, with almost no net job gains in more than six years.
Nearly all who signed the Declaration of Independence ran their own businesses. The Big Names, the Renaissance Men, have familiar stories; yes. But it is true of most of the less well known signatories as well.
George Washington’s success as an entre- preneur recently earned him the moniker Founding CEO. Born neither poor nor rich, with a father who died while he was just 11 years old, Washington transformed Mount Vernon “from a sleepy tobacco farm into an early industiral village.”
Ben Franklin ran several businesses and never patented a single of his many famous inventions, seeing them as gifts to the public. An early open-source advocate?
Thomas Jefferson invented many small practical devices (e.g. the swivel chair) but, like Franklin, had no interest in commercialization. Furthermore, if you count these sorts of things as entrepreneurial – and we do – he founded the University of Virginia and the middle part of the country known as The Louisiana Purchase. Jefferson however (and unhelpfully) was not exactly a huge fan of finance:
The system of banking we have both equally and ever reprobated. I contemplate it as a blot left in all our constitutions, which, if not covered, will end in their destruction, which is already hit by the gamblers in corruption, and is sweeping away in its progress the fortunes and morals of our citizens.
Letter to John Taylor, 1816
Well, nobody’s perfect. That kind of attitude is what lands you on the $2 bill. More seriously, his view of banks seems to have reflected his distaste for public debt and inter-generational debt. (He inherited his father-in-law’s estate and its debts, which took years to pay off and contributed to his own personal financial difficulties.) We can imagine he would have felt differently about the type of financial backing that allowed yeoman entrepreneurs to pursue happiness.
This 2013 piece by Bill Murphy Jr. in Inc. magazine tells the stories of the less famous self-made men behind the Declaration of Independence: “Doctors, lawyers, merchants (and a few ne’er do well heirs).” The merchants were entrepreneurs, obviously, but even those doctors and lawyers would have had an entrepreneurial bent, typically arranging their own educations or apprenticeships, hustling up clients, and running the business end of their own practices.
We hope all our readers and their families enjoy a Happy Independence Day.
Today’s Wall Street Journal reports: since 2005 productivity has declined 8% off its long-run trend, which has meant $1 trillion less in business output. The reason? Fewer start-ups. From Behind the Productivity Plunge: Fewer Start-ups
Lagging productivity growth is an enormous problem because virtually all of the increase in Americans’ standard of living is made possible by rising worker productivity. In our view, an important factor contributing to declining productivity growth is the large decline in the creation of new businesses. The creation rate of new businesses, as well as new plants built by existing firms, was about 30% lower in 2011 (the most recent year of data) compared with the annual average rate for the 1980s. (The data is the Census Bureau’s Business Dynamic Statistics.) The decline affected nearly all business sectors.
Steven Malanga coined the term startupicide – “suffocating regulations, inflated business taxes and fees, a lawsuit-friendly legal environment, and a political class uninterested in business concerns” – which gets sprayed on every business, large and small. At the margins those factors clearly affect the viability of new businesses and new projects. Here’s how we once put it, discussing just one of the four ingredients:
For Costco (one example) to build a new store, a 40% tax rate on the income will require much higher sales expectations for the store than if taxes were 30%, or 20%, or 0%. It’s the same analysis regardless of who is making the investment decision: rich angel investor, venture capitalist, Fortune 500 CFO. When taxes are higher, fewer stores get built and fewer companies get started.
The WSJ piece continues:
New businesses are critical for the U.S. economy to grow because a small fraction of today’s startups will become tomorrow’s economic heavyweights. Most of today’s workers are employed at older, established businesses, but the country cannot rely on existing companies to boost the economy. Businesses have a life cycle, in which even the largest and most successful reach a stage at which they stop expanding.
If history is any indication, many of today’s economic heavyweights will ultimately decline as new businesses take their place. Research by the Kaufman Foundation shows that only about half of the 1995 Fortune 500 firms remained on the list in 2010.
That’s the funny thing about those large companies: they all have birthdays, either as start-ups themselves or as spin-offs from other companies (who were once start-ups). Many of them are born during very bad times – as long as the entrepreneurial incentives, and entrepreneurial optimism, remain intact.
Over half the companies on the Fortune 500 were started during a recession or bear market. The patents for the Television, Jukebox, and Nylon were granted during the greatest period of job destruction in our history: The Great Depression. (Although we can’t confirm any patent information on the chocolate chip cookie, it too was invented at the same time.) This is precisely the creative destruction that makes our economy an engine of innovation and wealth creation.
That $1 trillion in forfeited economic output demonstrates that a growing economy, with plenty of opportunity, and no shortage of entrepreneurial activity (at start-ups and within firms) should not be taken for granted.
This article on valuation from the Houston Business Journal is written from the point of view of middle-market investment banking, but it’s also relevant to term sheet negotiations between entrepreneur and venture capitalist. Higher EBITDA doesn’t automatically lead to higher multiples (and higher valuations).
The reality is that valuations are much more complex and are primarily a function of the underlying fundamentals of a business. These fundamentals might include growth opportunities, recurring revenues, customer and product diversity, entry barriers, proprietary products and high levels of free cash flow. Our experience tells us that different buyers can have widely divergent views of value based on their relative assessments of these underlying fundamentals…
It is important for private business owners to understand valuation drivers and to develop the financial and operating data that will enable buyers to properly assess the underlying fundamentals of their business. More clarity for a buyer leads to a higher level of confidence and a more attractive valuation for the seller.
It also leads to a higher level of confidence in the relationship. The early conversations about valuation (and control) begin to shape the personal chemistry crucial to a successful long-term partnership. Clarity and transparency, which make it easier for everyone involved to observe how decisions are being made, are much more important to hopeful-future-teammates than either side trying to squeeze maximum value out of a single transaction.
If a good tone is set early and maintained consistently, over time everyone on the team worries less about who’s in control and more about how to create the best scoring opportunity.
Here is the long-overdue “VIth” installment of our Vintage Future series, in which we take a tongue-in-cheek look back at the predictions of past generations of investors and futurists.
In our line of work it’s good to guard against the hubris inherent in projecting conventional wisdom too far out into the future, and to remind ourselves that today’s trend can be tomorrow’s punchline.
Predicting technology trends is not for the weak at heart – and that’s before one tries to protect the IP and find a way to profit from it.
These are among the reasons we affectionately call the really early stage of investing adventure capital, and consider ourselves a “growth accelerator” for established, rapidly growing businesses with strong management teams. We prefer to focus our efforts on assessing competitive and execution risk rather than product or business model risk, and we want to see tangible evidence of the unique value offered by a company’s product or service.
N.B. – previously featured in Vintage Future:
- Nine Technologies That Will Change Your Future
- Innovative Products from the Past that Never Were
- Ten Worst Internet Ideas
- William Shatner narrating MicroWorld 1980
- Crazy Patents
- The Chef of the Future.