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The roots of unhappiness

A new working paperMW-CN870_happy__MG_20140718112128 from the National Bureau of Economic Research says NYC is the Most Unhappy City in America.

The study includes a national map of happiness in which it’s easy to see that our region is the most happy and its pockets of (relative) unhappiness are happier than other region’s least-happy pockets.  The researchers claim to have struggled to establish any patterns in the data:

The trio [of researchers] found that significant differences in happiness levels persisted even after they controlled for factors such as income, race, and other personal characteristics. The differences in happiness are significant, but not huge.

We have our own theories, expressed occasionally here, most recently in April 2013:

New evidence from the dismal science confirms what social science has already shown: the love of taxes is the root of unhappiness.

The original social science, from the December 2009 issue of Science, indicated that states with the highest taxes also have the least happy residents.  Residents of high tax states not only have less money to spend on other things that make them happy, they don’t enjoy many benefits in exchange for all their hard-earned tax dollars.  Roads, schools, and crime are no better (and in many cases worse) while their state governments borrow even more and spend disproportionately on public employee pensions and entitlement programs.  Their needs ignored at the expense of entrenched special interests, taxpayers get unhappy.  And then they get out.

From this one might argue causation; high taxes = unhappiness.  While we are certainly sympathetic to that point of view, we also have to wonder if it runs vice-versa, or at least cuts both ways: unhappy people like to raise taxes.

We are… happy.  And happy to report that’s true for our region as well.  NVSE readers already know that the Southeast’s advantages extend well beyond the matter of taxes and include lower public sector debt burdens, stronger job creation, the best climate for entrepreneurs, and a superior overall business climate.  (The actual climate happens to be conducive to a great quality of life as well.)

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3 BPV portfolio companies listed on the Inc 5000

imagesThree of our portfolio companies have been named to the Inc. 5000  list of the fastest growing private companies in America: one a communications company, one a business services/SaaS company, and one a healthcare company – all in Florida.

Congratulations to Orlando’s PowerDMS (4th year in a row), St.Petersburg’s  Tower Cloud (2nd year in a row),  and Miami’s TissueTech (1st year).

 

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Dead cats and iterative collaboration

Today is Erwin Schrödinger’s (he of the famous half-dead cat) 127th birthday.  We found this terrific excerpt from his 1933 Nobel Prize address:

If I am to have an interest in something, others must also have one. My word is seldom the first, but often the second, and may be inspired by a desire to contradict or to correct, but the consequent extension may turn out to be more important than the correction, which served only as a connection.

Though the tone of that quote echoes Sheldon Cooper of The Big Bang Theory. the content echoes a topic we like to cover here:  iterative collaboration.  From Hayek Was Right – Why Cloud Computing Proves the Power of Markets:

Many things about our company turned out differently than we had expected… The Hayekian knowledge problem is not a mere abstraction. Our innovations that have driven the greatest economic value uniformly arose from iterative collaboration between ourselves and our customers to find new solutions to hard problems.

Success is often achieved in incremental, adaptive fashion – with failure counted on to make a brief cameo at some point along the way. We love the collaborative imagery of a “correction” being a “connection” to the “extension” of an idea. Perhaps the great scientist ought to have received a Nobel for nerd poetry to go along with the one in physics.

Here is an explanation of his “thought experiment” that does, and doesn’t, kill a cat:

 

 

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A geographic analog to the process of creative destruction

The growth corridors of the high-tech South enjoy several advantages familiar to NVSE readers: growth-oriented tax policieslower public sector debt burdens, stronger job creation, the best climate for entrepreneurs, and a superior overall business climate.  (The actual climate happens to be conducive to a great quality of life as well.)

Additional proof now comes courtesy of the CATO Institute:  millions of Americans and trillions of annual income have migrated among the states, to the benefit of our region.

 

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Money walks because opportunity talks.

 

This migration of economic clout within the US has been more subtle than the California Gold Rush or Irish Potato Famine but is just as significant.  Some states are chasing away their earners, workers, and entrepreneurs; this is their tax base.

Daniel Mitchell (of CATO) picks one example (California) from the Tax Foundation’s map and concludes it’s a “slow-motion economic suicide.”

Voting for a tax hike isn’t akin to jumping off the Golden Gate bridge. Instead, by further penalizing success and expanding the burden of government, California is engaging in the economic equivalent of smoking four packs of cigarettes every day instead of three and one-half packs… In the long run, though, people can move, reorganize their finances, and take other steps to reduce their exposure to the greed of the political class.  In other words, people can vote with their feet … and with their money…

The state is going to become the France of America—assuming Illinois doesn’t get there first.  California has some natural advantages that make it very desirable. And I suspect that the state’s politicians could get away with above-average taxes simply because certain people will pay some sort of premium to enjoy the climate and geography.

But the number of people willing to pay will shrink as the premium rises.

In The Spread of Start-up America and the Rise of the High-tech South, Richard Florida, senior editor of The Atlantic combined Joseph Schumpeter‘s theory of creative destruction with Mancur Olson‘s theory for the rise and decline of nations and concludes that the Southeast would have a mercantile-like advantage but for the fact that employers can (and do!) simply move and join its attractive business climate:

Leading nations as well as leading regions, he (Olson) concluded, decline as a result of one overwhelming factor that he dubbed “organizational sclerosis” — a hardening of institutional, economic, and cultural arteries that leaves them incapable of dealing with a new and rapidly changing economic environment. Sound familiar? Practices, patterns, and norms of organizing and doing business that once worked so well become a constraint, a fetter, an obstacle to further progress. Decline sets in as once-dominant places get locked into the past and are unable to adapt to new circumstances, new technologies, and new conditions. A geographic analog to the process of creative destruction takes hold as new technologies, new business models, new values and norms, new industries and ultimately new institutions, and new ways of organizing economic activity shift to new places.

In Olson’s view the United States was fortunate, because it is a big country. While previous epochs of economic and geographic change tended to jump from country to country — moving, say, from Holland to England and later from England to the United States — America is so large that this process of rebirth and remaking can occur within its own boundaries.

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Deadlines, decisions, and cluster luck

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…

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.

keri-feature-clusterluck1

Last in cluster luck, first in (some of) our hearts

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.

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It’s unwise to rely on one’s instincts to decide when to rely on one’s instincts, redux

podcastartWe’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. PeteWho: 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.

 

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Interested, dedicated, fascinated by the job

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. 

~~~

Apollo_11_lunar_moduleAstronaut 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.

In a bit of serendipity we stumbled on this related post, from Richard Martin, which makes an interesting distinction between esprit de corps and teamwork:

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.

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Not all innovation is alike

innovationJames 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.

 

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CEOs are from Mars, VCs are from Venus – redux

mars venus

Borrow our title and we borrow your clever pic.

This article in Entrepreneur echoes (and borrows the title of) a post from our first month of blogging (November 2009):  CEOs are from Mars, VCs are from Venus?

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.

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.

 

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What California can learn from Texas

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.

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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.

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