Yearly Archives: 2015

From food cart to IPO in 10 years: innovation and “competitive capitalism”

In The only thing he ever made fly was government money, a post about the Wright Brothers’ government-backed competitor who failed badly, we wrote that:

The process of productive capital allocation is a critical ingredient of innovation and job growth. Entrepreneurs spending their own (and their partners’) money will create more jobs, more innovation, and a more vibrant economy than politicians picking winners and losers based on cronyism, campaign contributions, and constituent pork.

It is not an automatic process, of course. When $5,000 computers become $500 tablets, and conveniences ranging from steamships to Kodachrome to flip phones are supplanted by better ideas, the resulting surplus capital is not stuffed under plump mattresses – it’s used to fund the next round of businesses and innovations that enhance and enrich all our lives.  Including cheeseburgers.

Kevin D. Williamson points out that Shake Shack has gone from food cart to IPO over a period of time during which McDonald’s has struggled to tread water.  This might surprise some consumers but not likely anyone who’s worked for an archetypal big, faceless corporation (like McDonalds).  Start-ups may lack the economies of scale and R&D budgets of larger firms, but that’s the support venture capital can provide.  Those start-ups that do gain traction are able to raise capital, and, with hard work and a little luck, become large companies… who then face the next generation of start-ups.

Williamson goes on to make a broader defense of “competitive capitalism,” the aggregate effect of which is “indistinguishable from magic.”

(W)e are so used to its bounty that we never stop to notice that no king of old ever enjoyed quarters so comfortable as those found in a Holiday Inn Express, that Andrew Carnegie never had a car as good as a Honda Civic, that Akhenaten never enjoyed such wealth as is found in a Walmart Supercenter.

The irony is that capitalism has achieved through choice and cooperation what the old reds thought they were going to do with bayonets and gulags: It has recruited the most powerful and significant parts of the world’s capital structure into the service of ordinary people…

For people who dislike and misunderstand capitalism (or free markets, or laissez-faire, or economic liberalism, or whatever you want to call it), the governing principle of market competition is the “Walmart effect.” According to this model of how the economy works — a model with very little basis in reality, but never mind that — big companies such as Walmart muscle into a market or a territory, use advantages of scale and predatory pricing (“predatory” here meaning “saving consumers money at the expense of relatively well-off business owners”) to drive out so-called mom-and-pop operations, lower workers’ wages, and then make like Scrooge McDuck doing his Greg Louganis impersonation into a mile-high stack of hundred-dollar bills.

Big businesses vs. small businesses, employers vs. employees, factory owners vs. consumers: Every relationship in the marketplace is in this view distorted by power imbalances that almost always work in favor of entrenched business interests that use their relative power to further heighten the advantages they enjoy.

The opposite of the “Walmart effect” understanding of how the economy operates, a view more prevalent among people who like or simply understand capitalism, is the “Bill Gates’s nightmare effect.” Back in 1998, when Microsoft was at the height of its power — it had just become the world’s most valuable company — and Gates was at the height of his prestige, he told Charlie Rose that what worried him wasn’t competition from IBM or Apple or Netscape: “I worry about someone in a garage inventing something that I haven’t thought of.” That was in March of 1998; in September, two guys in a garage in Menlo Park incorporated Google.

It seems paradoxical, but failure is what makes us rich. Well over half of the companies on the 2009 Fortune 500 list began during a recession or bear market. The patents for the Television, Jukebox, and Nylon were granted during The Great Depression. Also born at that time: the chocolate chip cookie, Scrabble and Fender Guitars (kinda). The decline of U.S. Steel was bad for the company’s shareholders and its employees, but it was good for people who use steel — meaning everybody else in the world. Without the pressure and opportunity created by the possibility of failure the entire U.S. economy would be (at best) stuck in the early 19th century.

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 business, big 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.

The Luck Factor

In a bit of randomness courtesy of the interwebs this week, we stumbled upon a 12-year old article (and book) by Richard Wiseman, psychologist at the University of Hertfordshire, in which he argues that being lucky is an easy skill to learn and is based on four principles:  (1) creating or spotting chance opportunities, (2) listening to intuition, (3) creating self-fulfilling prophesies by expecting to be lucky, and (4) adopting a resilient attitude to bad luck.

As luck would have it, we’ve touched upon each of those four ideas here in our ongoing discussion of the role played by luck in sports and business.

(1) In Is there a process to introduce chocolate to peanut butter? we discussed the difference between luck and serendipity and how the right environment or attitude can foster the latter:

The term serendipity was coined in the 18th-century by novelist Horace Walpole, inspired by the Persian fairy tale about three princes traveling through the land of Serendip.  They “were always making discoveries, by accidents and sagacity, of things they were not in quest of.”  What distinguished their “abilities” from simple luck was that they could see meaningful combinations where others did not.

(2) We once wrote that good old-fashioned intuition has its place but it’s unwise to rely only on one’s instincts to decide when to rely on one’s instincts.

As we argued in Thinking consciously, unconsciously, and semi-consciously:  the best results often come from a combination of deliberation and intuition.  Too much deliberation can become analysis paralysis; and studies show that those who rely on intuition alone tend to overestimate its effectiveness.  (They recall the times it served them well and forget the times it didn’t.

(3) In A new envisagement of the world we quoted Samuel Eliot Morison’s 1943 Pulitzer Prize biography of Columbus to illustrate how his expectations of good fortune were not only self-fulfilling but became contagious:

At the end of 1492 most men in Western Europe felt exceedingly gloomy about the future. Christian civilization appeared to be shrinking in area and dividing into hostile units as its sphere contracted. For over a century there had been no important advance in natural science and registration in the universities dwindled as the instruction they offered became increasingly jejune and lifeless. Institutions were decaying, well-meaning people were growing cynical or desperate, and many intelligent men, for want of something better to do, were endeavoring to escape the present through studying the pagan past. . . .

Yet, even as the chroniclers of Nuremberg were correcting their proofs from Koberger’s press, a Spanish caravel named Nina scudded before a winter gale into Lisbon with news of a discovery that was to give old Europe another chance. In a few years we find the mental picture completely changed. Strong monarchs are stamping out privy conspiracy and rebellion; the Church, purged and chastened by the Protestant Reformation, puts her house in order; new ideas flare up throughout Italy, France, Germany and the northern nations; faith in God revives and the human spirit is renewed. The change is complete and startling: “A new envisagement of the world has begun, and men are no longer sighing after the imaginary golden age that lay in the distant past, but speculating as to the golden age that might possibly lie in the oncoming future.”

(4) In Deadlines, decisions, and cluster luck we lamented that although our hometown club was bouncing back from some bad luck, they were running out of time:

This article in Grantlandassessed 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 leveler 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.)

The NFL’s Best Coach*

Two days before Super Bowl XLIX this article about Bill Belichick appeared in Grantland.  It starts with a terrific journey back in time to young 9-year Billy cutting a homework-for-game-reports deal with his father – a well-known college football scout – and then travels forward to how he first made his bones as a defensive coach and then grew into an offensive master by constantly learning from his fellow coaches.

The author sees Belichick “bombarding opponents with shrewd, coldly rational tactics” and thinks his greatness “has never stemmed from the Big Idea, unless the Big Idea is the relentless application of many Little Ideas.”

It’s hard to win in the NFL, where most games are decided by small, often overlooked moments.  The great coaches, however, are adept at finding and exploiting seemingly infinitesimal advantages.  There’s a reason Bill Walsh called his book Finding the Winning Edge [for more detail, see The imperfect perfectionist – ed] and Don Shula called his The Winning Edge:  Gaining an “edge” is often the difference between winning and losing.  One doesn’t steward his team to 12 consecutive 10-plus-win seasons, as Belichick has, without an uncanny ability to identify and exploit the on-field edges that add up to wins.

But what about edges off the field?  It’s impossible to write about Belichick this week without raising the question.  Like almost all of his peers, Belichick isn’t above a little gamesmanship if it might help him win:  According to Halberstam, in order to slow down Buffalo’s no-huddle offense in Super Bowl XXV, Belichick told his Giants players to “accidentally kick the ball” away from the officials after it had been set up for play.

Each of the Patriots’ six Super Bowls is a testament to just how small that winning edge can be, with margins of just +3 +3 +3 -3 -4 +4.  But for two unbelievable catches by Giants receivers we’d be talking about an unprecedented 6-0 dynasty that averaged a championship every other year.  But for an unbelievable goal-line INT by an undrafted rookie community college graduate, we’d be talking about two different Brady/Belichick eras:  the first resembling the Aikman-led Cowboys of the early 90s, the second resembling the can’t-win-the-Big-One Vikings of the mid 70s.

The Grantland article includes a bit of catnip for those of you who like the X’s and O’s:  a defensive play designed around which way the center slides after the snap.  Talk about your “callous detail freak” looking for any edge.

We suspect his efforts to gain those “edges off the field” will also be a permanent part of his legacy.  His team hasn’t been in 6 Super Bowls over 15 years because of deflated balls, or illicitly videotaped signals, or (pre-Belichick) a snowplow driven by a convict on work release.  But you earn the reputation and invite the asterisks when you proudly display that same snowplow in an exhibit at your stadium.

To paraphrase the old adage: reputations are built over the long-term, and can be forfeited in just a moment.  In our business failure can be counted on to make (at least) a cameo, so it’s critical to learn how to fail the right way and make a distinction between business failure and personal failure.  An entrepreneur (or coach?) can try too hard to avoid an enterprise failure and pressure himself into a career-damning ethical lapse.

BPV often backs the same entrepreneurs in more than one business, and we view honesty and consistency as critical to sustaining long term relationships for long term growth as opposed to trying to squeeze maximum value from a single transaction.  We also 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.

FVF’s “state of the industry” panel with Robert Faber

Robert Faber (L) discussing our state’s entrepreneurial ecosystem.

This past Friday BPV principal Robert Faber helped cap off the 24th annual Florida Venture Capital Conference as part of the “State of the Industry” panel discussion.

The panel covered several topics, including: new non-traditional sources of capital attracted to our state’s (and region’s) attractive business climate, start-up valuations, and how critical it is for an entrepreneur to do his or her homework on potential venture partners.

BPVIII exceeds target, closes at $164 million, makes first investment

Ballast Point Ventures announces the final closing of its third venture capital fund. Ballast Point Ventures III and affiliates closed with commitments of more than $164 million, exceeding its initial target of $140 million.

Founded in 2002, Ballast Point Ventures provides growth equity venture capital to rapidly growing private companies in the Southeast and Texas. BPV has partnered with over thirty companies in its first two funds within its target industries of health care, technology-enabled business services, communications and consumer. The new Fund’s investors include large institutional investors, family offices and over sixty successful entrepreneurs.

“The BPV team appreciates the strong support of both our previous investors who have partnered with us again and a select group of new partners who are joining us in BPV III,” said Partner Drew Graham. “We are excited to continue helping entrepreneurs build outstanding growth companies throughout Florida, the Southeast and Texas, and we are encouraged by the high level of entrepreneurial activity we continue to see in the region.”

Ballast Point Ventures has been the most active investor in Florida companies over the past ten years.* Ballast Point Ventures III recently made its first investment in PowerDMS, a technology-enabled business services company based in Orlando, Florida.  PowerDMS provides technology solutions utilizing a Software-as-a-Service model in the Governance and Risk Compliance and Enterprise Content Management sectors.

“We have been fortunate to partner with an impressive group of talented and driven entrepreneurs,” said Partner Paul Johan. “We cherish those relationships and look forward to partnering with more great entrepreneurs as we invest BPV III. Successful private growth companies not only create tremendous value and often reinvent industries, but they also provide the vast majority of new jobs in this country.”

 ~

 * Growth equity and venture capital investments of at least $2 million in private Florida companies, based on 2003-14 data from the Dow Jones VentureSource database.

Moneyball moment for restaurants

Anthony Lye – President and CEO of portfolio company Red Book Connect – writes in Restaurant Hospitality magazine that widely available mobile and cloud technology have created a “Moneyball moment” for the restaurant industry.

The restaurant industry is having its Moneyball moment. Now that mobile and cloud technology are cheap and widely available, any restaurant can collect, analyze and act on huge swaths of data. Whether you have an Oakland A’s or New York Yankees budget, your restaurant has the ability to cut costs and increase profits by using big data that was invisible until recently.

When you collect in-store, near-store and above-store data, and then connect it all together in the cloud (i.e. on powerful computers located outside your restaurant), you see problems and opportunities that have gone unnoticed. You can begin to change conventional processes that have been killing your profit margins and losing you customers.

In-store data is all the information that comes from your restaurant. Your POS devices, fryers, refrigerators, temperature sensors and labor scheduling system can all communicate useful data. Combine them in the cloud, and you can detect patterns.

For example, one global restaurant brand learned that its fryers were a huge source of inefficiency. Five times per year, when they added new menu items, all 100,000 fryers had to be reconfigured and each required 30 minutes of labor. So, the company developed a way to push new instructions to fryers via the cloud. Now, an IT guy clicks one button, and all 100,000 fryers know how to cook the new menu item. It’s similar to the way Keanu Reeves learns Kung Fu in The Matrix.

By comparison, near-store and above-store data is all the information that originates outside the restaurant and above the restaurants in the company hierarchies. Near-store data includes weather, Yelp reviews, sports calendars, school holidays, special events and any other external data that could affect revenue and therefore the inventory and labor.

Normally, a good manager keeps an eye on the near-store data and adjusts inventory and labor based on experience or gut feel. When you instead connect all this data in the cloud and compare it against sales, both real time and historical, you can build much more efficient labor and inventory models for your restaurant. Instead of guessing, your managers forecast inventory and labor needs with fewer errors, all on their smartphones.

Related stories:

• Untangling skill and luck in sports and business
• The greatest comeback ever and the limits of decision models
• The super-rotation rivalry

Where are the start-ups? – Part II

6 years ago the number of business start-ups fell below the number of business failures, and it has yet to recover.  This leaves us a stunning 12th among developed nations in terms of business startup activity.

So argues Jim Clifton, Chairman and CEO of Gallup, who cites data that show 20 million of the oft-reported 26 million businesses in America are inactive.  Only a small % of the remaining 6 million are responsible for job growth:

Of those, 3.8 million have four or fewer employees — mom and pop shops owned by people who aren’t building a business as much as they are building a life. And God bless them all. That is what America is for. We need every single one of them.

Next, there are about a million companies with five to nine employees, 600,000 businesses with 10 to 19 employees, and 500,000 companies with 20 to 99 employees. There are 90,000 businesses with 100 to 499 employees. And there are just 18,000 with 500 employees or more, and that figure includes about a thousand companies with 10,000 employees or more. Altogether, that is America, Inc.

A common misconception lumps together “lifestyle” companies and high-growth start-ups. Job growth comes mostly from new businesses that grow rapidly, not the more common short-hand of “small businesses.” The jobs created by high-growth companies, busy inventing products and services (and sometimes industries), dwarf those lost in the ongoing employment churn experienced by small businesses. The net result is remarkably stable cumulative job creation from start-ups despite their high failure rate.

Mr. Clifton also writes that “Entrepreneurship is not systematically built into our culture the way innovation or intellectual development is.”  Very true, as this podcast from AEI argues in even greater detail.  The entire wide-ranging podcast is worth a listen. A few highlights:

• The economy needs more than a narrow rebound in tech entrepreneurship, especially since the current rebound has been accompanied by an uptick in “hardening” or consolidation as early firms are gobbled up before they boom.
• Using job creation as a measure is problematic because fewer people work for Twitter or Facebook than their previous equivalents – by the nature of what they produce. Michael Spence divides the US economy between the one that competes globally vs. the local market (tradeable vs. non-tradeable). The former generates national wealth but will employ fewer and fewer people; however, that’s what sprinkles money around the non-tradeable localities. “Not everyone can work at Google or Apple.”
• Innovation can be costly for individuals and firms in the short run, but is the key to wealth in the long run. E.g., productivity enhancements in low-tech/low-wage firms, consolidation that drives out less efficient mom&pops, and innovation that pushes stale incumbents out.

High profile firms such as Google and Facebook (hardly start-ups, anymore) enjoy outsized awareness because they’re personal and omnipresent, and belie the fact that the data show declining business dynamism overall and for start-ups specifically.  No one knows at the outset which high growth firms will explode and disrupt – so we need “more shots on goal.”

For every Facebook there are hundreds of other early-stage companies who receive financial backing and grow nicely. The economy is not built on a series of towering home runs that clear the fence no matter how strong the wind is blowing into the park. Winning takes singles, doubles, walks, anything that advances runners and scores runs. Over-regulating (or over-taxing) early-stage investment activity is like building a pitcher-friendly park and keeping the infield grass long: you better plan on low-scoring games.

Big Data in The Big D back in the Day

Before there was Moneyball, there was a little expansion football team in Dallas who invented Big Data (in sports) on their way to 20 consecutive winning seasons and 5 of the first XIII Super Bowls.  They managed to win just 2 of those 5, losing the others by 3, 4, and 4 points.

Yet even those losses serve as evidence in support of the idea of “Moneyball:”  Super Bowl V was so error-filled it’s an outlier known as “The Stupor Bowl,” while X & XIII were classics won by teams known for the type of big-game performances that can trump statistical strategies that need time for the math to work.

An immigrant statistician at IBM who knew nothing of football helped convert 260 scouting phrases (“he can run as fast as 2 cats“) into computer-friendly variables, input those into a giant box with less power than today’s laptops, and hired a psychologist to design a questionnaire sent to 10 scouts at 400 schools.  As a result, the Cowboys were able to uncover future Hall of Famers like Bob Hayes and Rayfield Wright at obscure colleges and fill roster spots with other athletes (e.g. basketball players & track stars) who’d never played one snap of college football..

Big 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 players in the midst of a game the reality is different.  Players don’t predict performance; they have to achieve it.

For more on this subject, please see Untangling skill and luck in sports and business, The greatest comeback ever and the limits of decision models, and March Madness and the availability heuristic.

This short video from ESPN films tells the Cowboys’ story.  Inspired by what GM Tex Schramm saw at the 1960 Winter Olympics – IBM had placed chips inside skis to collect data – they created the blueprint for the modern NFL out of thin air.

In honor of the playoffs, and invoking The Rule of 3… here are two more recent examples of how data is changing the NFL:

PART II – The Comeback of the Running Back argues that increased snap counts are favoring big-play running backs, especially as the game grinds on.

No running back was drafted in the first round of the last two NFL drafts. But general managers, coaches and scouts knew that the running game would return due to a mixture of economics and fitness. And now it has.

This season, running backs carved out a new role that looks like it will last: big-play specialists designed to exploit holes in today’s new-age defenses. Running backs may never be the focal point that they once were, but they are at least putting up a fight.

As the passing game gained prominence in recent years, two things happened: Linebackers and defensive backs shed weight to adjust to the new speed of the game, and up-tempo offenses resulted in more plays and more tired defenses. Those no-huddle offenses not only wore down defenses over the course of a game, but also the course of the season. This has led to exhausted defenses with lighter players who see hundreds more snaps than in the past…

To be sure, winning teams tend to run the ball more, especially late in games as they protect leads, leading to some statistical inflation. But NFL strategy wonks say that this development is much more than that. Worn-out defenses, which are using more defensive backs to defend the pass, are having a tough time bringing down lumbering running backs…

“People were focusing on the edges of the field, defenses were focusing on playing the pass and playing ‘basketball on grass,’ and what’s happening is the offenses are going back to oversize players, getting a power forward to go into the paint with those guys,” said former NFL general manager Phil Savage…

This is a classic phenomenon in sports: an undervalued commodity becoming valuable again because of a shift in how the game is played.

PART III – The Worst QBs Over 40 (Passes) points to data that suggests winning % drops off substantially when a QB – even an elite one – exceeds 30-39 pass attempts in a game.

Tasking any quarterback with videogame style pass attempts however, may be a losing strategy. The Count looked at the career records of the quarterbacks expected to start in this season’s NFL playoffs (except Arizona’s Ryan Lindley, who only has six career starts) and found that only New England’s Tom Brady (39-24, .619) and Indianapolis’ Andrew Luck (11-11, .500) have records of at least .500 when attempting 40 or more throws.