Voices » Scott Anthony » Innovation Lessons From the Baseball Draft
8:36 AM Friday June 6, 2008

This article is coauthored by Innosight Managing Director Matt Eyring.
The Major League Baseball draft is a relatively quiet event, at least compared to higher-profiles drafts in football and basketball. But the complexity and minutiae of the MLB draft--and what happens after the draft--deserves the most attention for those looking for innovation inspiration.
Seeing coverage of this week's baseball draft made us realize how much companies can learn about innovation from watching how great baseball teams manage their early portfolio of talent.
Baseball teams have to assemble the best talent possible, just like companies have to bet on the best innovation opportunities. A baseball team chooses between acquiring talent on the free agent market or drafting and building talent. A company chooses between acquisitions or organic growth.
Acquisitions are expensive, but perceived to be lower risk, because the talent (or idea) has proven itself demonstrably in the marketplace (for baseball, that means success on a major-league diamond). Organic growth is typically cheaper, but perceived to be risky because many times highly touted initiatives or prospects don't pan out.
Baseball teams know that talent follows a power-law pattern, where for every 1,000 players there are 100 players that are capable of playing at major league levels, 10 of whom are legitimately good players, and 1 of whom is a true superstar. The same is true for innovation.
The challenge is: Which project or which player? Just as a baseball team doesn't have complete information about what a player's true level of ability is on draft day, you don't know the real potential of any one innovation project.
Both of you are forced to deal with incomplete data. A team has to rely on a mix of limited performance data at the high school and college level and an assessment of a player's inherent skills. Good teams collect as much data as possible. They have sophisticated models to project how rough performance can project to the major league level. Good teams also let past patterns inform their decisions. High school pitchers? Very risky. College hitters? Much less risky.
With a well-organized scouting team, you should gather multiple data points in preparation to "draft" innovation opportunities. Get the very best market data you can, look at past successes and failures to see what lessons you can glean, and use qualitative metrics or patterns to guide decisions.
Teams recognize that not all draft picks will pan out. So they immediately expose them to tougher competition in the minor leagues. Similarly, you must find ways to test your critical assumptions as quickly and cheaply as possible by "exposing" your innovation to simulated market conditions. That might involve showing a customer a prototype, or running a limited test market.
Sometimes players go through the system quickly. Sometimes it takes a few years before they develop their skills. Sometimes it is clear that a projection was wrong and it's time to cut bait. Similarly, you must make quick decisions about which projects to accelerate, which to fine-tune, which to decelerate, and which to shut down.
How about that balance between acquisitions and organic growth? Baseball teams are learning that the quirks of the collective bargaining agreement mean that it's far better to be world-class at talent evaluation and lock up young talent early than it is to seek to acquire talent on the free agent market.
This is because by the time a player is eligible for free agency, their best years are often behind them. A limited free agent market leads to artificial scarcity, which means teams often pay above-market rates for players with declining skills.
You can learn a key lesson from this baseball dynamic. The market for acquisitions that are big enough to impact large companies is very thin, meaning companies often need to pay above-average rates for acquisitions.
Of course, the market for companies is more liquid than the market for baseball players. We bet you if you ran the data (and surely someone at Baseball Prospectus, The Hardball Times, or Baseball Think Factory has) the absolute best return on investment would be acquiring a hitter who has proven himself at a critical midpoint--perhaps at the second-tier double-A minor league level. Passing that hurdle greatly increases the odds that a player will succeed at the major league level. Ask yourself: What is the equivalent inflection point in our market?
As you look at your innovation portfolio, think of yourself as general manager approaching the draft. Place a lot of well-informed bets, using a variety of qualitative and quantitative inputs. Expose those bets to the market as quickly as possible. Recognize that not every bet is going to pan out. Accelerate the development path of the best resources, and shut down the rest.
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Scott D. Anthony is the president of Innosight, an innovation consulting and investing company with offices in Massachusetts, Singapore, and India. He has consulted to Fortune 500 and start-up companies in a wide range of industries. During 2005–2006 he spearheaded a yearlong project to help the newspaper industry grapple with industry transformation (Newspaper Next).
Anthony is the lead author on The Innovator’s Guide to Growth: Putting Disruptive Innovation to Work (Harvard Business School Press, 2008). He previously coauthored (with Harvard professor Clayton Christensen) Seeing What’s Next: Using the Theories of Innovation to Predict Industry Change (Harvard Business School Press, 2004).
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Comments
That's a fairly valid analogy but the analogy breaks down when it comes to innovation because ALL drafted baseball players, even very young ones, have track records of some kind which can be studied, and past performance can indicate whether future success is likely or not. In fact, the most savvy baseball teams use extremely sophisticated statistical analyses to do just that.
However, when it comes to innovation, and especially breakthrough innovations, we have no such past history to help us determine whether an investment will be a winner or not. Sometimes we're going on pure instinct. In fact, if we apply the draft methods of baseball teams to innovation portfolios, chances are we'll end up with a very safe one with little risk and little reward. This is just another example of why investment in innovation is such a tough sell. Would it be as predictive as the MLB draft.
- Posted by Val Vadeboncoeur
June 12, 2008 11:25 PM
I don't see Innovation as being like baseball with winners, losers, superstars and benchwarmers. Innovation is like markets; there is a perfectly legitimate market for a Porsche and there is a perfectly legitimate market for a Kia - in fact, the Kia market is far greater than the Porsche market. The majority of value generated by an innovation, say, a Microsoft product - is not from the inventors, but the billions of average people whose productivity was increased by a relatively small amount collectively supporting the value of a national currency.
The definition for innovation is flawed. As inferred in this article, innovation is defined as some new idea that makes a ton of money. Mathematically, this describes one equation with two unknowns which is essentially unsolvable. Obviously only the 99th percentile Rubik Cuber can solve the puzzle - if they are born lucky - that's why it resembles baseball, or golf, or tennis, or whacking any hard object with some type of club.
Suppose instead we split innovation into two definitions, a primary and a secondary. The primary definition is that Innovation is defined as the rate of change of knowledge with respect to time (all the ah-ha moments) where knowledge is defined as the rate of change of information with respect to time (all the analysis) where information is defined as facts and data. In order to measure innovation, one simply needs to identify high rates of change of knowledge WRT. The secondary definition is the value proposition, i.e., if a lot of people are becoming more productive because of the high rate of change of knowledge WRT, then it must have value.
Now we have a game that anyone can play, a few will always be Porsches anyway, but most will be Kias solving real problems for real people.
- Posted by Dan
July 1, 2008 1:35 AM
Let us not confuse normal business or product development with "Innovation"...although it's nice to lump everything together under the Innovation banner...that is hardly realistic!
- Posted by R.Vosari
July 1, 2008 3:39 PM