This post is coauthored by Innosight Managing Director Matt Eyring.
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. ...
Read the rest at Scott's Harvard Management blog, Innovation Insights.