People Innovation Excellence
 

Systems Engineering By Ricardo Valerdi

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ISE Magazine –Volume: 49, Number: 08

What we can learn from baseball analytics

The U.S. baseball industry has heavily invested in analytics. Finding inefficiencies has given teams and coaches a slight edge over their competitors that may translate into more wins per million dollars (win efficiency) and additional revenue through tickets, corporate sponsorship and television contracts (franchise value). An example of using analytics for competitive advantage is in the book Moneyball, which suggests:

  • Players should be evaluated on past performance rather than potential.
  • Certain metrics are overvalued, rewarding individual behavior rather than team behavior.
  • There is hidden value in recruiting often overlooked players who value team performance rather than expensive superstars who value individual accomplishments.

Applying Moneyball-type thinking to engineering projects might help organizations find hidden value and operate efficiently and effectively. My favorite is “win differential,” which is used to isolate a player’s ability to help a team win. A team’s likelihood of winning a game can be quantified in terms of probabilities throughout the game and is driven by multiple factors. One factor is the progress of the game. Since there is no game clock in baseball, progress is measured by the number of outs recorded. With some exceptions, a typical baseball game has 27 outs for each team (three outs each inning, nine innings total). If the score was 5-0 at the beginning of the game, i.e., with six outs recorded, the probability of win for the team that is ahead will be lower than if the same score existed toward the end of the game, i.e., with 26 outs recorded.

The events that lead to offensive production of runs or defensive production of outs can be attributed to individual player contributions. Winning probability difference places an emphasis on how a player helps the team on offense and defense.

The analog to engineering projects also pertains to the probability of a successful outcome, which may be cost-, schedule- or performance-based. A member of the project team may accomplish a certain milestone, technological breakthrough, customer approval or test that may increase the likelihood that a project will be successful in the end. There are optimistic expectations that it will be completed on time. If these estimates were updated at each significant event, the team would know its likelihood of success.

An important difference between baseball and engineering projects is the role of external factors that influence the outcomes. In baseball, most outcomes are decided by skill or luck. Some are influenced by external factors like weather or crowd noise. In engineering, external factors like personnel turnover, market forces and customer delays might play a more significant role in success.

Measuring certain things may lead to a desirable change in behavior in the short term but not in the long term. The point is to provide a different view to the way engineering projects are measured by borrowing from the playbook that professional baseball teams use to measure and evaluate players.


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