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Measuring Performance May 14, 2009

Posted by Tim Rodgers in baseball, Management & leadership.
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I’m a huge baseball fan. One of the things that I have always enjoyed about being a fan is the challenge of measuring and comparing individual performance. For years the only measures that were commonly available were batting average, home runs, and runs-batted-in (for batters), and wins-losses and earned run average (for pitchers). It was better than nothing, but it certainly didn’t provide a very complete or accurate view of a player’s overall performance, and certainly didn’t help you understand their value to the team’s objective, which is to win games.

There has always been a lot of “conventional wisdom” imbedded in the game that strongly influences players, managers, sportswriters, broadcasters, and fans. It takes the form of deeply-held biases that are typically accepted without question and subconsciously guides their behavior.

Starting around the mid-1970s, a group of dedicated baseball fans and self-admitted statistical nerds realized that there are enough measurable events in a baseball game, and enough baseball games in a season, to collect a lot of data and draw statistically-significant conclusions. They didn’t blindly accept the conventional wisdom, they posed questions and gathered data and discussed the results. Sometimes the conventional wisdom was supported by data, other times it was found to be completely unsupported. This scientific approach has become known as sabermetrics, defined by their pioneer Bill James as “the search for objective knowledge about baseball.”

It’s a search that never ends, because there will always be questions without data, and even with data it may never be possible to completely describe performance or contribution with numbers. But … that doesn’t mean we shouldn’t use objective, quantitative measures to help understand performance, even if that leads to more questions.

I believe the same concepts apply in the workplace.

Managers should strive to establish objective, quantitative metrics for team performance, ensuring that those measures are aligned with the interests of the larger enterprise so that optimizing team performance directly contributes to the success of the business. Ideally, those metrics should be completely owned by the team, meaning that the results can be unequivocally attributed to the team’s performance alone.

Managers must put mechanisms in place to make it easy to routinely measure the data, and publish the results for wide distribution.

Performance should be measured over a period of time to establish a baseline before setting goals, but now I’m getting into process control principles and I’m going to save that for another post.

Individual performance must be aligned with the team performance metrics. In other words, if an individual is performing well, then that must be reflected in the team’s metrics, otherwise either the metrics are wrong or the performance isn’t contributing to the success of the team (or the larger enterprise).

Last point (for now): the process doesn’t end. Managers must use the data and the analysis to ask new questions, including whether these are the right metrics at all. The numbers will never tell the whole story, but there is no story at all without the numbers. The purpose is not to reduce all human effort to a set of charts and graphs. The purpose is to use the charts and graphs to challenge assumptions and test hypotheses and continuously improve.

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Comments»

1. Data and Information « Managing in the 2000s - December 6, 2011

[…] written before about the importance of making decisions based on objective data, see Measuring performance and Data Driven. I don’t think managers and leaders should wait until all the data is in […]


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