PI CME: A Lesson from a Groundhog

February 7, 2010 at 5:06 pm Leave a comment

Authors Note: I couldn’t resist sharing this. There are lessons here for those of us interested in PI and PI CME.

What Can Punxsutawney Phil Teach About Performance Measurement?
Spend Matters, February 5, 2010 1:01 PM

Punxsutawney Phil saw his shadow on February 2nd; looks like six more weeks of winter. It has come to my attention, however, that his predictions have been right only 37% of the time. Born and raised in Lancaster County, Pennsylvania, I was more attuned to the predictions of rival groundhog Octorara Orphie, from the Slumbering Groundhog Lodge of Quarryville, PA, founded 102 years ago. This year Orphie predicted an early spring, as did a number of other woodchuck prognosticators. As they say, there are lies, damned lies, and predictive groundhog analytics. (By the way, if you’re interested in joining the Quarryville Slumbering Groundhog Lodge, you must be at least 35, as Slumbering Groundhogs must all be old enough to be President of the United States.)

With groundhogs demonstrating so many occasions of predictive inaccuracy, perhaps the KPI for the arrival of spring needs to be based upon more robust data. Since Punxsutawney Phil is correct only a little more than one third of the time, maybe the performance measure needs to be defined more clearly; in any case, how can you base the prediction of such an important event on the shadow of a rodent soothsayer? Besides, if you apply Six Sigma tools, you may find that there is too much variation in the conditions outside Phil’s burrow. Or, Phil himself probably needs a Gage R&R (gage repeatability and reproducibility) to ensure that his measurement system will produce reliable results. Perhaps Punxsutawney Phil needs to be replaced, possibly by automation, as suggested by PETA, who would prefer a cruelty-free robotic groundhog. But KPIs should be based upon an organization’s own goals, not on those of other organizations, such as PETA.

Now that we have some baseline data on Phil, we can begin to set some targets for improvement. We probably need to put in place some performance-improvement incentives, or a “carrot” approach, if you will. I’m not sure whether groundhogs eat carrots, but they do like sticks, suggesting the “stick” approach instead. If performance incentives do not prove effective, we should consider outsourcing Phil’s job to lower-cost counties in Pennsylvania, or following through on the automation threat. It’s a global economy, and predicting spring does not need to be performed by high-priced local rodents and their fancy top-hatted protégés.


Entry filed under: Improvement, PI CME.

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