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[QualitiAmo - Stefania]

Su Lean Blog potete leggere un articolo dal titolo: "Measuring for Improvement ".

Questa è la versione tradotta in italiano con il traduttore automatico di Google.

When visiting the "gemba" at a few hospitals in England two weeks back (I saw five hospitals in three days), I heard a great expression at one London hospital:

"We're trying to shift from collecting data for judgment to
data for improvement."

Brilliant!

Even though I subscribe to Lean concepts like "the right process leads to the right results," my focus on process doesn't mean you ignore results. Process measures are important -- having the right measures, in a timely way is critical to any lean implementation.

When I've helped hospital in their initial lean implementations, we go from monthly measures that are often 4 to 6 weeks old to daily measures (or even, for example, laboratory turnaround times that are measured each shift). The right metrics, a small number, meaningful to staff, things they can have an influence on through their process (as opposed to complicated financial ratios) - that's what we put in place.

Measurement is like any tool - it can be used in good ways or bad ways.

Many organizations would focus on data for judgment sake. Which individual is performing well or badly? Maybe the variation is due to the system. I saw one large laboratory measure each phlebotomist's individual productivity every day.

That's OK, if those with low productivity are coached and mentored. If you have "data for improvement," you treat the people differently than if you're using the "data for judgment." Having measures shouldn't be used, in the old G.E. style, to fire the lowest 10% in phlebotomist productivity.

A lean leader would ask why their productivity is lower. Are they assigned to a part of the hospital where draws are more difficult? This might require a "gemba" view in addition to just measures. Was the employee not trained well or not trained the right way? There are a dozen questions you should ask before just firing or punishing somebody.

If you're using data for judgment, and people are in an environment of fear, all sorts of bad things can happen -- people will fudge the numbers or fudge the system. That's why we need data for improvement... the mindset and the philosophy that goes with the data and the measures, treating people the right way so they can focus on improvement instead of focusing on gaming the system.

What lessons have you learned along these lines? I feel like, sometimes, I could write a whole book on this subject. But, instead maybe read the works of Dr. Deming or the outstanding book by Dr. Donald Wheeler, Understanding Variation: The Key to Managing Chaos, probably the most influential book in my professional life.