Laws of Leadership: The Pareto Principle in Practice

Ever go into a meeting and see a Pareto Chart that is linear? Or maybe there is a slight rise at the top... but clearly it's not in accordance with the Pareto Principle?

Pareto Principle: Also known as the 80/20 rule, it states that roughly 80% of effects come from 20% of causes—in ops, 80% of downtime might stem from 20% of factors.

This one is essential for setting priorities in a leadership role.

When leading change, the temptation is to pull the most easily accessible data, crank it into a Pareto Chart, and talk about the largest bar.

But that's not really the right use of the Pareto principle. If the data you're looking at doesn't adhere to the Pareto principle, that’s a hint that the data you're looking at doesn't represent the problem correctly.

The Pareto Principle doesn't just tell us where to look, but also where NOT to look.

Example: The same data (e.g., 100 hours of downtime) can be sliced by fishbone components: huMan (operator, shift, supervisor), Machine, Method (job/die), Material (application), Measurement, Environment.

No matter how you slice it, you will get a chart and there will be a largest bar, even if the factor you sliced it by is not a factor at all.

However, if you cut the data by each factor (fishbone components) to see which yields the steepest Pareto distribution (steep 80/20 curve), that will reveal the answer you seek.

Machine downtime, for example, may yield a linear relationship while "by operator" may show a Pareto distribution. If that happens, you need to work "by operator.”

If you find the correct distribution and take the top cause, then you need to break out all of your KPIs on just that top bar to see where the top factor is different from average.

In our example, perhaps we find out that the largest bar in "top operator" has 6x as many feeder stops as the department average. Now you know who is struggling and what training will fix it.

You can create a lot of burn-out by attacking the largest bar on a chart with no Pareto distribution, it overwhelms teams, dilutes efforts, and delays real progress.

The proper approach is to find a Pareto distribution, then dissect the top bars with whatever metrics you have to understand why they're producing such downtime/quality issues/financial losses etc.

Leading change is hard. Understanding the Pareto Principle helps us target the right actions.

Change leadership is a marathon. You can't chase every rabbit or you simply won't succeed.