Nov 5 2018
“Vilfredo Pareto was a respected economist and sociologist, which few people know. He invented the theory of Pareto optimality, which describes a maximum efficiency of the competitive economy. Better known to the general public for his empirical law of 80/20 (in general, 20% of the causes generate 80% of the effects), his reputation is in reality often reduced to the use of the diagram of the same name (that he did not even invent!)
And that’s where things go wrong. I’m sure you know this famous diagram, the one where you stack problems in pre-labeled columns. Those who know me know that most of the time, these famous diagrams (actually invented by Joseph Juran) generate in me a reflex of distrust…”
Sourced from LinkedIn Pulse
Michel Baudin‘s comments: Cécile Roche’s article has a clever title that works in English as well as in French. The body of the article, however, is in French, and I recommend Google-translating it into the language of your choice. The result won’t be perfect but you will get the gist.
Her experience with Pareto diagrams confirms the points I have been making about them in this blog. I agree with Cécile’s conclusions that they are good for slides but not as drivers for actual change. On the other hand, I don’t believe it has to be that way and I see many practical uses for the analysis behind the diagrams, if not for the diagrams themselves.
Cécile Roche’s Take On Pareto Diagrams
The main objections she elaborates on in her article are as follows:
- Pareto diagrams tell you what you already know.
- Generic categories, like “Supplier problems,” are useless.
- Drawing the diagram is storing problems instead of solving them.
- The best improvement opportunities may actually be in “trivial many” rather than the “vital few.”
As shown in Tradition, Tradition, Data Visualization, and Pareto Charts, the standard Pareto diagram violates many principles of chart design that have emerged since the 1940s. It also makes the point that, to use Pareto analysis in decision support, you are better off with a table of numbers than with the diagram.
Economists know Pareto better for his optimality concept than for the diagrams that Juran came up with later. If a factory’s performance were optimal, then you couldn’t change it in any way that would improve it. Pareto’s version of optimality differs. If it is Pareto-optimal, you can improve performance is some dimensions but only by making it worse in others. For example, you can reduce lead times, but only by sacrificing quality and increasing costs.
A Factory Can Always Be Improved argues that a factory is never Pareto-optimal. Optimal, in any sense, is a word that should actually be barred in manufacturing, because optimization is the opposite of continuous improvement. When a manager says “We’ve optimized this line,” it translates to “We won’t work on improving it.”
Uses for Pareto Analysis
If all you do is put a Pareto diagram in a management presentation, then, as Cécile points out, it’s a waste of time. Revisiting Pareto points out the uses of the analysis behind the diagram, not only to set priorities in solving quality problems but also to design production lines, structure warehouses, and organize logistics, based on a Pareto analysis of product volumes and component frequencies of use that breaks them down into Runners, Repeaters, and Strangers.