Pareto analysis

Pareto analysis ranks the possible causes or categories behind a problem by how much of the total impact each accounts for, typically shown as a bar chart ordered from largest to smallest contributor with a cumulative percentage line overlaid. It takes its name from the Pareto principle, the loose observation that a small share of causes, often characterized as around 20%, tends to account for a large share of the effect, often characterized as around 80%, though the exact split varies by situation and should be measured, not assumed.

In practice, a team investigating support tickets, defects, or churn might tally how many cases fall into each category, order categories by count, and find that fixing the top two or three explains most of the volume, making them the priority over a long tail of rarer causes. This differs from a general root cause analysis in that it is specifically a prioritization tool: it tells a team where to look first, not why a given cause occurred.

Pareto analysis matters because effort is finite and problems rarely have a single cause; it directs resources toward the categories with the largest measurable payoff. The main pitfall is treating the 80/20 split as a law rather than a pattern to verify, and lumping dissimilar issues into one category just to make it look like the biggest contributor.