Root-Cause Pareto

A Pareto chart is easy; a Pareto that survives challenge in a management meeting is not. The difference is four disciplines applied before the chart exists.

Workflow

1. Pick the unit of measure deliberately. Occurrences, minutes, or money - choose the one closest to the pain being managed and say why. Ranking breakdowns by count when one category costs 10x more minutes per event points the team at the wrong problem. When in doubt, show count and impact side by side.
2. Enforce category hygiene before counting:
   • Categories must sit at one granularity level (no "Mechanical failure" next to "Sensor S-114 misaligned")
   • "Other/Miscellaneous" must stay under ~15% of the total; if it is bigger, the categorization failed - split it before proceeding
   • Merge synonyms and near-duplicates (free-text logs always contain them; list the merges made)
3. Normalize by exposure before comparing. Line A with 3 shifts will "lead" any raw ranking against Line B with 1 shift. Divide by machine-hours, orders, or units produced when comparing across lines, shifts, or periods - state the exposure base used.
4. Check stability. A Pareto from one bad week is an anecdote. Compare the ranking across at least two comparable periods; only categories that stay on top deserve investment. Note rank changes.
5. Rank, plot, and go one level deeper on the #1 category. Break the top category into its own sub-Pareto or apply 5-why prompts to its most frequent instances. The actionable cause is usually one level below the headline category.
6. Define the counter-metric. Before recommending an action, state which number should move, by roughly how much, and when to re-measure. A Pareto without a follow-up measurement is decoration.

Pitfalls to check explicitly

• Unit mismatch (count vs duration vs cost) silently reordering priorities
• Unnormalized cross-line comparisons
• "Other" as the tallest bar
• Categories mixing symptoms ("stopped") with causes ("no material")
• Acting on unstable rankings from short windows

Output format

1. One sentence: unit of measure, exposure base, period, and total impact covered
2. The ranked table (category, impact, share, cumulative) - chart optional, table mandatory
3. Sub-analysis of the top category with candidate root causes
4. Recommended action + counter-metric + re-measure date
5. Data notes: merges performed, rows excluded, Other%

Source: industrial-engineering-ai-skills by Eren Gulmez (MIT). The full method pack - entry skill, role agents, data-hygiene rules and artifact templates - lives there.