--- name: pareto-chart description: "Count a problem, split it into categories on purpose, and rank them largest first with a running cumulative percentage, so you can see whether a few categories carry most of it. Then split the top bar again before acting. The ranking, the vital few and the warnings (too little data, a big Other bar, no clear vital few) are computed, not typed in. Use when: You have a recurring problem made up of many separate events (defects, complaints, delays, failures) and need to decide where to start. You can count or measure those events over a fixed period from a record you trust, such as reject tags, a ticket log or a downtime log. Not for: There's one single failure to understand, not many events to sort. Go straight to a cause analysis such as 5 Whys. You only have a handful of events. With fewer than about 30 counted events, one unusual day can reorder the bars. The categories are opinions (a survey of what people think the main problem is) rather than counts of what actually happened." --- # Pareto chart Count a problem, split it into categories on purpose, and rank them largest first with a running cumulative percentage, so you can see whether a few categories carry most of it. Then split the top bar again before acting. The ranking, the vital few and the warnings (too little data, a big Other bar, no clear vital few) are computed, not typed in. Family: Problem solving / root cause analysis · Format: .xlsx · Domain: core ## What it is A Pareto chart is a bar chart of a problem split into categories, sorted largest first, with a line showing the running total as a percentage. It's named after Vilfredo Pareto, an economist who noticed that a small share of people held most of the land in Italy. Joseph Juran, a quality pioneer, turned that into a working rule of thumb for quality problems: a vital few causes usually account for most of the trouble, and the rest are a useful many. People call it the 80/20 rule, but that's a shorthand, not a law. Real data might split 70/30 or 90/10, or not concentrate at all. The chart's job is to show you which it is before you spend effort, so you work on the biggest part of the problem rather than the loudest or the easiest. It tells you where to look, not why it happens: the cause analysis comes next. Sources: Joseph M. Juran, Quality Control Handbook (McGraw-Hill, 1951); Kaoru Ishikawa, Guide to Quality Control (Asian Productivity Organization, 1968). ## When to use it Use it when: - You have a recurring problem made up of many separate events (defects, complaints, delays, failures) and need to decide where to start. - You can count or measure those events over a fixed period from a record you trust, such as reject tags, a ticket log or a downtime log. - A team disagrees about which issue matters most and you want the data to settle it before choosing a problem to solve. - You want to check whether a countermeasure worked: chart the same thing, split the same way, over an equal period, before and after. Not when: - There's one single failure to understand, not many events to sort. Go straight to a cause analysis such as 5 Whys. - You only have a handful of events. With fewer than about 30 counted events, one unusual day can reorder the bars. - The categories are opinions (a survey of what people think the main problem is) rather than counts of what actually happened. - The question is a trend over time (is it getting worse?). A run chart answers that; a Pareto chart adds everything up and hides the timing. ## How to fill it in - **effect** — Write down exactly what one event is, in words someone else could count the same way: "a painted part rejected at final inspection for a finish defect", not "quality issues". This is the effect, the problem you're splitting up. If two people would count differently from your description, tighten it before collecting anything. - **stratifyBy** — Choose the axis on purpose: the one way you'll split the effect into categories. Stratifying means sorting the events into groups by one characteristic, such as defect type, cause, location, machine, shift, product or customer. Pick the split most likely to point at something you can act on, and say why. Use categories that don't overlap, so each event lands in exactly one. If you're not sure which split matters, chart two or three and keep the one that shows a clear top bar. This first split is level 1. - **unit** — Decide what the bars measure: how often it happens (count), what it costs, or how much time it loses. Ranking by frequency and by cost can put the categories in a different order: a rare defect that scraps a whole batch can matter more than a common one fixed in seconds. Choose the measure that matches why the problem matters, write down the unit (rejected parts, dollars, minutes), and don't mix measures on one chart. - **period** — Use one fixed period, with a start and end date, and the same data source for every category. Mixing a month of one category with a week of another, or the day shift's log with both shifts' log, makes the ranking meaningless. Pick a period long enough to cover normal variation (often two to six weeks) and note anything unusual that happened in it. Write where the numbers came from, and how you checked them. - **categories** — Enter each category and its total for the period. Count from the record, not from memory. Keep an Other bucket for small, one-off categories, but keep it small: if Other is among the largest bars, open it up and give its biggest items their own categories. The chart sorts the bars for you, with Other always last. - **chart** — Nothing to enter here: the chart ranks the categories, works out each one's share and the cumulative percentage, and marks the vital few, the named categories that together reach roughly 80% of the total. Read it as a rough guide. If the bars are all about the same height, or it takes most of the categories to reach 80%, there's no clear vital few: try a different split or measure rather than working on everything. The warnings also flag too few categories, too few counted events, and an Other bucket that's too large. - **breakdown** — Before acting, split the top bar again by a second axis. This is level 2. The level 1 chart splits the whole problem (every rejected part, by defect type); level 2 takes only the largest level 1 bar and splits that (only the colour contamination rejects, by where the old colour came from). A label like "colour contamination" isn't yet something you can fix, but its biggest source often is. Break the largest bar down first rather than moving on to the second bar, and check the level 2 values add up to the level 1 bar. - **nextStep** — Write what happens after the chart. A Pareto chart shows where the problem is concentrated, not why. The usual next step is a cause analysis on the top level 2 category: a fishbone diagram to lay out possible causes, and 5 Whys to follow the strongest one to something you can act on, then an A3 if it's a bounded problem worth a full record. Also note when you'll redraw the chart, with the same split, measure and period length, to see whether the countermeasure moved the top bar. ## What good looks like The example below continues Line 2's paint booth. With changeovers now about 35 minutes, final inspection counted 100 parts rejected for a finish defect over four weeks, from the reject tags checked against the rework log. The split is by defect type, ranked by count, with a sentence on why count is the right measure for this line (every reject costs about the same to repaint). Colour contamination is the clear top bar at 52%, and three named categories reach roughly 80%. The Other bucket is small and last. At level 2, the colour contamination rejects are split by where the old colour came from: residue in the spray gun or nozzle is 31 of the 52. The next step is a cause analysis on that residue with the booth operators, and a recount over the same length of period afterwards. Full worked example, on-screen and as a downloadable .xlsx: https://www.katafacts.com/katas/pareto-chart ## Common mistakes - **Treating 80/20 as exact.** — The 80% line is a rule of thumb. Forcing the data to show 20% of categories causing 80% of the problem, or ignoring a chart that shows 60/40, turns a way of looking into a belief. Read what the chart actually shows, and if there's no clear vital few, say so and try another split. - **A huge Other bar.** — When Other is among the largest bars, the chart is hiding categories that may belong in the vital few. It usually means the categories were set too narrowly or the record is vague. Open the Other bucket, name its biggest items, and redraw. - **Mixing periods or sources.** — Four weeks of one defect next to one week of another, or one shift's log next to both shifts' log, ranks the data collection, not the problem. Every bar needs the same period and the same source. - **Counting the wrong thing.** — Ranking by how often something happens when cost or customer impact is what matters (or the reverse) points the team at the wrong bar. Frequency and cost can rank the same categories differently, so choose the measure on purpose and write down why. - **Charting opinions instead of counts.** — A chart of what people say the main problem is measures how memorable or annoying each issue is, not how often it happens. Count events from a record, or go and tally them first-hand. - **Stopping at the chart.** — A Pareto chart shows where to look, not why it happens. Jumping from "colour contamination is the top bar" straight to a fix skips the level 2 breakdown and the cause analysis, and the fix often lands on the wrong cause. ## What it connects to Upstream: - **First-pass yield tracker** (`first-pass-yield-tracker`) — Shows which stage loses the most units. A Pareto chart of that stage's rejects, split by defect type or cause, shows what to work on inside it. - **Eight wastes (DOWNTIME) worksheet** (`eight-wastes-worksheet`) — Once a waste is spotted, count its occurrences over a period and chart them by cause or location, so the team works on the biggest source first. - **Value stream map — current and future state** (`value-stream-map`) — The map shows which process box has the quality or delay problem; a Pareto chart of that box's defects or stoppages shows what's driving it. Downstream: - **A3 problem solving** (`a3`) — A Pareto chart is what earns an A3's root cause section the right to chase one category instead of guessing. Take the top level 2 category into the A3's cause analysis. - **Fishbone diagram** (not in the catalogue yet) — Lays out the possible causes of the top bar (method, materials, machines, measurement, people and environment) so the cause analysis doesn't lock on to the first idea. - **5-Whys** (not in the catalogue yet) — Follows the strongest cause of the top level 2 category, one "why" at a time, until it reaches something in the process you can act on. ## Where AI helps Judgement — stays with you: - Choosing which effect to count and which axis to split it by - Choosing the measure (count, cost or time) that matches why the problem matters - Deciding whether the chart shows a real vital few, and which bar to break down - Going to see the work and checking the record matches what actually happens Analysis — AI helps: - Suggesting other ways to split a problem when the bars come out flat - Explaining why frequency and cost can rank the same categories differently - Explaining when a Pareto chart fits and when a run chart or a cause analysis fits better Drudgery — automated: - Sorting the categories and working out each share and the cumulative percentage - Marking the vital few and flagging a large Other bucket, too little data or flat bars - Drawing the bars and cumulative line, and exporting to xlsx in the house format --- Pareto chart is licensed [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribution: Katafacts (katafacts.com). ## Using this skill Apply this method as part of whatever broader task, instructions, or deliverable you're already working on -- it's a method to use, not a standalone conversation to start. There is no generation tool for this catalogue yet, so draft the artifact's actual content yourself, following the fields above, the same way a person filling this out by hand would. The canonical guide page and a downloadable worked example (.xlsx) are at https://www.katafacts.com/katas/pareto-chart.