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Pareto Analysis: guide & examples

A Pareto chart ranks categories by a common amount and shows their cumulative share of the total. It helps identify the largest observed contributors.

5 practical steps · 2 worked examples · Editable practice worksheet

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What is it, and why use it?

A Pareto chart ranks categories by a common amount and shows their cumulative share of the total. It helps identify the largest observed contributors.

It helps a team focus investigation where the recorded impact is greatest instead of selecting the most memorable incident.

Explore the Pareto Analysis features and local-file workflow

When to use it

Use it when events or impacts can be grouped into meaningful, consistently defined categories.

When another tool fits better

Use a Control Chart for time patterns or Fishbone for possible causes. A Pareto chart of problem categories is not a causal analysis.

Before you start

  • A common period and category definitions.
  • Whole counts for frequency mode, or a consistent unit for numeric impact.
  • A plan for handling duplicates, missing values and excluded rows.

Use fictional or approved non-sensitive information. Do not include patient details or proprietary records in practice worksheets.

Step-by-step in CI Tools

  1. Choose frequency or numeric impact and enter Measurement unit when appropriate.

  2. Add category/amount pairs, or import CSV/XLSX after selecting columns and reviewing the preview.

  3. Review included rows, invalid-entry warnings and Filter categories. Duplicate category names aggregate.

  4. Read the descending bars and cumulative percentage line; select a bar for details.

  5. Investigate the leading contributors and retain the same definitions when comparing later periods. Save the input data with the editable worksheet.

Read a cumulative percentage correctly

At each bar, the line shows that category plus all larger categories as a share of the included total. Filtering changes the denominator. Use the table and selected-bar details to check which observations contribute.

Completed worked examples

Demonstrations only: all organizations, observations, targets and results below are fictional. They are not clinical instructions or universal performance standards.

Healthcare operations — fictional

Referral rework categories

Starting information: A fictional office categorizes 50 rework events.

Fictional rework event counts
  • Missing attachment: 25
  • Unclear contact details: 15
  • Other incomplete fields: 10

The first two categories total 40 of 50 events (80%). Counts describe categories, not proven root causes.

Completed demonstration: Referral rework categories
Missing attachment25 events = 50%
Unclear contact details15 events; cumulative 80%
Other incomplete fields10 events; cumulative 100%

What the result means: The first two categories account for 80% of these recorded events. That does not make 80% a universal rule or prove their underlying causes.

General business — fictional

Dispatch delay impact

Starting information: A fictional supplier records delay minutes using one unit.

Completed demonstration: Dispatch delay impact
Missing stock120 minutes
Label correction60 minutes; cumulative 75% of 240
Other60 minutes; total 240

What the result means: Minutes weight the categories differently from counts. Do not combine event counts and delay minutes in the same chart.

Practise in a separate worksheet

Open the tool’s built-in synthetic sample as a new editable worksheet. It may differ from the worked demonstrations above. It never replaces an existing worksheet. Save any work you want to retain to your computer.

Open built-in practice worksheet

You’ll be asked to log in if needed. No worksheet is created just by reading this page.

Common mistakes and how to avoid them

  • Treating the 80% line as a law: it is a reference, not a required cutoff.
  • Mixing counts and costs: use one interpretable unit.
  • Calling the largest category a root cause without investigation.

Interpret the result

The cumulative line uses the included, valid and filtered data. Review exclusions and totals before drawing conclusions. Focus on both frequency and consequence; a rare high-severity problem may still require attention.

Record the assumptions and unanswered questions alongside the result. Use the relevant local review process before making operational decisions.

Credible further learning

These independent educational resources explain the methods. They do not endorse CI Tools Suite. Some external resources have their own access requirements.

Resource links reviewed 29 October 2026. Our interface instructions and fictional examples are original CI Tools learning material.

Put the method into practice

Start a new worksheet, use the guide beside your work and keep an editable .citools copy on your computer.

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