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Fishbone Diagram

Ishikawa diagram; cause-and-effect diagram

A fishbone diagram lays out the possible causes of a problem in categories that branch off a central spine. The problem sits at the head, and causes form the bones.

Lean teams use it to brainstorm causes widely before narrowing down. It keeps a group from fixating on the first idea and shows where to collect data.

Where it comes from

The diagram was developed by Japanese quality expert Kaoru Ishikawa, which is why it is also called an Ishikawa diagram. It is often listed among the basic tools of quality control.

At a glance

A fishbone for uneven paint thickness

A fishbone for uneven paint thickness. Possible causes grouped by category, from the worked example. Data then picks out the real one: nozzle wear.Uneven paintthicknessMethodSpray distanceLine speedMachineNozzle wearPump pressureMaterialPaint viscosityBatch mixMeasurementGauge calibrationEnvironmentHumidity swingsBooth temperaturePeopleTrainingShift handoverOrange: the cause the data confirmed

Swipe sideways to see the whole diagram.

Possible causes grouped by category, from the worked example. Data then picks out the real one: nozzle wear.

How to apply Fishbone Diagram

  1. 1

    Write the problem at the head

    State the effect clearly and specifically. Draw a horizontal spine leading to it.

  2. 2

    Choose cause categories

    Common sets are the 6Ms: people, machine, method, material, measurement and environment. Office teams often use process, policy, people and systems.

  3. 3

    Brainstorm causes

    Have the team add possible causes under each category. Ask why to add sub-causes as smaller bones.

  4. 4

    Select likely causes

    Mark the causes the team thinks matter most. Base the choice on evidence where you have it.

  5. 5

    Verify with data

    Test the selected causes at the gemba or with data. Drill into confirmed ones with 5 Whys.

Worked example

A coating line sees uneven paint thickness. The team lists causes under method, machine, material and environment, including spray nozzle wear and humidity swings. Data shows thickness tracks nozzle age, so nozzle replacement moves into the PM plan.

Common mistakes

  • Treating every cause on the diagram as proven instead of verifying the likely ones.
  • Building the diagram without the people who do the work.
  • Writing vague causes such as "training" that cannot be tested or acted on.

When Fishbone Diagram is not the right tool

A fishbone diagram lists possible causes. It does not prove any of them. Use data or tests to confirm the likely causes before acting.

For a simple problem with one clear chain of cause, five whys is quicker.

Choosing the categories

Manufacturing teams often use six categories: people, machine, method, material, measurement and environment. Older versions call people "man" and environment "mother nature".

Service and office teams often use process, policy, people and systems instead. Pick categories that help the team think, then add or drop as needed.

Narrowing the causes

Once the diagram is full, the team votes on the most likely causes. Data, such as a Pareto chart of defect types, then checks the vote.

Kaoru Ishikawa described the diagram, and it is often called an Ishikawa diagram after him.

FAQ

Fishbone Diagram: common questions

Is a fishbone diagram a lean tool?
Yes. It is a standard quality and lean problem-solving tool. Lean teams use it inside A3s and kaizen events, and Six Sigma teams use it in DMAIC.
What are the 6Ms of a fishbone diagram?
People, machine, method, material, measurement and environment. Older versions say man instead of people and mother nature instead of environment.
How is a fishbone different from 5 Whys?
A fishbone spreads wide to list many possible causes. 5 Whys goes deep on one cause chain to reach its root.
Which DMAIC phase uses the fishbone diagram?
Mostly Analyze, where the team lists and then tests possible causes. Some teams also use it in Measure to decide what data to collect.
How many causes should a fishbone have?
There is no set number. The aim is to capture the plausible causes in each category, then narrow them down with data.

Further reading and sources

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