Design Thinking & Innovation

Fishbone Diagram

Sort possible causes of a problem into six categories so you can find the real source.

How to use this worksheet
  1. State the problem (the effect) as a specific, observable fact.
  2. Brainstorm causes in each category. One cause per line, as specific as possible.
  3. Ask "why" for each cause to find deeper causes and add them as their own lines.
  4. Mark the three to five most likely root causes and plan how to verify them with data.
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What exactly is going wrong? Include where, when and how much.

Prompts and example

Ask yourself

  • Can you measure it?
  • Is it a new problem or a persistent one?

Example

12 percent of orders shipped late in October, up from 4 percent in September.

Possible causes

Add causes under the category where they belong.

People

Skills, training, motivation, communication

    Process

    Methods, procedures, handovers

      Equipment

      Tools, systems, machines, software

        Materials

        Inputs, data, supplies, information

          Environment

          Location, conditions, culture, time pressure

            Measurement

            Metrics, monitoring, inspection, data quality

              Prompts

              Ask yourself

              • What changed just before the problem started?
              • Which causes can you verify with data this week?

              Which causes will you investigate first, and how?

              Prompts and example

              Example

              1) Stock counts in the system (verify with a cycle count this week). 2) Manual order check (measure the delay per order).

              Causes per category

              Before you finish

              About the fishbone diagram

              Kaoru Ishikawa introduced the cause-and-effect diagram in the 1960s for quality control. The categories shown here are the classic manufacturing "6Ms" adapted for general use.

              The diagram structures brainstorming, it does not prove anything. Verify the shortlisted causes with data before acting.

              Recommended reading

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