Is / Is Not Analysis is a problem-definition technique that compares where a problem occurs with closely related conditions where it does not occur.

The method helps teams narrow the problem before jumping to causes.

It is especially useful when the team can compare affected and unaffected products, locations, times, or conditions.

Why comparison helps

A problem statement such as:

Product scratches are increasing.

is broad.

A comparison may reveal:

  • IS: Product A;
  • IS NOT: Product B;
  • IS: Line 2;
  • IS NOT: Line 1;
  • IS: after changeover;
  • IS NOT: during steady production.

These differences can contain useful clues.

Use the same dimensions as problem definition

5W1H helps define What, Where, When, Who, Which, and How.

Is / Is Not Analysis strengthens that work by asking what similar condition is not affected.

Typical dimensions include:

  • what object is affected;
  • where it occurs;
  • when it occurs;
  • how large the problem is.

Example

Suppose a sealing defect appears on one package family.

The team finds:

  • IS: 500 ml package;
  • IS NOT: 250 ml package;
  • IS: Filler 3;
  • IS NOT: Filler 2;
  • IS: after tooling change;
  • IS NOT: before tooling change;
  • IS: Supplier B film;
  • IS NOT: Supplier A film.

The differences create investigation priorities.

They do not prove cause.

Look for distinctions and changes

For each Is / Is Not comparison, ask:

  • What is different between these conditions?
  • What changed recently?
  • Which difference could logically explain the effect?

This helps move from broad brainstorming toward evidence-based investigation.

Do not confuse correlation with cause

A difference is only a clue.

If the problem occurs with Supplier B material, the supplier may not be the cause.

Perhaps Supplier B material is used only on a particular machine or during a particular shift.

The team still needs to verify the causal mechanism.

Root Cause Analysis provides the broader investigation framework.

Use facts from the Gemba

The comparisons should be based on evidence.

Observe the real process.

Review:

  • production records;
  • material lots;
  • maintenance history;
  • setup data;
  • timestamps;
  • measurements;
  • environmental conditions.

Avoid filling the table from memory.

Common mistakes

Choosing unrelated “Is Not” conditions, treating every difference as causal, starting with the suspected cause, using vague descriptions, and failing to verify the final explanation are common mistakes.

Practical sequence

  1. Define the problem clearly.
  2. Describe where the problem IS.
  3. Identify the closest comparable condition where it IS NOT.
  4. Repeat for location, time, product, and magnitude.
  5. List meaningful differences.
  6. identify recent changes.
  7. generate causal hypotheses.
  8. test those hypotheses.
  9. verify the cause with evidence.

The practical lesson

Is / Is Not Analysis reduces the search space.

By comparing what failed with what did not fail, teams can focus root-cause investigation on the differences that actually matter.