Cause-and-effect matrix

Learning objectives

• Weight CTQ outputs against process inputs.
• Score relationships consistently across the team.
• Select the vital few Xs for validation.

Prioritising Xs

• List CTQ outputs with weights (1–10).
• List process steps and inputs from the detailed map.
• Score relationships with 0/1/3/9.
• Sum weighted scores; sensitivity-check the top Xs.

Garment-factory example

For collar appearance, folder setting, seam allowance, operator handling, feed balance and material stretch are scored against symmetry, puckering, dimension and strength; the top three Xs feed the data plan.

Method

1. Confirm CTQs and weights with the sponsor.
2. Calibrate scoring definitions before rating.
3. Score cross-functionally and reconcile outliers.
4. Plan data collection for the top Xs.

Common mistakes

• Treating scores as measured effects.
• Letting one manager set all scores.