Calculator Library / Prioritization
Build a weighted C&E Matrix, score how strongly process inputs affect customer requirements, rank the highest-priority causes, and watch the chart update instantly as the team changes the matrix.
Live Tool
Core formula: Weighted cause score = sum of (relationship x CTQ weight)
Define the customer outputs or CTQs across the top, assign their relative importance, then score each process input or suspected cause against those outputs.
Dynamic Chart
Output Influence
| CTQ / Output | Weight | Average Relationship | Primary Focus |
|---|---|---|---|
| Add CTQs and causes to see the output summary. | |||
Instructions
The page updates as the team types, so it works well in workshops, DMAIC tollgates, and cross-functional prioritization sessions where multiple stakeholders need to see the scoring effect immediately.
A Cause and Effect Matrix is used to prioritize the process inputs, causes, or design factors that are most likely to influence customer-critical outputs. It is especially useful when a team has a long list of possible drivers and needs a disciplined way to decide where measurement, validation, and improvement time should go first.
In Lean Six Sigma, teams often use the matrix after VOC and CTQ work, after SIPOC or process mapping, and before deeper Analyze-phase validation. It creates a structured bridge between customer requirements and the possible process variables that may be driving performance.
| Practice | Why It Matters | What to Watch |
|---|---|---|
| Agree on the scale first | Prevents each scorer from inventing a private meaning for each number. | Do not start scoring until the team agrees on what weak, moderate, and strong mean. |
| Weight outputs deliberately | Keeps the matrix aligned to customer and business priorities. | A low-value CTQ should not dominate the ranking just because it is easier to score. |
| Use the matrix for focus, not proof | The ranking shows where to investigate first, not what is already proven. | Top-ranked inputs still need data, observation, or experimentation. |
| Review the outliers | One extreme score can heavily shift the ranking. | Challenge unusual ratings before accepting the final order at face value. |
In Define, the tool helps connect Voice of the Customer requirements to the process boundary and clarifies what outputs deserve the most attention. In Measure and Analyze, it narrows the field of possible inputs so teams can focus data collection, capability checks, stratification, DOE planning, or root-cause validation on the most credible drivers.
A Cause and Effect Matrix helps teams connect process inputs or suspected causes to customer or business requirements, then rank those inputs using weighted relationships so improvement effort focuses on the most influential drivers.
Each CTQ or output receives a weight. Each cause is rated for relationship strength against each CTQ. The tool multiplies each relationship score by the CTQ weight and sums the results into a weighted total and ranked priority order.
Most teams use 0 for no relationship, 1 for weak, 3 for moderate, and 9 for strong, but any consistent 0 to 10 rating logic can work if the team aligns on what each score means before scoring begins.
It is commonly used in Define and Measure to prioritize possible input factors before deeper data collection, and again in Analyze to focus validation effort on the highest-ranked causes.
No. The matrix is a prioritization tool. It structures team judgment and converts it into ranked focus areas, but the highest-ranked inputs still need data, observation, and analysis to verify real causal impact.
Use SIPOC first when the team needs clearer process boundaries before ranking causes.
Use a Fishbone to expand the list of possible causes before narrowing them in the matrix.
Use Pareto logic after prioritization when data is available to confirm the largest contributors.
Move from influence ranking into structured failure-risk prioritization when the team is ready for control planning.