Start with a few metrics
Most plants measure too much and act on too little. Three to five metrics that people understand and can influence beat a dozen nobody checks.
The metrics most plants use
| Metric | What it tells you | How it is worked out |
|---|---|---|
| First pass yield | Share of units right first time, with no rework | Good units first time divided by units started |
| Defect rate | How often defects occur | Defective units divided by units made, or defects per million opportunities |
| Scrap and rework | The cost and volume of waste | Units or cost scrapped or reworked in the period |
| Customer complaints and returns | What the customer actually sees | Count per period, ideally per volume shipped |
| Supplier quality | Incoming material problems | Rejected lots or parts per delivery |
How to set it up
- Choose metrics that fit the process. A high-volume line suits first pass yield; a batch process may suit right-first-time batches.
- Write a definition for each. What counts as a defect, what counts as a unit, which period. Two shifts counting differently make a trend meaningless.
- Record at the source. Capture the result at the step that caused it, as the work happens, not from a weekly summary.
- Set a target and show the trend. A number without a target or a trend does not tell anyone whether to act.
- Review daily. Put the metrics on the team board so a bad day is seen the same day. See manufacturing KPIs.
- Dig into the exceptions. When a metric misses, rank the causes with a Pareto chart and start problem solving.
Cost of poor quality
Many organisations also track the cost of poor quality: the money spent on failure (scrap, rework, returns) and on appraisal and prevention. It turns quality data into a figure leaders can compare with other priorities.
Mistakes to avoid
- Measuring only at final inspection, which hides where defects start.
- Changing definitions mid-year, which breaks the trend.
- Reporting averages across lines and shifts that hide a bad one.