Business alignment: Metrics should concentrate on the processes that contribute most importantly to the bottom line — up and down the value chain.
- Beware of metrics overload: Setting up too many metrics can detract attention from what’s important. Include only those metrics that will be acted on — by either removing a degradation problem or by holding the gain.
- Honest assessment: Metrics must provide a true picture, whether it’s good, bad, or ugly. Creating metrics to make the performance of an organization or an individual look good is useless and often is counter-productive.
- Consistency: Components of any metric need to be defined at the outset and remain constant.
- Repeatability and reproducibility: Measurements should have little or no subjectivity. The measurement response should have little or no dependence on who recorded the response and when the response was recorded.
- What’s the problem?: When the metrics response is unsatisfactory, organizations need to conduct a root-cause analysis and take corrective or preventive actions.
- Time-series tracking: Metrics should be captured in time-series format, not as a snapshot of a point-in-time activity. Time-series tracking can describe trends and separate special-cause from common-cause variability in predictable processes.
- Predictability: A predictability statement should be made when time-series tracking indicates that a process is predictable.
- Peer comparability: Compare the metrics with peer groups in another business or company. A peer comparison can help identify new kinds of improvement possibilities.
Avoid ''Analysis Paralysis'' When Using Metrics
0 Viewsby Forrest Breyfogle
