Developing Performance Measures for Lessons Learned Programs cont'd

Lessons Learned Handbook:

DOE-HDBK-7502-95

2. Define performance measures for each lessons learned objective.

Each performance measure should reflect a process. Understanding the

performance measure data and the underlying process is necessary in

order to optimize the lessons learned objective.

Collect Performance Measurement Data:

If data to support the performance measures already exist:

Document source of data and define parameters for sorting.

Review the source of data and clean up anomalies.

Add new parameters to data collection if needed.

If data to support the performance measures does not exist:

Explicitly define data to be collected.

Create consistent and verifiable system to hold data.

Task person(s) to collect data.

3. Analyze the performance measures data for trends and significant changes.

Use Statistical Process Control (or other comparable methods) as the

criteria to determine if trends and changes are occurring or if the data is

stable.

If a significant change occurs, determine why. Assess costs of

action vs. inaction, perform corrective action (if the performance

measurement change was negative), perform reinforcing actions (if

the change was positive), or take no action.

If the process is stable, determine if the performance is at an

acceptable, stable value. Criteria to apply:

Continuous improvement

"Zero defects"

Risk vs. benefit analysis (Probability Risk Assessment)

Comparison against "benchmark" (other companies, INPO

guidelines, etc.)

If a performance change is needed, the PROCESS must be changed.

Study the process and performance measure data.

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