Performance measurement is an important cornerstone of the contracts
between the University of California and the U.S. Department of Energy for the operation
of its laboratories. Performance metrics should be constructed to encourage performance
improvement, effectiveness, efficiency, and appropriate levels of internal controls. They
should incorporate "best practices" related to the performance being measured
and cost/risk/benefit analysis, where appropriate.
The Department of Energy has promulgated a set of Total
Quality Management guidelines that indicate that performance metrics should lead to a
quantitative assessment of gains in:
- Organizational Performance
The key elements of the performance metrics to these
guidelines should address:
- Alignment with Organizational Mission
- Cost Reduction and/or Avoidance
The first step in developing performance metrics is to involve the
people who are responsible for the work to be measured because they are the most
knowledgeable about the work. Once these people are identified and involved, it is
- Identify critical work processes and customer
- Identify critical results desired and align them to
- Develop measurements for the critical work processes or
- Establish performance goals, standards, or benchmarks.
The establishment of performance goals can best be
specified when they are defined within three primary levels:
Objectives: Broad, general areas of
review. These generally reflect the end goals based on the mission of a function.
Criteria: Specific areas of
accomplishment that satisfy major divisions of responsibility within a function.
Measures: Metrics designed to drive
improvement and characterize progress made under each criteria. These are specific
quantifiable goals based on individual expected work outputs.
The SMART test is frequently used to provide a quick
reference to determine the quality of a particular performance metric:
S = Specific: clear and focused to avoid
misinterpretation. Should include measure assumptions and definitions and be easily
M = Measurable: can be quantified and
compared to other data. It should allow for meaningful statistical analysis. Avoid
"yes/no" measures except in limited cases, such as start-up or systems-in-place
A = Attainable: achievable, reasonable,
and credible under conditions expected.
R = Realistic: fits into the
organization's constraints and is cost-effective.
T = Timely: doable within the time frame
Types of Metrics
Quality performance metrics allow for the collection of meaningful
data for trending and analysis of rate-of-change over time. Examples are:
- Trending against known standards: the standards may come
from either internal or external sources and may include benchmarks.
- Trending with standards to be established: usually this
type of metric is used in conjunction with establishing a baseline.
Yes/No metrics are used in certain situations
usually involving establishing trends, baselines, or targets, or in start-up cases.
Because there is no valid calibration of the level of performance for this type of
measure, the should be used sparingly. Examples are:
- Establish/implement a system.
- Reporting achieved (without analyses).
- System is in place (without regard to effectiveness).
- Threshold achieved (arbitrary standards).
- Analysis performed (without criteria).
Determining the Quality
The following questions serve as a checklist to determine the quality
of the performance metrics that have been defined.
- Is the metric objectively measurable?
- Does the metric include a clear statement of the end
- Does the metric support customer requirements, including
compliance issues where appropriate?
- Does the metric focus on effectiveness and/or efficiency
of the system being measured?
- Does the metric allow for meaningful trend or statistical
- Have appropriate industry or other external stands been
- Does the metric include milestones and/or indicators to
express qualitative criteria?
- Are the metrics challenging but at the same time
- Are assumptions and definitions specified for what
constitutes satisfactory performance?
- Have those who are responsible for the performance being
measured been fully involved in the development of this metric?
- Has the metric been mutually agreed upon by you and your