Select measures and analytic techniques to be used in statistically managing selected subprocesses.
Refer to the Measurement and Analysis process area for more information about establishing measurable objectives; specifying the measures and analyses to be performed;
obtaining, analyzing, and updating measures; and reporting results.
Typical Work Products
1. Definitions of measures and analytic techniques to be used in (or proposed for) statistically managing
subprocesses
2. Operational definitions of measures, their collection points in subprocesses, and how the integrity of measures will be
determined
3. Traceability of measures back to the project’s quality and process-performance objectives
4. Instrumented organizational support environment that supports automatic data collection
Subpractices
1. Identify common measures from the organizational process assets that support statistical management.
Refer to the Organizational Process Definition process area for more information about common measures.
Product lines or other stratification criteria may categorize common measures.
2. Identify additional measures that may be needed for this instance to cover critical product and process attributes of the selected
subprocesses.
In some cases, measures may be research oriented. Such measures should be explicitly identified.
3. Identify the measures that are appropriate for statistical management.
Critical criteria for selecting statistical management measures include the following:
· Controllable (e.g., Can a measure’s values be changed by changing how the subprocess is implemented?)
· Adequate performance indicator (e.g., Is the measure a good indicator of how well the subprocess is performing relative to the objectives of interest?)
Examples of subprocess measures include the following:
· Requirements volatility
· Ratios of estimated to measured values of planning parameters (e.g., size, cost, and schedule)
· Coverage and efficiency of peer reviews
· Test coverage and efficiency
· Effectiveness of training (e.g., percent of planned training completed and test scores)
· Reliability
· Percentage of total defects inserted or found in different phases of the project lifecycle
· Percentage of total effort expended in different phases of the project lifecycle
4. Specify the operational definitions of measures, their collection points in subprocesses, and how the integrity of measures will be
determined.
Operational definitions are stated in precise and unambiguous terms. They address two important criteria:
· Communication: What has been measured, how it was measured, what are the units of measure, and what has been included or excluded?
· Repeatability: Is the measurement repeatable, given the same definition, to get the same results?
5. Analyze the relationship of identified measures to the objectives of the organization and its projects, and derive objectives that
state target measures or ranges to be met for each measured attribute of each selected subprocess.
6. Instrument the organizational or project support environment to support collection, derivation, and analysis of statistical
measures.
This instrumentation is based on the following:
· Description of the organization’s set of standard processes
· Description of the project’s defined process
· Capabilities of the organizational or project support environment
7. Identify appropriate statistical analysis techniques that are expected to be useful in statistically managing the selected
subprocesses.
The concept of “one size does not fit all” applies to statistical analysis techniques. What makes a particular technique appropriate is not just the type of measures but, more important, how
the measures will be used and whether the situation warrants applying that technique. The appropriateness of the selection may need to be reviewed from time to time.
Examples of statistical analysis techniques are given in the next specific practice.
8. Revise measures and statistical analysis techniques as necessary.