Establish and maintain an understanding of the variation of selected subprocesses using selected measures and analytic techniques.

Refer to the Measurement and Analysis process area for more information about collecting, analyzing, and using measurement results.

Understanding variation is achieved, in part, by collecting and analyzing process and product measures so that special causes of variation can be identified and addressed to achieve predictable performance.

A special cause of process variation is characterized by an unexpected change in process performance. Special causes are also known as assignable causes because they can be identified, analyzed, and addressed to prevent recurrence.

The identification of special causes of variation is based on departures from the system of common causes of variation. These departures can be identified by the presence of extreme values or other identifiable patterns in data collected from the subprocess or associated work products. Typically, knowledge of variation and insight about potential sources of anomalous patterns are needed to detect special causes of variation.

Typical Work Products

1.    Collected measurements

2.    Natural bounds of process performance for each measured attribute of each selected subprocess

3.    Process performance compared to the natural bounds of process performance for each measured attribute of each selected subprocess

Typical Supplier Deliverables

1.    Collected supplier measurements

2.    Natural bounds of supplier process performance for each measured attribute of each selected subprocess

3.    Supplier process performance compared to the natural bounds of process performance for each measured attribute of each selected subprocess

Subpractices

1.    Establish trial natural bounds for subprocesses having suitable historical performance data.

Refer to the Organizational Process Performance process area for more information about organizational process-performance baselines.

Natural bounds of an attribute are the range within which variation normally occurs. All processes show some variation in process and product measures each time they are executed. The issue is whether this variation is due to common causes of variation in the normal performance of the process or to some special cause that can and should be identified and removed.

When a subprocess is initially executed, suitable data for establishing trial natural bounds are sometimes available from prior instances of the subprocess or comparable subprocesses, process-performance baselines, or process-performance models. Typically, these data are contained in the organization’s measurement repository. As the subprocess is executed, data specific to that instance are collected and used to update and replace the trial natural bounds. However, if the subprocess has been materially tailored, or if conditions are materially different from those in previous instantiations, data in the repository may not be relevant and should not be used.

In some cases, there may be no comparable historical data (e.g., when introducing a new subprocess, when entering a new application domain, or when significant changes have been made to the subprocess). In such cases, trial natural bounds will have to be made from early process data of this subprocess. These trial natural bounds must then be refined and updated as subprocess execution continues.

2.    Collect data, as defined by selected measures, on subprocesses as they execute.

3.    Calculate the natural bounds of process performance for each measured attribute.

4.    Identify special causes of variation.

The criteria for detecting special causes of variation are based on statistical theory and experience and depend on economic justification. As criteria are added, special causes are more likely to be identified if they are present, but the likelihood of false alarms also increases.

5.    Analyze special cause of process variation to determine the reasons the anomaly occurred.

Some anomalies may simply be extremes of the underlying distribution rather than problems. Those implementing a subprocess are usually the ones best able to analyze and understand special causes of variation.

6.    Determine the corrective action to be taken when special causes of variation are identified.

Removing a special cause of process variation does not change the underlying subprocess. It addresses an error in the way the subprocess is executed.

Refer to the Project Monitoring and Control process area for more information about taking corrective action.

7.    Recalculate natural bounds for each measured attribute of the selected subprocesses as necessary.

Recalculating the (statistically estimated) natural bounds is based on measured values that signify that the subprocess has changed, not on expectations or arbitrary decisions.