Select subprocesses and attributes critical to evaluating performance and that help to achieve the project’s quality and process performance objectives.


Some subprocesses are critical because their performance significantly influences or contributes to achieving the project’s objectives. These subprocesses may be good candidates for monitoring and control using statistical and other quantitative techniques as described in the first specific practice of the second specific goal.

Also, some attributes of these subprocesses can serve as leading indicators of the process performance to expect of subprocesses that are further downstream and can be used to assess the risk of not achieving the project’s objectives (e.g., by using process performance models).

Subprocesses and attributes that play such critical roles may have already been identified as part of the analyses described in the previous specific practice.

For small projects, and other circumstances in which subprocess data may not be generated frequently enough in the project to support a sufficiently sensitive statistical inference, it may still be possible to understand performance by examining process performance across similar iterations, teams, or projects.

Example Work Products

  1. Criteria used to select subprocesses that are key contributors to achieving the project’s objectives
  2. Selected subprocesses
  3. Attributes of selected subprocesses that help in predicting future project performance


1. Analyze how subprocesses, their attributes, other factors, and project performance results relate to each other.

A root cause analysis, sensitivity analysis, or process performance model can help to identify the subprocesses and attributes that most contribute to achieving particular performance results (and variation in performance results) or that are useful indicators of future achievement of performance results.

Refer to the Causal Analysis and Resolution (CAR) (CMMI-DEV) process area for more information about determining causes of selected outcomes.

2. Identify criteria to be used in selecting subprocesses that are key contributors to achieving the project’s quality and process performance objectives.


Examples of criteria used to select subprocesses include the following:
  • There is a strong correlation with performance results that are addressed in the project’s objectives.
  • Stable performance of the subprocess is important.
  • Poor subprocess performance is associated with major risks to the project.
  • One or more attributes of the subprocess serve as key inputs to process performance models used in the project.
  • The subprocess will be executed frequently enough to provide sufficient data for analysis.

3. Select subprocesses using the identified criteria.

Historical data, process performance models, and process performance baselines can help in evaluating candidate subprocesses against selection criteria.

Refer to the Decision Analysis and Resolution (DAR) (CMMI-DEV) process area for more information about evaluating alternatives.

4. Identify product and process attributes to be monitored.

These attributes may have been identified as part of performing the previous subpractices.

Attributes that provide insight into current or future subprocess performance are candidates for monitoring, whether or not the associated subprocesses are under the control of the project. Also, some of these same attributes may serve other roles, (e.g., to help in monitoring project progress and performance as described in Project Monitoring and Control [PMC]).


Examples of product and process attributes include the following:
  • Effort consumed to perform the subprocess
  • The rate at which the subprocess is performed
  • Cycle time for process elements that make up the subprocess
  • Resource or materials consumed as input to the subprocess
  • Skill level of the staff member performing the subprocess
  • Quality of the work environment used to perform the subprocess
  • Volume of outputs of the subprocess (e.g., intermediate work products)
  • Quality attributes of outputs of the subprocess (e.g., reliability, testability)