Quantitative Project Management

To effectively address the specific practices in this process area, the organization should have already established a set of standard processes and related organizational process assets, such as the measurement repository and the process asset library, for use by each project in establishing its defined process. The project’s defined process is a set of sub-processes that form an integrated and coherent life cycle for the project. It is established, in part, through selecting and tailoring processes from the set of standard processes.

Process performance is a measure of the actual process results achieved. Process performance is characterized by both process measures (e.g., effort, cycle time, and defect removal efficiency) and product measures (e.g., reliability, defect density, and response time).

The quality and process-performance objectives, measures, and baselines are developed as described in the Organizational Process Performance process area. Subsequently, the results of performing the processes associated with the Quantitative Project Management process area (e.g., measurement definitions and measurement data) become part of the organizational process assets referred to in the Organizational Process Performance process area.

Sub-processes are defined components of a larger defined process. For example, a typical organization's development process may be defined in terms of sub-processes such as requirements development, design, build, test, and peer review. The sub-processes themselves may be further decomposed as necessary into other sub-processes and process elements.

This process area applies to managing a project, but the concepts found here also apply to managing other groups and functions. Applying these concepts to managing other groups and functions may not necessarily contribute to achieving the business objectives, but may help these groups and functions control their own processes.

An essential element of quantitative management is having confidence in estimates (i.e., being able to predict the extent to which the project can fulfill its quality and process-performance objectives). The sub-processes that will be statistically managed are chosen based on identified needs for predictable performance. A second key element of quantitative management is understanding the nature and extent of the variation experienced in process performance, and recognizing when the project’s actual performance may not be adequate to achieve the project’s quality and process performance objectives.

Statistical management involves statistical thinking and the correct use of a variety of statistical techniques, such as run charts, control charts, confidence intervals, prediction intervals, and tests of hypotheses. Quantitative management uses data from statistical management to help the project predict whether it will be able to achieve its quality and process-performance objectives and identify what corrective action should be taken.