Thursday, April 10, 2008

Help! I am Totally Lost When Interpreting the QPM Specific Practices

QPM SP 1.1 states “Establish and maintain the project’s quality and process-performance objectives.” When you are starting to implement the Maturity Level 4 PAs you won’t have a Process Capability Baseline, that is ultimately the goal of being at ML 4 so the organization can then move to ML 5. One of the main thrusts of ML 4 is to analyze the process data looking for Special Causes of Variation. Once those have been analyzed, then it is possible to determine the process capability. For SP 1.1 the project’s quality and process-performance objectives (QPPOs) are set by management and are based, in part, on the organization’s objectives (OPP SP 1.3). The Process Performance Models (PPMs) are then used to determine if the QPPOs can be met. If not, the QPPOs should be appropriately adjusted.

QPM SP 1.2 states "Select the sub-processes that compose the project's defined process based on historical stability and capability datat." One of the key words in this practice statement is "historical". Sources of historical stability and capability data include the organization’s process performance baselines (PPBs) and PPMs (OPP SP 1.4 and SP 1.5). And the intent of this practice is to tailor the organization’s standard processes (OSSP) so the project’s processes will support the project’s QPPOs defined in SP 1.1.

QPM SP 1.3 states “Select the sub-processes of the project’s defined process that will be statistically managed.” The model does not say that these sub-processes MUST be statistically managed, but these WILL be statistically managed. And this practice focuses more on than just selecting sub-processes. It also focuses on identifying the attributes of each sub-process that will be used to statistically manage the sub-process.

People appear to get confused with Maturity Level 4 (ML 4) sounds when trying to understand QPM independently from the rest of the model. You cannot do that. You have to consider OPP and QPM together when looking at ML 4. OPP provides the analysis of the historical data to build the PPBs and PPMs which are then used by the projects to help them appropriately tailor the OSSP to what will meet the project’s QPPOs. QPM SP 1.2 uses the word "compose", which may contribute to some of the confusion. Since compose is not in the CMMI Glossary, then the dictionary definition is applicable. The Webster definition of compose is “To form by putting together two or more things or parts; to put together; to make up; to fashion.” So for this practice, compose means going to the OSSP and selecting the processes and sub-processes that will meet the QPPOs and then applying the necessary tailoring criteria. What this practice implies is that the OSSP may have several different processes for each Process Area (PA) so the project manager can choose the most appropriate one when composing the project's defined process.

Another ML 4 concept that may be the cause of confusion is the notion of Quantitative Management vs. Statistical Management. QPM SG 1 is all about quantitatively managing the project, which means the Project Manager must be periodically reviewing progress, performance, and risks using the PPMs to determine/predict if the project will meet its QPPOs. If not, then appropriate correctives actions must be taken to address the deficiencies in achieving the project’s QPPOs (QPM SP 1.4) Statistical Management is covered by QPM SG 2. The intent is for the project to statistically manage those sub-processes that are critical to achieving the project’s QPPOs. There are only a small set of sub-processes that are critical to achieving the project’s QPPOs. If the organization were to statistically manage all processes, that would be insane. This approach would mean that the organization would need PPBs and PPMs for EVERY process, regardless of their importance to the QPPOs. And then the shear overhead of collecting, analyzing, and reporting data on every process would most likely bring the organization to its knees. Work would come to a standstill because it was taking far too much time to statistically manage each process and taking corrective actions that may not be necessary. Unless you have an infinite budget and dedicated staff to perform these analyses, that is why the model states to statistically manage SELECTED sub-processes.

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