Quantitative Project Management: A Project Management Process Area at Maturity Level 4
Purpose
The purpose of Quantitative Project Management (QPM) is to quantitatively manage the project to achieve the project’s established quality and process performance objectives.
Tip
QPM helps an acquirer migrate from using the rear-view mirror to manage the project to using predictive, forward-looking approaches to help steer the project to success.
Introductory Notes
The Quantitative Project Management process area involves the following activities:
• Establishing and maintaining the project’s quality and process performance objectives
• Composing a defined process for the project to help to achieve the project’s quality and process performance objectives
• Selecting subprocesses and attributes critical to understanding performance and that help to achieve the project’s quality and process performance objectives
• Selecting measures and analytic techniques to be used in quantitative management
• Monitoring the performance of selected subprocesses using statistical and other quantitative techniques
• Managing the project using statistical and other quantitative techniques to determine whether or not the project’s objectives for quality and process performance are being satisfied
• Performing root cause analysis of selected issues to address deficiencies in achieving the project’s quality and process performance objectives
Tip
CMMI-ACQ avoids implementation specifics. Some acquisition organizations may implement QPM practices by assigning experts in quantitative management to specific projects; others may execute their projects in a more homogeneous manner, supporting these practices with general organizational resources. Regardless of who performs the QPM practices, the focus should be on helping projects quantitatively manage achievement of quality and process performance objectives.
Tip
When effectively implemented, QPM empowers individuals and teams by enabling them to make more accurate estimates (make predictions) and, therefore, to make sounder commitments based on these estimates (predictions).
Organizational process assets used to achieve high maturity, including quality and process performance objectives, selected processes, measures, baselines, and models, are established using organizational process performance processes and used in quantitative project management processes. The project can use organizational process performance processes to define additional objectives, measures, baselines, and models as needed to effectively analyze and manage performance. The measures, measurements, and other data resulting from quantitative project management processes are incorporated into the organizational process assets. In this way, the organization and its projects derive benefit from assets improved through use.
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QPM and OPP are tightly coupled process areas; each produces work products used by the other. Refer to OPP extensively when considering how to implement QPM.
The project’s defined process is a set of interrelated subprocesses that form an integrated and coherent process for the project. The Integrated Project Management practices describe establishing the project’s defined process by selecting and tailoring processes from the organization’s set of standard processes. (See the definition of “defined process” in the glossary.)
Quantitative Project Management practices, unlike Integrated Project Management practices, help you to develop a quantitative understanding of the expected performance of processes or subprocesses. This understanding is used as a basis for establishing the project’s defined process by evaluating alternative processes or subprocesses for the project and selecting the ones that will best achieve the quality and process performance objectives.
Establishing effective relationships with suppliers is also important to the successful implementation of this process area. Establishing effective relationships can involve establishing quality and process performance objectives for suppliers, determining the measures and analytic techniques to be used to gain insight into supplier progress and performance, and monitoring progress toward achieving those objectives.
Hint
Take advantage of the quantitative insights a high maturity supplier brings to the relationship. But be realistic: Don’t expect your lower maturity suppliers to have the same understanding of the value of managing quantitatively.
The acquirer uses statistical and other quantitative techniques to both manage its work and to gain insight into supplier work and work products.
An essential element of quantitative management is having confidence in predictions (i.e., the ability to accurately predict the extent to which the project can fulfill its quality and process performance objectives). Subprocesses to be managed through the use of statistical and other quantitative techniques are chosen based on the needs for predictable process performance.
Another essential 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.
Thus, quantitative management includes statistical thinking and the correct use of a variety of statistical techniques. (See the definition of “quantitative management” in the glossary.)
Tip
Here “statistical thinking” refers to the use of statistical techniques as tools in appropriate ways to assess the variation in the performance of a process, to investigate its causes, and to recognize from the data when the process is not performing as it should. (See the definition of “statistical techniques” in the glossary.)
Statistical and other quantitative techniques are used to develop an understanding of the actual performance or to predict the performance of processes. Such techniques can be applied at multiple levels, from a focus on individual subprocesses to analyses that span lifecycle phases, projects, and support functions. Non-statistical techniques provide a less rigorous but still useful set of approaches that together with statistical techniques help the project to understand whether or not quality and process performance objectives are being satisfied and to identify any needed corrective actions.
This process area applies to managing a project. Applying these concepts to managing other groups and functions can help to link different aspects of performance in the organization to provide a basis for balancing and reconciling competing priorities to address a broader set of business objectives.
Tip
A related term is “statistical and other quantitative techniques.” (See its definition in the glossary.) High maturity organizations and projects leverage an understanding of which factors matter in an unfolding situation to control its future course. Statistical and other quantitative techniques provide the insight needed to accomplish this feat, thus helping “steer” the project toward achieving its objectives.
Related Process Areas
Refer to the Solicitation and Supplier Agreement Development process area for more information about establishing supplier agreements.
Refer to the Causal Analysis and Resolution process area for more information about identifying causes of selected outcomes and taking action to improve process performance.
Refer to the Integrated Project Management process area for more information about establishing the project’s defined process.
Refer to the Measurement and Analysis process area for more information about aligning measurement and analysis activities and providing measurement results.
Refer to the Organizational Process Definition process area for more information about establishing organizational process assets.
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See How to Measure Anything: Finding the Value of “Intangibles” in Business by Douglas W. Hubbard (John Wiley & Sons, Inc.).
Refer to the Organizational Performance Management process area for more information about proactively managing the organization’s performance to meet its business objectives.
Refer to the Organizational Process Performance process area for more information about establishing and maintaining a quantitative understanding of the performance of selected processes in the organization’s set of standard processes in support of achieving quality and process performance objectives, and providing process performance data, baselines, and models to quantitatively manage the organization’s projects.
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See Moving Up the CMMI Capability and Maturity Levels Using Simulation by David M. Raffo and Wayne Wakeland (www.sei.cmu.edu/reports/08tr002.pdf).
Refer to the Project Monitoring and Control process area for more information about providing an understanding of the project’s progress so that appropriate corrective actions can be taken when the project’s performance deviates significantly from the plan.
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See Understanding Variation: The Key to Managing Chaos, second edition, by Donald J. Wheeler (SPC Press, Inc.).
Specific Practices by Goal
SG 1 Prepare for Quantitative Management
Preparation for quantitative management is conducted.
Preparation activities include establishing quantitative objectives for the project, composing a defined process for the project that can help to achieve those objectives, selecting subprocesses and attributes critical to understanding performance and achieving the objectives, and selecting measures and analytic techniques that support quantitative management.
These activities may need to be repeated when needs and priorities change, when there is an improved understanding of process performance, or as part of risk mitigation or corrective action.
SP 1.1 Establish the Project’s Objectives
Establish and maintain the project’s quality and process performance objectives.
Tip
Generally, these objectives are established early during project planning as customer requirements relating to product quality, service quality, and process performance are being established and analyzed.
When establishing the project’s quality and process performance objectives, think about the processes that will be included in the project’s defined process and what the historical data indicate regarding their process performance. These considerations, along with others such as technical capability, will help in establishing realistic objectives for the project.
Hint
Once a supplier or set of suppliers is selected, revisit these objectives. Teaming with suppliers that have quantitatively managed processes may present opportunities to optimize those processes across organizational boundaries.
The project’s objectives for quality and process performance are established and negotiated at an appropriate level of detail (e.g., for individual product components, subprocesses, project teams) to permit an overall evaluation of the objectives and risks at the project level. As the project progresses, project objectives can be updated as the project’s actual performance becomes known and more predictable, and to reflect changing needs and priorities of relevant stakeholders.
The acquirer establishes the project’s quality and process performance objectives based on objectives of the organization, the customer, and other relevant stakeholders. The acquirer can also establish quality and process performance objectives for supplier deliverables. These quantitative quality and process performance objectives for the supplier are documented in the supplier agreement. The acquirer typically expects the supplier to execute its processes and apply its process performance models toward achieving these objectives.
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Quality and process performance objectives (QPPOs) should satisfy certain criteria, such as “SMART criteria.” In this context, SMART is an acronym standing for “specific, measurable, attainable, relevant, and time bound” (see Wikipedia for more information).
Example Work Products
1. The project’s quality and process performance objectives
2. Assessment of the risk of not achieving the project’s objectives
Hint
Supplier QPPOs that are “specified” prior to contract award will need to be revised once the selected supplier’s process performance baselines (PPBs) are established.
Subpractices
1. Review the organization’s objectives for quality and process performance.
This review ensures that project staff understand the broader business context in which the project operates. The project’s objectives for quality and process performance are developed in the context of these overarching organizational objectives.
Refer to the Organizational Process Performance process area for more information about establishing quality and process performance objectives.
Tip
The project’s QPPOs should be based, in part, on those of the organization. This approach helps to ensure that the project’s QPPOs are aligned with those of the organization, while recognizing unique project or customer needs.
2. Identify the quality and process performance needs and priorities of the customer, suppliers, end users, and other relevant stakeholders.
Typically, the identification of relevant stakeholders’ needs will begin early (e.g., during development of the acquisition strategy). Needs are further elicited, analyzed, refined, prioritized, and balanced during acquisition requirements development.
3. Define and document measurable quality and process performance objectives for the project.
Defining and documenting objectives for the project involve the following:
• Incorporating appropriate organizational quality and process performance objectives
• Writing objectives that reflect the quality and process performance needs and priorities of the customer, end users, and other relevant stakeholders
• Determining how each objective will be achieved
• Reviewing the objectives to ensure they are sufficiently specific, measurable, attainable, relevant, and time-bound
4. Derive interim objectives to monitor progress toward achieving the project’s objectives.
Interim objectives can be established for attributes of selected lifecycle phases, milestones, work products, and subprocesses. Since process performance models characterize relationships among product and process attributes, these models can be used to help derive interim objectives that guide the project toward achieving its objectives.
5. Determine the risk of not achieving the project’s quality and process performance objectives.
The risk is a function of the established objectives, the product architecture, the project’s defined process, availability of needed knowledge and skills, etc. Process performance baselines and models can be used to evaluate the likelihood of achieving a set of objectives and provide guidance in negotiating objectives and commitments. The assessment of risk can involve various project stakeholders and can be conducted as part of the conflict resolution described in the next subpractice.
6. Resolve conflicts among the project’s quality and process performance objectives (e.g., if one objective cannot be achieved without compromising another).
Process performance models can help to identify conflicts and help to ensure that the resolution of conflicts does not introduce new conflicts or risks.
Resolving conflicts involves the following activities:
• Setting relative priorities for objectives
• Considering alternative objectives in light of long-term business strategies as well as short-term needs
• Involving the customer, end users, senior management, project management, and other relevant stakeholders in tradeoff decisions
• Revising objectives as necessary to reflect results of conflict resolution
7. Establish traceability to the project’s quality and process performance objectives from their sources.
8. Define and negotiate quality and process performance objectives for suppliers.
Refer to the Solicitation and Supplier Agreement Development process area for more information about establishing supplier agreements.
9. Revise the project’s quality and process performance objectives as necessary.
SP 1.2 Compose the Defined Process
Using statistical and other quantitative techniques, compose a defined process that enables the project to achieve its quality and process performance objectives.
Tip
Some organizations may not need alternative subprocesses (e.g., because the projects are sufficiently similar to one another). In such cases, some alternatives remain to be explored (e.g., one can adjust the level or depth of intensity with which a subprocess is applied; see subpractice 2).
Refer to the Integrated Project Management process area for more information about establishing the project’s defined process.
Refer to the Organizational Process Definition process area for more information about establishing organizational process assets.
Refer to the Organizational Process Performance process area for more information about establishing performance baselines and models.
Composing the project’s defined process goes beyond the process selection and tailoring described in the Integrated Project Management process area. It involves identifying alternatives to one or more processes or subprocesses, performing quantitative analysis of performance, and selecting the alternatives that are best able to help the project to achieve its quality and process performance objectives.
Tip
PPBs and process performance models (PPMs) can help the project evaluate alternatives to determine which alternatives best help it achieve its QPPOs.
These subprocesses can include activities used for interacting with a supplier (e.g., negotiating a supplier agreement, conducting supplier reviews).
1. Criteria used to evaluate alternatives for the project
2. Alternative subprocesses
3. Subprocesses to be included in the project’s defined process
4. Assessment of risk of not achieving the project’s objectives
Subpractices
1. Establish the criteria to use in evaluating process alternatives for the project.
2. Identify alternative processes and subprocesses for the project.
Identifying alternatives can include one or more of the following:
• Analyzing organizational process performance baselines to identify candidate subprocesses that would help achieve the project’s quality and process performance objectives
• Identifying subprocesses from the organization’s set of standard processes as well as tailored processes in the process asset library that can help to achieve the objectives
• Identifying processes from external sources (e.g., such as other organizations, professional conferences, academic research)
• Adjusting the level or depth of intensity with which a subprocess is applied (as described in further detail in a subpractice that follows)
Adjusting the level or depth of intensity with which the subprocesses are applied can involve the following choices:
• Number and type of peer reviews to be held and when
• Amount of effort or calendar time devoted to particular tasks
• Number and selection of people involved
• Skill level requirements for performing specific tasks
• Selective application of specialized construction or verification techniques
• Reuse decisions and associated risk mitigation strategies
• The product and process attributes to be measured
• Sampling rate for management data
Refer to the Integrated Project Management process area for more information about using organizational process assets for planning project activities.
3. Analyze the interaction of alternative subprocesses to understand relationships among the subprocesses, including their attributes.
An analysis of the interaction will provide insight into the relative strengths and weaknesses of particular alternatives. This analysis can be supported by a calibration of the organization’s process performance models with process performance data (e.g., as characterized in process performance baselines).
Additional modeling may be needed if existing process performance models cannot address significant relationships among the alternative subprocesses under consideration and there is high risk of not achieving objectives.
Hint
When project subprocesses interact with supplier or end-user subprocesses, the dynamics may not always be obvious. Use process simulation in concert with PPMs to uncover hidden behavior and unintended consequences.
4. Evaluate alternative subprocesses against the criteria.
Use historical data, process performance baselines, and process performance models as appropriate to assist in evaluating alternatives against the criteria. These evaluations can include use of a sensitivity analysis particularly in high risk situations.
Refer to the Decision Analysis and Resolution process area for more information about evaluating alternatives.
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Systems thinking may be used to evaluate the underlying dynamics of common patterns of failure; see “Acquisition Archetypes: Changing Counterproductive Behaviors in Real Acquisitions” at www.sei.cmu.edu/acquisition/research/archetypes.cfm.
5. Select the alternative subprocesses that best meet the criteria.
It may be necessary to iterate through the activities described in the previous subpractices several times before confidence is achieved that the best available alternatives have been identified.
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For more information about process simulation, see the Raffo and Wakeland report mentioned earlier.
6. Evaluate the risk of not achieving the project’s quality and process performance objectives.
An analysis of risk associated with the selected alternative defined process can lead to identifying new alternatives to be evaluated, as well as areas requiring more management attention.
Refer to the Risk Management process area for more information about identifying and analyzing risks.
SP 1.3 Select Subprocesses and Attributes
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.
Tip
The focus of SP 1.2 is on determining which process will best help the organization achieve QPPOs. In SP 1.3, the focus shifts to identifying those critical subprocesses within that process that need to be performed correctly and consistently (that need to be “mastered”) so that project performance will not suffer; in addition, the focus is on identifying those attributes that give an early indication (or “signal”) that the project has gone “off course.”
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.
Hint
Learn which knobs you can turn at different points within a project to desirably affect project performance and achievement of outcomes. Such learning goes on at the organizational level (OPP SPs 1.2 and 1.5) and continues within individual 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
Hint
Avoid subprocesses that are beyond the acquisition team’s ability to control. Subprocesses that are enacted by a supplier or end user are important to track, for example, but difficult to quantitatively manage using statistical process control techniques because the processes fall outside the acquirer’s control.
Subpractices
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 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.
Tip
The project’s selection of subprocesses and attributes is based, in part, on those selected by the organization (OPP SP 1.2).
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 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]).
Tip
This practice has a dynamic aspect to it. While many measures and analytic techniques can be identified in advance, and thus the project team(s) may be prepared to apply these elements and interpret their results, specific situations may arise during the project that require more in-depth analysis to diagnose the situation and evaluate potential resolutions (e.g., see SP 2.3). Access to special expertise in analytic techniques may be needed in these circumstances.
SP 1.4 Select Measures and Analytic Techniques
Select measures and analytic techniques to be used in quantitative management.
Refer to the Measurement and Analysis process area for more information about aligning measurement and analysis activities and providing measurement results.
1. Definitions of measures and analytic techniques to be used in quantitative management
2. Traceability of measures back to the project’s quality and process performance objectives
3. Quality and process performance objectives for selected subprocesses and their attributes
4. Process performance baselines and models for use by the project
Subpractices
1. Identify common measures from the organizational process assets that support quantitative management.
Refer to the Organizational Process Definition process area for more information about establishing organizational process assets.
Refer to the Organizational Process Performance process area for more information about establishing performance baselines and models.
Product lines, standard services, and service levels or other stratification criteria can categorize common measures.
Tip
For example, the identification of measures to support monitoring of selected subprocesses (SP 2.1) is based on the attributes selected (SP 1.3) and on the measures established by the organization to be included in its process performance analyses (OPP SP 1.3).
2. Identify additional measures that may be needed to cover critical product and process attributes of the selected subprocesses.
In some cases, measures can be research oriented. Such measures should be explicitly identified.
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Much of the material found in the remaining subpractices (2 through 9) represents a direct application of MA SG 1, Align Measurement and Analysis Activities.
3. Identify the measures to be used in managing subprocesses.
When selecting measures, keep the following considerations in mind:
• Measures that aggregate data from multiple sources (e.g., different processes, input sources, environments) or over time (e.g., at a phase level) can mask underlying problems, making problem identification and resolution difficult.
• For short-term projects, it may be necessary to aggregate data across similar instances of a process to enable analysis of its process performance while continuing to use the unaggregated data in support of individual projects.
• Selection should not be limited to progress or performance measures only. “Analysis measures” (e.g., inspection preparation rates, staff member skill levels, path coverage in testing) may provide better insight into process performance.
Tip
Additional measures may be needed, for example, to address unique customer requirements or supplier approaches.
4. Specify the operational definitions of measures, their collection points in subprocesses, and how the integrity of measures will be determined.
5. Analyze the relationship of identified measures to the project quality and process performance objectives and derive subprocess quality and process performance objectives that state targets (e.g., thresholds, ranges) to be met for each measured attribute of each selected subprocess.
Tip
See the definitions of “statistical and other quantitative techniques” and “statistical techniques” in the glossary.
6. Identify the statistical and other quantitative techniques to be used in quantitative management.
In quantitative management, the process performance of selected subprocesses is analyzed using statistical and other quantitative techniques that help to characterize subprocess variation, identify when statistically unexpected behavior occurs, recognize when variation is excessive, and investigate why. Examples of statistical techniques that can be used in the analysis of process performance include statistical process control charts, regression analysis, analysis of variance, and time series analysis. The project can benefit from analyzing the performance of subprocesses not selected for their impact on project performance. Statistical and other quantitative techniques can be identified to address these subprocesses as well.
Statistical and other quantitative techniques sometimes involve the use of graphical displays that help visualize associations among the data and results of analyses. Such graphical displays can help visualize process performance and variation over time (i.e., trends), identify problems or opportunities, and evaluate the effects of particular factors.
7. Determine what process performance baselines and models may be needed to support identified analyses.
In some situations, the set of baselines and models provided as described in Organizational Process Performance may be inadequate to support quantitative project management. This situation can happen when the objectives, processes, stakeholders, skill levels, or environment for the project are different from other projects for which baselines and models were established.
As the project progresses, data from the project can serve as a more representative data set for establishing missing or a project specific set of process performance baselines and models.
Hypothesis testing comparing project data to prior historical data can confirm the need to establish additional baselines and models specific to the project.
8. Instrument the organizational or project support environment to support collection, derivation, and analysis of 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
9. Revise measures and statistical analysis techniques as necessary.
SG 2 Quantitatively Manage the Project
The project is quantitatively managed.
Quantitatively managing the project involves the use of statistical and other quantitative techniques to do the following:
• Monitor the selected subprocesses using statistical and other quantitative techniques
• Determine whether or not the project’s quality and process performance objectives are being satisfied
• Perform root cause analysis of selected issues to address deficiencies
Tip
We prepare for quantitative management in SG 1. We perform quantitative management in SG 2. Under some circumstances, it may be necessary to revisit the practices under SG 1 (e.g., to address changes to QPPOs or select a superior subprocess alternative).
SP 2.1 Monitor the Performance of Selected Subprocesses
Monitor the performance of selected subprocesses using statistical and other quantitative techniques.
The intent of this specific practice is to use statistical and other quantitative techniques to analyze variation in subprocess performance and to determine actions necessary to achieve each subprocess’s quality and process performance objectives.
1. Natural bounds of process performance for each selected subprocess attribute
2. The actions needed to address deficiencies in the process stability or capability of each selected subprocess
Example Supplier Deliverables
1. Actions needed to address deficiencies in supplier process performance or the quality of deliverables
Tip
This subpractice addresses the question, “Is the subprocess stable?”
Subpractices
1. Collect data, as defined by the selected measures, on the subprocesses as they execute.
2. Monitor the variation and stability of the selected subprocesses and address deficiencies.
This analysis involves evaluating measurements in relation to the natural bounds calculated for each selected measure and identifying outliers or other signals of potential non-random behavior, determining their causes, and preventing or mitigating the effects of their recurrence (i.e., addressing special causes of variation).
During such analysis, be sensitive to the sufficiency of the data and to shifts in process performance that can affect the ability to achieve or maintain process stability.
Analytic techniques for identifying outliers or signals include statistical process control charts, prediction intervals, and analysis of variance. Some of these techniques involve graphical displays.
Other deficiencies in process performance to consider include when variation is too large to have confidence that the subprocess is stable, or too great to assess its capability (next subpractice) of achieving the objectives established for each selected attribute.
Hint
When the subprocess variation is too large, investigate process and measurement fidelity. Also, investigate what is happening “upstream” and at a lower level of granularity. You may need to restratify your data (e.g., to match input types) or disaggregate the measure (so it is no longer reporting totals) to achieve adequate control.
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See Example 7.1 in Measuring the Software Process: Statistical Process Control for Software Process Improvement, by William A. Florac and Anita D. Carleton (Addison-Wesley).
3. Monitor the capability and performance of the selected subprocesses and address deficiencies.
The intent of this subpractice is to identify what actions to take to help the subprocess achieve its quality and process performance objectives. Be sure that the subprocess performance is stable relative to the selected measures (previous subpractice) before comparing its capability to its quality and process performance objectives.
Tip
This subpractice addresses the question, “Is the subprocess capable?”
Hint
Regularly compare the natural bounds for the subprocess (“voice of the process”) against the associated QPPOs (“voice of the customer”) and take corrective action as appropriate.
Tip
Sometimes you can change QPPOs associated with a particular subprocess by investigating whether other subprocesses can give up some needed slack (or by differentiating which type or size of work products the subprocess is applied to).
Some actions can involve the use of root cause analysis, which is further described in SP 2.3.
Refer to the Project Monitoring and Control process area for more information about managing corrective action to closure.
SP 2.2 Manage Project Performance
Manage the project using statistical and other quantitative techniques to determine whether or not the project’s objectives for quality and process performance will be satisfied.
Refer to the Measurement and Analysis process area for more information about aligning measurement and analysis activities and providing measurement results.
Tip
Expand your process improvement toolkit to include techniques such as Six Sigma or Theory of Constraints when managing project performance.
Refer to the Organizational Performance Management process area for more information about managing business performance.
This specific practice is project focused and uses multiple inputs to predict if the project’s quality and process performance objectives will be satisfied. Based on this prediction, risks associated with not meeting the project’s quality and process performance objectives are identified and managed, and actions to address deficiencies are defined as appropriate.
X-Ref
For information on how to use Six Sigma with CMMI, see “CMMI and Six Sigma: Partners in Process Improvement” at www.sei.cmu.edu/library/abstracts/books/0321516087.cfm.
Key inputs to this analysis include the individual subprocess stability and capability data derived from the previous specific practice, as well as performance data from monitoring other subprocesses, risks, and suppliers’ progress.
X-Ref
For more information on using Theory of Constraints and the critical thinking tools, see Thinking for a Change: Putting the TOC Thinking Processes to Use by Lisa Scheinkopf (CRC).
Example Work Products
1. Predictions of results to be achieved relative to the project’s quality and process performance objectives
2. Graphical displays and data tabulations for other subprocesses, which support quantitative management
3. Assessment of risks of not achieving the project’s quality and process performance objectives
4. Actions needed to address deficiencies in achieving project objectives
1. Supplier process performance data for quality and process performance objectives and expected service levels
Subpractices
1. Periodically review the performance of subprocesses.
Stability and capability data from monitoring selected subprocesses, as described in SP 2.1, are a key input into understanding the project’s overall ability to meet quality and process performance objectives. In addition, subprocesses not selected for their impact on project objectives can still create problems or risks for the project and thus some level of monitoring for these subprocesses may be desired as well. Analytic techniques involving the use of graphical displays can also prove to be useful to understanding subprocess performance.
2. Monitor and analyze suppliers’ progress toward achieving their quality and process performance objectives.
3. Periodically review and analyze actual results achieved against established interim objectives.
4. Use process performance models calibrated with project data to assess progress toward achieving the project’s quality and process performance objectives.
Process performance models are used to assess progress toward achieving objectives that cannot be measured until a future phase in the project lifecycle. Objectives can either be interim objectives or overall objectives.
Tip
The organization’s PPMs (OPP SP 1.5), when calibrated with project-specific data or PPBs, can help the project determine whether it will be able to achieve its QPPOs.
Calibration of process performance models is based on the results obtained from performing the activities described in the previous subpractices and specific practices.
5. Identify and manage risks associated with achieving the project’s quality and process performance objectives.
Refer to the Risk Management process area for more information about identifying and analyzing risks and mitigating risks.
6. Determine and implement actions needed to address deficiencies in achieving the project’s quality and process performance objectives.
The intent of this subpractice is to identify and implement the right set of actions, resources, and schedule to place the project back on a path toward achieving its objectives.
Some actions can involve the use of root cause analysis, which is addressed in the next specific practice.
Refer to the Project Monitoring and Control process area for more information about managing corrective action to closure.
When corrective actions result in changes to attributes or measures related to adjustable factors in a process performance model, the model can be used to predict the effects of the actions. When undertaking critical corrective actions in high risk situations, a process performance model can be created to predict the effects of the change.
SP 2.3 Perform Root Cause Analysis
Perform root cause analysis of selected issues to address deficiencies in achieving the project’s quality and process performance objectives.
Tip
The deficiencies mentioned in the specific practice statement are those arising out of the analyses described in SP 2.1 (subprocess performance deficiencies) and SP 2.2 (predicted deficiencies in achieving project QPPOs).
Issues to address include deficiencies in subprocess stability and capability, and deficiencies in project performance relative to its objectives.
Root cause analysis of selected issues is best performed shortly after the problem is first identified, while the event is still recent enough to be carefully investigated.
The formality of and effort required for a root cause analysis can vary greatly and can be determined by such factors as the stakeholders who are involved; the risk or opportunity that is present; the complexity of the situation; the frequency with which the situation could recur; the availability of data, baselines, and models that can be used in the analysis; and how much time has passed since the events triggering the deficiency.
In the case of a subprocess that exhibits too much variation, is performed rarely, and involves different stakeholders, it could take weeks or months to identify root causes.
Likewise, the actions to take can range significantly in terms of effort and time needed to determine, plan, and implement them.
It is often difficult to know how much time is needed unless an initial analysis of the deficiencies is undertaken.
Refer to the Causal Analysis and Resolution process area for more information about identifying causes of selected outcomes and taking action to improve process performance.
Refer to the Measurement and Analysis process area for more information about aligning measurement and analysis activities and providing measurement results.
Example Work Products
1. Subprocess and project performance measurements and analyses (including statistical analyses) recorded in the organization’s measurement repository
2. Graphical displays of data used to understand subprocess and project performance and performance trends
3. Identified root causes and potential actions to take
Subpractices
1. Perform root cause analysis, as appropriate, to diagnose process performance deficiencies.
Process performance baselines and models are used in diagnosing deficiencies; identifying possible solutions; predicting future project and process performance; and evaluating potential actions as appropriate.
The use of process performance models in predicting future project and process performance is described in a subpractice of the previous specific practice.
X-Ref
Although an Ishikawa diagram (i.e., fishbone diagram) is a popular tool for simple root cause analysis, most deficiencies affecting achievement of the project’s QPPOs require more in-depth analysis. In addition to the use of PPBs and PPMs, consider tools such as the current reality tree from the Theory of Constraints. For more information, visit the Goldratt Institute at www.goldratt.com/ or consult Wikipedia.
2. Identify and analyze potential actions.
3. Implement selected actions.
4. Assess the impact of the actions on subprocess performance.
This assessment of impact can include an evaluation of the statistical significance of the impacts resulting from the actions taken to improve process performance.