Subset Overview / Details
______________________________________________________________
Requirement Set: CMMI
Subset: Quantitative Project
Management (QPM)
______________________________________________________________
Notes:
·
The contents of this web page were extracted from
the following document: Capability Maturity Model® Integration
(CMMISM), Version 1.1, Continuous Representation,
CMU/SEI-2002-TR-011, March 2002 (CMMI-SE/SW/IPPD/SS). Copyright 2002 by
Carnegie Mellon University. NO WARRANTY.
·
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·
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·
In the CMMI, a subset is known as a "Process
Area (PA)" and a requirement is known as a "Practice". The
specific practices are referred to as SPs and the generic practices are
referred to as GPs.
·
This web page contains the text for SPs and GPs as
it appears in Chapter 7 of the CMMI document, in the section corresponding to
the process area named in the heading of this page. This web page does not
include the detailed description of the GPs that appears in a separate chapter
of the CMMI document; the detailed
description of the GPs is available in a separate web
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______________________________________________________________
Category: Project Management
Purpose
The purpose of the Quantitative Project Management
process area is to quantitatively manage the project’s defined process to
achieve the project’s established quality and process-performance objectives. [PA165]
Introductory Notes
The Quantitative Project Management process area involves
the following: [PA165.N101]
· Establishing and maintaining the project’s quality and process-performance objectives
· Identifying suitable subprocesses that compose the project’s defined process based on historical stability and capability data found in process performance baselines or models
· Selecting the subprocesses of the project’s defined process to be statistically managed
· Monitoring the project to determine whether the project’s objectives for quality and process performance are being satisfied, and identifying appropriate corrective action
· Selecting the measures and analytic techniques to be used in statistically managing the selected subprocesses
· Establishing and maintaining an understanding of the variation of the selected subprocesses using the selected measures and analytic techniques
· Monitoring the performance of the selected subprocesses to determine whether they are capable of satisfying their quality and process-performance objectives, and identifying corrective action
· Recording statistical and quality management data in the organization’s measurement repository
The quality and process-performance objectives, measures,
and baselines identified above 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. [PA165.N102]
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
organization’s measurement repository and the organization’s process asset
library, for use by each project in establishing its defined process. The
project’s defined process is a set of subprocesses that form an integrated and
coherent life cycle for the project. It is established, in part, through
selecting and tailoring processes from the organization’s set of standard
processes. See Chapter 3 for an explanation of how “defined process” is used in
the CMMI Product Suite. [PA165.N103]
For Supplier Sourcing
The quality and timeliness of the products delivered by a supplier may have a significant impact on the performance of the project’s processes. To meet the objectives of the project requires careful handling of the supplier agreements to ensure that the measurements and progress of the supplier’s efforts are made available to the project. The practices of the Supplier Agreement Management and Integrated Supplier Management process areas should be coordinated with this process area. Establishment of effective relationships with suppliers is necessary for the successful implementation of this process area’s specific practices. [PA165.N103.AMP101]
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). [PA165.N106]
Subprocesses are defined components of a larger defined
process. For example, a typical organization's development process may be
defined in terms of subprocesses such as requirements development, design,
build, test, and peer review. The subprocesses themselves may be further
decomposed as necessary into other subprocesses and process elements. [PA165.N107]
One 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
subprocesses that will be statistically managed are chosen based on identified
needs for predictable performance. See the definitions of “statistically
managed process” and “quantitatively managed process” in Appendix C, the
glossary. See Chapter 3 for an explanation of how “quality and
process-performance objective” is used in the CMMI Product Suite. [PA165.N108]
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. [PA165.N109]
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. [PA165.N110]
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 organization’s business objectives, but may help
these groups and functions control their own processes. [PA165.N111]
Examples of
other groups and functions include the following: [PA165.N113]
· Quality assurance
· Process definition and improvement
· Effort reporting
· Customer complaint handling
· Problem tracking and reporting
Refer to the Project Monitoring and Control process area for more
information about monitoring and controlling the project and taking corrective
action. [PA165.R101]
Refer to the Measurement and Analysis process area for more information
about establishing measurable objectives, specifying the measures and analyses
to be performed, obtaining and analyzing measures, and providing results.
[PA165.R102]
Refer to the Organizational Process Performance process area for more
information about the organization’s quality and process-performance
objectives, process performance analyses, process performance baselines, and
process performance models. [PA165.R103]
Refer to the Organizational Process Definition process area for more
information about the organizational process assets, including the
organization’s measurement repository. [PA165.R104]
Refer to the Integrated Project Management process area for more information
about establishing and maintaining the project’s defined process.
[PA165.R105]
Refer to the Causal Analysis and Resolution process area for more
information about how to identify the causes of defects and other problems, and
taking action to prevent them from occurring in the future.
[PA165.R106]
Refer to the Organizational Innovation and Deployment process area for
more information about selecting and deploying improvements that support the
organization’s quality and process-performance objectives.
[PA165.R107]
Specific Goals
SG 1 Quantitatively
Manage the Project [PA165.IG101]
The project is quantitatively managed using quality and process-performance objectives.
SG 2 Statistically
Manage Subprocess Performance
[PA165.IG102]
The performance of selected subprocesses within the project's defined process is statistically managed.
Generic Goals
GG 1 Achieve
Specific Goals [CL102.GL101]
The process supports and enables achievement of the specific goals of the process area by transforming identifiable input work products to produce identifiable output work products.
GG 2 Institutionalize
a Managed Process [CL103.GL101]
The process is institutionalized as a managed process.
GG 3 Institutionalize
a Defined Process [CL104.GL101]
The process is institutionalized as a defined process.
GG 4 Institutionalize
a Quantitatively Managed Process
[CL105.GL101]
The process is institutionalized as a quantitatively managed process.
GG 5 Institutionalize
an Optimizing Process [CL106.GL101]
The process is institutionalized as an optimizing process.
Practice-to-Goal Relationship Table
SG 1 Quantitatively Manage the Project [PA165.IG101]
SP 1.1-1 Establish the Project’s Objectives
SP 1.2-1 Compose the Defined Process
SP 1.3-1 Select the Subprocesses that Will Be Statistically Managed
SP 1.4-1 Manage Project Performance
SG 2 Statistically Manage Subprocess Performance [PA165.IG102]
SP 2.1-1 Select Measures and Analytic Techniques
SP 2.2-1 Apply Statistical Methods to Understand Variation
SP 2.3-1 Monitor Performance of the Selected Subprocesses
SP 2.4-1 Record Statistical Management Data
GG 1 Achieve Specific Goals [CL102.GL101]
GP 1.1 Perform Base Practices
GG 2 Institutionalize a Managed Process [CL103.GL101]
GP 2.1 Establish an Organizational Policy
GP 2.2 Plan the Process
GP 2.3 Provide Resources
GP 2.4 Assign Responsibility
GP 2.5 Train People
GP 2.6 Manage Configurations
GP 2.7 Identify and Involve Relevant Stakeholders
GP 2.8 Monitor and Control the Process
GP 2.9 Objectively Evaluate Adherence
GP 2.10 Review Status with Higher Level Management
GG 3 Institutionalize a Defined Process [CL104.GL101]
GP 3.1 Establish a Defined Process
GP 3.2 Collect Improvement Information
GG 4 Institutionalize a Quantitatively Managed Process [CL105.GL101]
GP 4.1 Establish Quantitative Objectives for the Process
GP 4.2 Stabilize Subprocess Performance
GG 5 Institutionalize an Optimizing Process [CL106.GL101]
GP 5.1 Ensure Continuous Process Improvement
GP 5.2 Correct Root Causes of Problems
Specific Practices by Goal
SG 1 Quantitatively Manage the Project
The project is quantitatively managed using
quality and process-performance objectives.
[PA165.IG101]
SP 1.1-1 Establish the Project’s Objectives
Establish
and maintain the project’s quality and process-performance objectives. [PA165.IG101.SP101]
When establishing the project’s quality and
process-performance objectives, it is often useful to think ahead about which
processes from the organization’s set of standard processes will be included in
the project’s defined process, and what the historical data indicates regarding
their process performance. These considerations will help in establishing
realistic objectives for the project. Later, as the project’s actual
performance becomes known and more predictable, the objectives may need to be
revised. [PA165.IG101.SP101.N102]
Typical Work Products
1. The project’s quality and
process-performance objectives [PA165.IG101.SP101.W101]
Subpractices
1. Review the organization's objectives for
quality and process performance. [PA165.IG101.SP101.SubP101]
The intent of this review is to
ensure that the project understands the broader business context in which the
project will need to operate. The project’s objectives for quality and process
performance are developed in the context of these overarching organizational
objectives.
[PA165.IG101.SP101.SubP101.N101]
Refer
to the Organizational Process Performance process area for more information
about the organization’s quality and process-performance objectives. [PA165.IG101.SP101.SubP101.N101.R101]
2. Identify the quality and process performance
needs and priorities of the customer, end users, and other relevant
stakeholders. [PA165.IG101.SP101.SubP102]
Examples
of quality and process performance attributes for which needs and priorities
might be identified include the following:
[PA165.IG101.SP101.SubP102.N101]
· Functionality
· Reliability
· Maintainability
· Usability
· Duration
· Predictability
· Timeliness
· Accuracy
3. Identify how process performance is to be
measured. [PA165.IG101.SP101.SubP103]
Consider whether the measures
established by the organization are adequate for assessing progress in
fulfilling customer, end-user, and other stakeholder needs and priorities. It
may be necessary to supplement these with additional measures. [PA165.IG101.SP101.SubP103.N101]
Refer
to the Measurement and Analysis process area for more information about
defining measures. [PA165.IG101.SP101.SubP103.N101.R101]
4. Define and document measurable quality and
process-performance objectives for the project. [PA165.IG101.SP101.SubP104]
Defining and documenting
objectives for the project involve the following: [PA165.IG101.SP101.SubP104.N101]
· Incorporating the organization’s quality and process-performance objectives
· Writing objectives that reflect the quality and process-performance needs and priorities of the customer, end users, and other stakeholders, and the way these objectives should be measured
Examples
of quality attributes for which objectives might be written include the
following: [PA165.IG101.SP101.SubP104.N102]
· Mean time between failures
· Critical resource utilization
· Number and severity of defects in the released product
· Number and severity of customer complaints concerning the provided service
Examples
of process performance attributes for which objectives might be written include
the following: [PA165.IG101.SP101.SubP104.N103]
· Percentage of defects removed by product verification activities (perhaps by type of verification, such as peer reviews and testing)
· Defect escape rates
· Number and density of defects (by severity) found during the first year following product delivery (or start of service)
· Cycle time
· Percentage of rework time
5. Derive interim objectives for each
life-cycle phase, as appropriate, to monitor progress toward achieving the project’s
objectives. [PA165.IG101.SP101.SubP105]
An
example of a method to predict future results of a process is the use of
process performance models to predict the latent defects in the delivered
product using interim measures of defects identified during product
verification activities (e.g., peer reviews and testing). [PA165.IG101.SP101.SubP105.N101]
6. Resolve conflicts among the project’s
quality and process-performance objectives (e.g., if one objective cannot be
achieved without compromising another objective).
[PA165.IG101.SP101.SubP106]
Resolving conflicts involves the
following:
[PA165.IG101.SP101.SubP106.N101]
· Setting relative priorities for the 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 the tradeoff decisions
· Revising the objectives as necessary to reflect the results of the conflict resolution
7. Establish traceability to the project’s
quality and process-performance objectives from their sources. [PA165.IG101.SP101.SubP107]
Examples
of sources for objectives include the following:
[PA165.IG101.SP101.SubP107.N101]
· Requirements
· Organization's quality and process-performance objectives
· Customer's quality and process-performance objectives
· Business objectives
· Discussions with customers and potential customers
· Market surveys
An
example of a method to identify and trace these needs and priorities is Quality
Function Deployment (QFD). [PA165.IG101.SP101.SubP107.N102]
8. Define and negotiate quality and
process-performance objectives for suppliers.
[PA165.IG101.SP101.SubP108]
Refer
to the Supplier Agreement Management process area for more information about
establishing and maintaining agreements with suppliers.
[PA165.IG101.SP101.SubP108.R101]
9. Revise the project’s quality and
process-performance objectives as necessary.
[PA165.IG101.SP101.SubP109]
SP 1.2-1 Compose the Defined Process
Select
the subprocesses that compose the project’s defined process based on historical
stability and capability data.
[PA165.IG101.SP102]
Refer to the Integrated Project Management process area for more information
about establishing and maintaining the project’s defined process.
[PA165.IG101.SP102.R101]
Refer to the Organizational Process Definition process area for more
information about the organization’s process asset library, which might include
a process element of known and needed capability.
[PA165.IG101.SP102.R102]
Refer to the Organizational Process Performance process area for more
information about the organization’s process performance baselines and process
performance models. [PA165.IG101.SP102.R103]
Subprocesses are identified from the process elements in
the organization's set of standard processes and the process artifacts in the
organization's process asset library.
[PA165.IG101.SP102.N101]
Typical Work Products
1. Criteria used in identifying
which subprocesses are valid candidates for inclusion in the project’s defined
process [PA165.IG101.SP102.W101]
2. Candidate subprocesses for
inclusion in the project’s defined process
[PA165.IG101.SP102.W102]
3. Subprocesses to be included
in the project’s defined process [PA165.IG101.SP102.W103]
4. Identified risks when
selected subprocesses lack a process performance history
[PA165.IG101.SP102.W104]
Subpractices
1. Establish the criteria to use in identifying
which subprocesses are valid candidates for use.
[PA165.IG101.SP102.SubP101]
Identification may be based on
the following:
[PA165.IG101.SP102.SubP101.N101]
· Quality and process-performance objectives
· Existence of process-performance data
· Product line standards
· Project life-cycle models
· Customer requirements
· Laws and regulations
2. Determine whether the subprocesses that are
to be statistically managed, and that were obtained from the organizational
process assets, are suitable for statistical management. [PA165.IG101.SP102.SubP102]
A subprocess may be more suitable
for statistical management if it has a history of the following: [PA165.IG101.SP102.SubP102.N101]
· Stable performance in previous comparable instances
· Process performance data that satisfies the project's quality and process-performance objectives
Historical data are primarily
obtained from the organization's process performance baselines. However, these
data may not be available for all subprocesses. [PA165.IG101.SP102.SubP102.N102]
3. Analyze the interaction of subprocesses to
understand the relationships among the subprocesses and the measured attributes
of the subprocesses. [PA165.IG101.SP102.SubP103]
Examples
of analysis techniques include system dynamics models and simulations. [PA165.IG101.SP102.SubP103.N101]
4. Identify the risk when no subprocess is
available that is known to be capable of satisfying the quality and
process-performance objectives (i.e., no capable subprocess is available or the
capability of the subprocess is not known).
[PA165.IG101.SP102.SubP104]
Even when a subprocess has not
been selected to be statistically managed, historical data and process
performance models may indicate that the subprocess is not capable of
satisfying the quality and process-performance objectives. [PA165.IG101.SP102.SubP104.N101]
Refer
to the Risk Management process area for more information about risk
identification and analysis.
[PA165.IG101.SP102.SubP104.N101.R101]
SP 1.3-1 Select the Subprocesses that Will Be Statistically Managed
Select
the subprocesses of the project's defined process that will be statistically
managed. [PA165.IG101.SP103]
Selecting the subprocesses to be statistically managed is
often a concurrent and iterative process of identifying applicable project and
organization quality and process-performance objectives, selecting the
subprocesses, and identifying the process and product attributes to measure and
control. Often the selection of a process, quality and process-performance
objective, or measurable attribute will constrain the selection of the other
two. For example, if a particular process is selected, the measurable
attributes and quality and process-performance objectives may be constrained by
that process.
[PA165.IG101.SP103.N101]
Typical Work Products
1. Quality and
process-performance objectives that will be addressed by statistical management [PA165.IG101.SP103.W101]
2. Criteria used in selecting
which subprocesses will be statistically managed
[PA165.IG101.SP103.W102]
3. Subprocesses that will be statistically
managed [PA165.IG101.SP103.W103]
4. Identified process and
product attributes of the selected subprocesses that should be measured and
controlled [PA165.IG101.SP103.W104]
Subpractices
1. Identify which of the quality and
process-performance objectives of the project will be statistically managed. [PA165.IG101.SP103.SubP101]
2. Identify the criteria to be used in
selecting the subprocesses that are the main contributors to achieving the
identified quality and process-performance objectives and for which predictable
performance is important. [PA165.IG101.SP103.SubP102]
Examples
of sources for criteria used in selecting subprocesses include the following: [PA165.IG101.SP103.SubP102.N102]
· Customer requirements related to quality and process performance
· Quality and process-performance objectives established by the customer
· Quality and process-performance objectives established by the organization
· Organization’s performance baselines and models
· Stable performance of the subprocess on other projects
· Laws and regulations
3. Select the subprocesses that will be
statistically managed using the selection criteria.
[PA165.IG101.SP103.SubP104]
It may not be possible to
statistically manage some subprocesses (e.g., where new subprocesses and
technologies are being piloted). In other cases, it may not be economically
justifiable to apply statistical techniques to certain subprocesses. [PA165.IG101.SP103.SubP104.N101]
4. Identify the product and process attributes
of the selected subprocesses that will be measured and controlled. [PA165.IG101.SP103.SubP103]
Examples
of product and process attributes include the following:
[PA165.IG101.SP103.SubP103.N101]
· Defect density
· Cycle time
· Test coverage
SP 1.4-1 Manage Project Performance
Monitor
the project to determine whether the project’s objectives for quality and
process performance will be satisfied, and identify corrective action as
appropriate. [PA165.IG101.SP104]
Refer to the Measurement and Analysis process area for more information
about analyzing and using measures.
[PA165.IG101.SP104.R101]
A prerequisite for such a comparison is that the selected
subprocesses of the project’s defined process are being statistically managed
and their process capability is understood.
[PA165.IG101.SP104.N101]
Typical Work Products
1. Estimates (predictions) of
the achievement of the project’s quality and process-performance objectives [PA165.IG101.SP104.W101]
2. Documentation of the risks
in achieving the project’s quality and process-performance objectives [PA165.IG101.SP104.W102]
3. Documentation of actions
needed to address the deficiencies in achieving the project’s objectives [PA165.IG101.SP104.W103]
Subpractices
1. Periodically review the performance of each
subprocess and the capability of each subprocess selected to be statistically
managed, to appraise progress toward achieving the project’s quality and
process-performance objectives. [PA165.IG101.SP104.SubP101]
The process capability of each
selected subprocess is determined with respect to that subprocess’ established
quality and process-performance objectives. These objectives are derived from
the project’s quality and process-performance objectives, which are for the
project as a whole.
[PA165.IG101.SP104.SubP101.N101]
2. Periodically review the actual results
achieved against the established interim objectives for each phase of the
project life cycle to appraise progress toward achieving the project’s quality
and process-performance objectives. [PA165.IG101.SP104.SubP102]
3. Track suppliers' results for achieving their
quality and process-performance objectives.
[PA165.IG101.SP104.SubP103]
4. Use process performance models calibrated
with obtained measures of critical attributes to estimate progress toward
achieving the project’s quality and process-performance objectives. Process
performance models are used to estimate progress toward achieving objectives
that cannot be measured until a future phase in the project life cycle. An
example is the use of process performance models to predict the latent defects
in the delivered product using interim measures of defects identified during
peer reviews. [PA165.IG101.SP104.SubP104]
Refer
to the Organizational Process Performance process area for more information
about process performance models.
[PA165.IG101.SP104.SubP104.R101]
The calibration is based on the
results obtained from performing the previous subpractices. [PA165.IG101.SP104.SubP104.N101]
5. Identify and manage the risks associated
with achieving the project’s quality and process-performance objectives. [PA165.IG101.SP104.SubP105]
Refer
to the Risk Management process area for more information about identifying and
managing risks. [PA165.IG101.SP104.SubP105.R101]
Example
sources of the risks include the following:
[PA165.IG101.SP104.SubP105.N101]
· Inadequate stability and capability data in the organization’s measurement repository
· Subprocesses having inadequate performance or capability
· Suppliers not achieving their quality and process-performance objectives
· Lack of visibility into supplier capability
· Inaccuracies in the organization’s process performance models for predicting future performance
· Deficiencies in predicted process performance (estimated progress)
· Other identified risks associated with identified deficiencies
6. Determine and document actions needed to
address the deficiencies in achieving the project’s quality and
process-performance objectives. [PA165.IG101.SP104.SubP106]
The intent of these actions is to
plan and deploy the right set of activities, resources, and schedule to place
the project back on track as much as possible to meet its objectives. [PA165.IG101.SP104.SubP106.N101]
Examples
of actions that can be taken to address deficiencies in achieving the project’s
objectives include the following:
[PA165.IG101.SP104.SubP106.N102]
· Changing quality or process performance objectives so that they are within the expected range of the project’s defined process
· Improving the implementation of the project’s defined process so as to reduce its normal variability (reducing variability may bring the project’s performance within the objectives without having to move the mean)
· Adopting new subprocesses and technologies that have the potential for satisfying the objectives and managing the associated risks
· Identifying the risk and risk mitigation strategies for the deficiencies
· Terminating the project
Refer
to the Project Monitoring and Control process area for more information about
taking corrective action. [PA165.IG101.SP104.SubP106.N102.R101]
SG 2 Statistically Manage Subprocess Performance
The performance of selected subprocesses within
the project's defined process is statistically managed. [PA165.IG102]
This specific goal describes an activity critical to
achieving the Quantitatively Manage the Project specific goal of this process
area. The specific practices under this specific goal describe how to
statistically manage the subprocesses whose selection was described in the
specific practices under the first specific goal. When the selected
subprocesses are statistically managed, their capability to achieve their
objectives can be determined. By these means, it will be possible to predict
whether the project will be able to achieve its objectives, which is key to
quantitatively managing the project.
[PA165.IG102.N101]
SP 2.1-1 Select Measures and Analytic Techniques
Select
the measures and analytic techniques to be used in statistically managing the
selected subprocesses.
[PA165.IG102.SP101]
Refer to the Measurement and Analysis process area for more information
about establishing measurable objectives; on defining, collecting, and
analyzing measures; and on revising measures and statistical analysis techniques.
[PA165.IG102.SP101.R101]
Typical Work Products
1. Definitions of the measures
and analytic techniques to be used in (or proposed for) statistically managing
the subprocesses [PA165.IG102.SP101.W101]
2. Operational definitions of
the measures, their collection points in the subprocesses, and how the
integrity of the measures will be determined
[PA165.IG102.SP101.W102]
3. Traceability of measures
back to the project’s quality and process-performance objectives [PA165.IG102.SP101.W103]
4. Instrumented organizational
support environment to support automatic data collection
[PA165.IG102.SP101.W104]
Subpractices
1. Identify common measures from the
organizational process assets that support statistical management. [PA165.IG102.SP101.SubP101]
Refer
to the Organizational Process Definition process area for more information
about common measures. [PA165.IG102.SP101.SubP101.R101]
Product lines or other
stratification criteria may categorize common measures. [PA165.IG102.SP101.SubP101.N101]
2. Identify additional measures that may be
needed for this instance to cover critical product and process attributes of
the selected subprocesses. [PA165.IG102.SP101.SubP102]
In some cases, measures may be
research oriented. Such measures should be explicitly identified. [PA165.IG102.SP101.SubP102.N102]
3. Identify the measures that are appropriate
for statistical management. [PA165.IG102.SP101.SubP103]
Critical criteria for selecting
statistical management measures include the following: [PA165.IG102.SP101.SubP103.N101]
· Controllable (e.g., can a measure’s values be changed by changing how the subprocess is implemented?)
· Adequate performance indicator (e.g., is the measure a good indicator of how well the subprocess is performing relative to the objectives of interest?)
Examples
of subprocess measures include the following:
[PA165.IG102.SP101.SubP103.N102]
· Requirements volatility
· Ratios of estimated to measured values of the planning parameters (e.g., size, cost, and schedule)
· Coverage and efficiency of peer reviews
· Test coverage and efficiency
· Effectiveness of training (e.g., percent of planned training completed and test scores)
· Reliability
· Percentage of the total defects inserted or found in the different phases of the project life cycle
· Percentage of the total effort expended in the different phases of the project life cycle
4. Specify the operational definitions of the
measures, their collection points in the subprocesses, and how the integrity of
the measures will be determined. [PA165.IG102.SP101.SubP104]
Operational definitions are
stated in precise and unambiguous terms. They address two important criteria as
follows:
[PA165.IG102.SP101.SubP104.N101]
· Communication: What has been measured, how it was measured, what the units of measure are, and what has been included or excluded
· Repeatability: Whether the measurement can be repeated, given the same definition, to get the same results
5. Analyze the relationship of the identified
measures to the organization’s and project’s objectives, and derive objectives
that state specific target measures or ranges to be met for each measured
attribute of each selected subprocess. [PA165.IG102.SP101.SubP105]
6. Instrument the organizational support
environment to support collection, derivation, and analysis of statistical
measures. [PA165.IG102.SP101.SubP106]
The instrumentation is based on
the following:
[PA165.IG102.SP101.SubP106.N101]
· Description of the organization's set of standard processes
· Description of the project’s defined process
· Capabilities of the organizational support environment
7. Identify the appropriate statistical
analysis techniques that are expected to be useful in statistically managing
the selected subprocesses. [PA165.IG102.SP101.SubP107]
The concept of “one size does not
fit all” applies to statistical analysis techniques. What makes a particular
technique appropriate is not just the type of measures, but more importantly,
how the measures will be used and whether the situation warrants applying that
technique. The appropriateness of the selection may need to be investigated
from time to time.
[PA165.IG102.SP101.SubP107.N101]
Examples of statistical analysis
techniques are given in the next specific practice. [PA165.IG102.SP101.SubP107.N102]
8. Revise the measures and statistical analysis
techniques as necessary. [PA165.IG102.SP101.SubP108]
SP 2.2-1 Apply Statistical Methods to Understand Variation
Establish
and maintain an understanding of the variation of the selected subprocesses
using the selected measures and analytic techniques. [PA165.IG102.SP102]
Refer to the Measurement and Analysis process area for more information
about collecting, analyzing, and using measure results.
[PA165.IG102.SP102.R101]
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. [PA165.IG102.SP102.N101]
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.
[PA165.IG102.SP102.N102]
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 the data collected from the subprocess or associated
work products. Knowledge of variation and insight about potential sources of
anomalous patterns are typically needed to detect special causes of variation. [PA165.IG102.SP102.N103]
Sources of
anomalous patterns of variation may include the following: [PA165.IG102.SP102.N104]
· Lack of process compliance
· Undistinguished influences of multiple underlying subprocesses on the data
· Ordering or timing of activities within the subprocess
· Uncontrolled inputs to the subprocess
· Environmental changes during subprocess execution
· Schedule pressure
· Inappropriate sampling or grouping of data
Typical Work Products
1. Collected measures [PA165.IG102.SP102.W101]
2. Natural bounds of process
performance for each measured attribute of each selected subprocess [PA165.IG102.SP102.W102]
3. Process performance
compared to the natural bounds of process performance for each measured
attribute of each selected subprocess [PA165.IG102.SP102.W103]
Subpractices
1. Establish trial natural bounds for
subprocesses having suitable historical performance data. [PA165.IG102.SP102.SubP101]
Refer
to the Organizational Process Performance process area for more information
about organizational process performance baselines.
[PA165.IG102.SP102.SubP101.R101]
Natural bounds of an attribute
are the range within which variation normally occurs. All processes will 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.
[PA165.IG102.SP102.SubP101.N101]
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. These data are
typically 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 in
question has been materially tailored, or if the conditions are materially
different than in previous instantiations, the data in the repository may not
be relevant and should not be used. [PA165.IG102.SP102.SubP101.N102]
In some cases, there may be no
historical comparable data (for example, 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. [PA165.IG102.SP102.SubP101.N103]
Examples
of criteria for determining whether data are comparable include the following: [PA165.IG102.SP102.SubP101.N104]
· Product lines
· Application domain
· Work product and task attributes (e.g., size of product)
· Size of project
2. Collect data, as defined by the selected
measures, on the subprocesses as they execute.
[PA165.IG102.SP102.SubP102]
3. Calculate the natural bounds of process
performance for each measured attribute.
[PA165.IG102.SP102.SubP103]
Examples
of where the natural bounds are calculated include the following: [PA165.IG102.SP102.SubP103.N101]
· Control charts
· Confidence intervals (for parameters of distributions)
· Prediction intervals (for future outcomes)
4. Identify special causes of variation. [PA165.IG102.SP102.SubP104]
An
example of a criterion for detecting a special cause of process variation in a
control chart is a data point that falls outside of the 3-sigma control limits. [PA165.IG102.SP102.SubP104.N101]
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 present, but the likelihood of false alarms
also increases.
[PA165.IG102.SP102.SubP104.N102]
5. Analyze the special cause of process
variation to determine the reasons the anomaly occurred.
[PA165.IG102.SP102.SubP105]
Examples
of techniques for analyzing the reasons for special causes of variation include
the following: [PA165.IG102.SP102.SubP105.N101]
· Cause-and-effect (fishbone) diagrams
· Designed experiments
· Control charts (applied to subprocess inputs or to lower level subprocesses)
· Subgrouping (analyzing the same data segregated into smaller groups based on an understanding of how the subprocess was implemented facilitates isolation of special causes)
Some anomalies may simply be
extremes of the underlying distribution rather than problems. The people
implementing a subprocess are usually the ones best able to analyze and
understand special causes of variation. [PA165.IG102.SP102.SubP105.N102]
6. Determine what corrective action should be
taken when special causes of variation are identified.
[PA165.IG102.SP102.SubP106]
Removing a special cause of
process variation does not change the underlying subprocess. It addresses an
error in the way the subprocess is being executed. [PA165.IG102.SP102.SubP106.N101]
Refer
to the Project Monitoring and Control process area for more information about
taking corrective action. [PA165.IG102.SP102.SubP106.N101.R101]
7. Recalculate the natural bounds for each
measured attribute of the selected subprocesses as necessary. [PA165.IG102.SP102.SubP107]
Recalculating the (statistically
estimated) natural bounds is based on measured values that signify that the
subprocess has changed, not on expectations or arbitrary decisions. [PA165.IG102.SP102.SubP107.N101]
Examples
of when the natural bounds may need to be recalculated include the following: [PA165.IG102.SP102.SubP107.N102]
· There are incremental improvements to the subprocess
· New tools are deployed for the subprocess
· A new subprocess is deployed
· The collected measures suggest that the subprocess mean has permanently shifted or the subprocess variation has permanently changed
SP 2.3-1 Monitor Performance of the Selected Subprocesses
Monitor
the performance of the selected subprocesses to determine their capability to
satisfy their quality and process-performance objectives, and identify
corrective action as necessary.
[PA165.IG102.SP103]
The intent of this specific practice is to do the
following:
[PA165.IG102.SP103.N101]
· Determine statistically the process behavior expected from the subprocess
· Appraise the probability that the process will meet its quality and process-performance objectives
· Identify the corrective action to be taken, based upon a statistical analysis of the process performance data
Corrective action may include renegotiating the affected
project objectives, identifying and implementing alternative subprocesses, or
identifying and measuring lower level subprocesses to achieve greater detail in
the performance data. Any or all of these actions are intended to help the
project use a more capable process. See the definition of “capable process” in
Appendix C, the glossary. [PA165.IG102.SP103.N102]
A prerequisite for comparing the capability of a selected
subprocess against its quality and process-performance objectives is that the
performance of the subprocess is stable and predictable with respect to its
measured attributes. [PA165.IG102.SP103.N104]
Process capability is analyzed for those subprocesses and
those measured attributes for which (derived) objectives have been established.
Not all subprocesses or measured attributes that are statistically managed are
analyzed regarding process capability.
[PA165.IG102.SP103.N105]
The historical data may be inadequate for initially
determining whether the subprocess is capable. It also is possible that the
estimated natural bounds for subprocess performance may shift away from the quality
and process-performance objectives. In either case, statistical control implies
monitoring capability as well as stability.
[PA165.IG102.SP103.N106]
Typical Work Products
1. Natural bounds of process
performance for each selected subprocess compared to its established (derived)
objectives [PA165.IG102.SP103.W101]
2. For each subprocess, its
process capability [PA165.IG102.SP103.W102]
3. For each subprocess, the
actions needed to address deficiencies in its process capability [PA165.IG102.SP103.W103]
Subpractices
1. Compare the quality and process-performance
objectives to the natural bounds of the measured attribute. [PA165.IG102.SP103.SubP101]
This comparison provides an
appraisal of the process capability for each measured attribute of a subprocess.
These comparisons can be displayed graphically, in ways that relate the
estimated natural bounds to the objectives or as process capability indices,
which summarize the relationship of the objectives to the natural bounds. [PA165.IG102.SP103.SubP101.N101]
2. Monitor changes in quality and
process-performance objectives and selected subprocess’ process capability. [PA165.IG102.SP103.SubP102]
3. Identify and document subprocess capability
deficiencies. [PA165.IG102.SP103.SubP103]
4. Determine and document actions needed to
address subprocess capability deficiencies.
[PA165.IG102.SP103.SubP104]
Examples
of actions that can be taken when a selected subprocess’ performance does not
satisfy its objectives include the following: [PA165.IG102.SP103.SubP104.N101]
· Changing quality and process-performance objectives so that they are within the subprocess’ process capability
· Improving the implementation of the existing subprocess so as to reduce its normal variability (reducing variability may bring the natural bounds within the objectives without having to move the mean)
· Adopting new process elements and subprocesses and technologies that have the potential for satisfying the objectives and managing the associated risks
· Identifying risks and risk mitigation strategies for each subprocess’ process capability deficiency
Refer
to the Project Monitoring and Control process area for more information about
taking corrective action. [PA165.IG102.SP103.SubP104.N101.R101]
SP 2.4-1 Record Statistical Management Data
Record
statistical and quality management data in the organization’s measurement
repository. [PA165.IG102.SP104]
Refer to the Measurement and Analysis process area for more information
about managing and storing data, measurement definitions, and results.
[PA165.IG102.SP104.R101]
Refer to the Organizational Process Definition process area for more
information about the organization’s measurement repository.
[PA165.IG102.SP104.R102]
Typical Work Products
1. Statistical and quality
management data recorded in the organization’s measurement repository [PA165.IG102.SP104.W101]
Generic Practices by Goal
(Note: The detailed description of the GPs is available in a separate web page. Using the hyperlink provided here will open that web page in a separate window. However, the GP elaborations pertinent to the process area of this web page are available below.)
GG 1 Achieve Specific Goals
The process supports and enables achievement of the specific goals of the process area by transforming identifiable input work products to produce identifiable output work products.
Perform
the base practices of the quantitative project management process to develop
work products and provide services to achieve the specific goals of the process
area. [GP102]
GG 2 Institutionalize a Managed Process
The process is institutionalized as a managed process.
GP 2.1 Establish an Organizational Policy
Establish
and maintain an organizational policy for planning and performing the
quantitative project management process.
[GP103]
Elaboration:
This policy establishes organizational expectations for
quantitatively managing the project using quality and process-performance
objectives, and statistically managing selected subprocesses within the
project’s defined process [PA165.EL101]
Establish
and maintain the plan for performing the quantitative project management
process. [GP104]
Elaboration:
Typically, this plan for performing the quantitative
project management process is included in (or referenced by) the project plan,
which is described in the Project Planning process area. [PA165.EL111]
Provide
adequate resources for performing the quantitative project management process,
developing the work products, and providing the services of the process. [GP105]
Elaboration:
Special expertise in statistics and statistical process
control may be needed to define the techniques for statistical management of
selected subprocesses, but staff will use the tools and techniques to perform
the statistical management. Special expertise in statistics may also be needed
for analyzing and interpreting the measures resulting from statistical
management. [PA165.EL102]
Examples of
other resources provided include the following tools: [PA165.EL103]
· System dynamics models
· Automated test-coverage analyzers
· Statistical process and quality control packages
· Statistical analysis packages
Assign
responsibility and authority for performing the process, developing the work
products, and providing the services of the quantitative project management
process. [GP106]
Train
the people performing or supporting the quantitative project management process
as needed. [GP107]
Elaboration:
Examples of
training topics include the following: [PA165.EL104]
· Process modeling and analysis
· Process measurement data selection, definition, and collection
Place
designated work products of the quantitative project management process under
appropriate levels of configuration management.
[GP109]
Elaboration:
Examples of
work products placed under configuration management include the following: [PA165.EL110]
· Subprocesses to be included in the project’s defined process
· Operational definitions of the measures, their collection points in the subprocesses, and how the integrity of the measures will be determined
· Collected measures
GP 2.7 Identify and Involve Relevant Stakeholders
Identify
and involve the relevant stakeholders of the quantitative project management
process as planned. [GP124]
Elaboration:
Examples of
activities for stakeholder involvement include the following: [PA165.EL109]
· Establishing project objectives
· Resolving issues among the project’s quality and process-performance objectives
· Appraising performance of the selected subprocesses
· Identifying and managing the risks in achieving the project’s quality and process-performance objectives
· Identifying what corrective action should be taken
GP 2.8 Monitor and Control the Process
Monitor
and control the quantitative project management process against the plan for
performing the process and take appropriate corrective action. [GP110]
Elaboration:
Examples of
measures used in monitoring and controlling include the following: [PA165.EL105]
· Profile of subprocesses under statistical management (e.g., number planned to be under statistical management, number currently being statistically managed, and number that are statistically stable)
· Number of special causes of variation identified
GP 2.9 Objectively Evaluate Adherence
Objectively
evaluate adherence of the quantitative project management process against its
process description, standards, and procedures, and address noncompliance. [GP113]
Elaboration:
Examples of
activities reviewed include the following: [PA165.EL106]
· Quantitatively managing the project using quality and process-performance objectives
· Statistically managing selected subprocesses within the project’s defined process
Examples of
work products reviewed include the following: [PA165.EL108]
· Subprocesses to be included in the project’s defined process
· Operational definitions of the measures
· Collected measures
GP 2.10 Review Status with Higher Level Management
Review
the activities, status, and results of the quantitative project management
process with higher level management and resolve issues. [GP112]
GG 3 Institutionalize a Defined Process
The process is institutionalized as a defined process.
GP 3.1 Establish a Defined Process
Establish
and maintain the description of a defined quantitative project management
process. [GP114]
GP 3.2 Collect Improvement Information
Collect
work products, measures, measurement results, and improvement information
derived from planning and performing the quantitative project management
process to support the future use and improvement of the organization’s
processes and process assets. [GP117]
GG 4 Institutionalize a Quantitatively Managed Process
The process is institutionalized as a quantitatively managed process.
GP 4.1 Establish Quantitative Objectives for the Process
Establish
and maintain quantitative objectives for the quantitative project management
process that address quality and process performance based on customer needs
and business objectives. [GP118]
GP 4.2 Stabilize Subprocess Performance
Stabilize
the performance of one or more subprocesses to determine the ability of the
quantitative project management process to achieve the established quantitative
quality and process-performance objectives.
[GP119]
GG 5 Institutionalize an Optimizing Process
The process is institutionalized as an optimizing process.
GP 5.1 Ensure Continuous Process Improvement
Ensure
continuous improvement of the quantitative project management process in
fulfilling the relevant business objectives of the organization. [GP125]
GP 5.2 Correct Root Causes of Problems
Identify
and correct the root causes of defects and other problems in the quantitative
project management process. [GP121]