SG 1 Align Measurement and Analysis Activities Measurement objectives and activities are aligned with identified information needs and objectives. The specific practices covered under this specific goal may be addressed concurrently or in any order: Table . Practice-to-Goal Relationship Table | Continuous Representation | Staged Representation | | SG 1 Align Measurement and Analysis Activities | SG 1 Align Measurement and Analysis Activities | SP 1.1-1 Establish Measurement Objectives | SP 1.1-1 Establish Measurement Objectives | SP 1.2-1 Specify Measures | SP 1.2-1 Specify Measures | SP 1.3-1 Specify Data Collection and Storage Procedures | SP 1.3-1 Specify Data Collection and Storage Procedures | SP 1.4-1 Specify Analysis Procedures | SP 1.4-1 Specify Analysis Procedures | | SG 2 Provide Measurement Results | SG 2 Provide Measurement Results | SP 2.1-1 Collect Measurement Data | SP 2.1-1 Collect Measurement Data | SP 2.2-1 Analyze Measurement Data | SP 2.2-1 Analyze Measurement Data | SP 2.3-1 Store Data and Results | SP 2.3-1 Store Data and Results | SP 2.4-1 Communicate Results | SP 2.4-1 Communicate Results | | GG 1 Achieve Specific Goals | | GP 1.1 Perform Base Practices | | | GG 2 Institutionalize a Managed Process | GG 2 Institutionalize a Managed Process | GP 2.1 Establish an Organizational Policy | GP 2.1 Establish an Organizational Policy | GP 2.2 Plan the Process | GP 2.2 Plan the Process | GP 2.3 Provide Resources | GP 2.3 Provide Resources | GP 2.4 Assign Responsibility | GP 2.4 Assign Responsibility | GP 2.5 Train People | GP 2.5 Train People | GP 2.6 Manage Configurations | GP 2.6 Manage Configurations | GP 2.7 Identify and Involve Relevant Stakeholders | GP 2.7 Identify and Involve Relevant Stakeholders | GP 2.8 Monitor and Control the Process | GP 2.8 Monitor and Control the Process | GP 2.9 Objectively Evaluate Adherence | GP 2.9 Objectively Evaluate Adherence | GP 2.10 Review Status with Higher Level Management | GP 2.10 Review Status with Higher Level Management | | GG 3 Institutionalize a Defined Process | GG 3 Institutionalize a Defined Process | GP 3.1 Establish a Defined Process | GP 3.1 Establish a Defined Process | GP 3.2 Collect Improvement Information | GP 3.2 Collect Improvement Information | | GG 4 Institutionalize a Quantitatively Managed Process | | GP 4.1 Establish Quantitative Objectives for the Process | | GP 4.2 Stabilize Subprocess Performance | | | GG 5 Institutionalize an Optimizing Process | | GP 5.1 Ensure Continuous Process Improvement | | GP 5.2 Correct Root Causes of Problems | | SP 1.1-1 Establish Measurement Objectives Establish and maintain measurement objectives that are derived from identified information needs and objectives. Measurement objectives document the purposes for which measurement and analysis are done, and specify the kinds of actions that may be taken based on the results of data analyses. The sources for measurement objectives may be management, technical, project, product, or process implementation needs. The measurement objectives may be constrained by existing processes, available resources, or other measurement considerations. Judgments may need to be made about whether the value of the results will be commensurate with the resources devoted to doing the work. Modifications to identified information needs and objectives may, in turn, be indicated as a consequence of the process and results of measurement and analysis. Sources of information needs and objectives may include the following: Project plans Monitoring of project performance Interviews with managers and others who have information needs Established management objectives Strategic plans Business plans Formal requirements or contractual obligations Recurring or other troublesome management or technical problems Experiences of other projects or organizational entities External industry benchmarks Process-improvement plans Refer to the Project Planning process area for more information about estimating project attributes and other planning information needs. Refer to the Project Monitoring and Control process area for more information about project performance information needs. Refer to the Requirements Development process area for more information about meeting customer requirements and related information needs. Refer to the Requirements Management process area for more information about maintaining requirements traceability and related information needs. Typical Work Products Measurement objectives Subpractices Document information needs and objectives. Information needs and objectives are documented to allow traceability to subsequent measurement and analysis activities. Prioritize information needs and objectives. It may be neither possible nor desirable to subject all initially identified information needs to measurement and analysis. Priorities may also need to be set within the limits of available resources. Document, review, and update measurement objectives. It is important to carefully consider the purposes and intended uses of measurement and analysis. The measurement objectives are documented, reviewed by management and other relevant stakeholders, and updated as necessary. Doing so enables traceability to subsequent measurement and analysis activities, and helps ensure that the analyses will properly address identified information needs and objectives. It is important that users of measurement and analysis results be involved in setting measurement objectives and deciding on plans of action. It may also be appropriate to involve those who provide the measurement data. Provide feedback for refining and clarifying information needs and objectives as necessary. Identified information needs and objectives may need to be refined and clarified as a result of setting measurement objectives. Initial descriptions of information needs may be unclear or ambiguous. Conflicts may arise between existing needs and objectives. Precise targets on an already existing measure may be unrealistic. Maintain traceability of the measurement objectives to the identified information needs and objectives. There must always be a good answer to the question, "Why are we measuring this?" Of course, the measurement objectives may also change to reflect evolving information needs and objectives. SP 1.2-1 Specify Measures Specify measures to address the measurement objectives. Measurement objectives are refined into precise, quantifiable measures. Measures may be either "base" or "derived." Data for base measures are obtained by direct measurement. Data for derived measures come from other data, typically by combining two or more base measures. | Examples of commonly used base measures include the following: Estimates and actual measures of work product size (e.g., number of pages) Estimates and actual measures of effort and cost (e.g., number of person hours) Quality measures (e.g., number of defects, number of defects by severity) |
| Examples of commonly used derived measures include the following: Earned Value Schedule Performance Index Defect density Peer review coverage Test or verification coverage Reliability measures (e.g., mean time to failure) Quality measures (e.g., number of defects by severity/total number of defects) |
Derived measures typically are expressed as ratios, composite indices, or other aggregate summary measures. They are often more quantitatively reliable and meaningfully interpretable than the base measures used to generate them. Typical Work Products Specifications of base and derived measures Subpractices Identify candidate measures based on documented measurement objectives. The measurement objectives are refined into specific measures. The identified candidate measures are categorized and specified by name and unit of measure. Identify existing measures that already address the measurement objectives. Specifications for measures may already exist, perhaps established for other purposes earlier or elsewhere in the organization. Specify operational definitions for the measures. Operational definitions are stated in precise and unambiguous terms. They address two important criteria as follows: Communication: What has been measured, how was it measured, what are the units of measure, and what has been included or excluded? Repeatability: Can the measurement be repeated, given the same definition, to get the same results? Prioritize, review, and update measures. Proposed specifications of the measures are reviewed for their appropriateness with potential end users and other relevant stakeholders. Priorities are set or changed, and specifications of the measures are updated as necessary. SP 1.3-1 Specify Data Collection and Storage Procedures Specify how measurement data will be obtained and stored. Explicit specification of collection methods helps ensure that the right data are collected properly. It may also aid in further clarifying information needs and measurement objectives. Proper attention to storage and retrieval procedures helps ensure that data are available and accessible for future use. Typical Work Products Data collection and storage procedures Data collection tools Subpractices Identify existing sources of data that are generated from current work products, processes, or transactions. Existing sources of data may already have been identified when specifying the measures. Appropriate collection mechanisms may exist whether or not pertinent data have already been collected. Identify measures for which data are needed, but are not currently available. Specify how to collect and store the data for each required measure. Explicit specifications are made of how, where, and when the data will be collected. Procedures for collecting valid data are specified. The data are stored in an accessible manner for analysis, and it is determined whether they will be saved for possible reanalysis or documentation purposes. Questions to be considered typically include the following: Have the frequency of collection and the points in the process where measurements will be made been determined? Has the time line that is required to move measurement results from the points of collection to repositories, other databases, or end users been established? Who is responsible for obtaining the data? Who is responsible for data storage, retrieval, and security? Have necessary supporting tools been developed or acquired? Create data collection mechanisms and process guidance. Data collection and storage mechanisms are well integrated with other normal work processes. Data collection mechanisms may include manual or automated forms and templates. Clear, concise guidance on correct procedures is available to those responsible for doing the work. Training is provided as necessary to clarify the processes necessary for collection of complete and accurate data and to minimize the burden on those who must provide and record the data. Support automatic collection of the data where appropriate and feasible. Automated support can aid in collecting more complete and accurate data. Examples of such automated support include the following: |
However, some data cannot be collected without human intervention (e.g., customer satisfaction or other human judgments), and setting up the necessary infrastructure for other automation may be costly. Prioritize, review, and update data collection and storage procedures. Proposed procedures are reviewed for their appropriateness and feasibility with those who are responsible for providing, collecting, and storing the data. They also may have useful insights about how to improve existing processes, or be able to suggest other useful measures or analyses. Update measures and measurement objectives as necessary. Priorities may need to be reset based on the following: Considerations include whether new forms, tools, or training would be required to obtain the data. SP 1.4-1 Specify Analysis Procedures Specify how measurement data will be analyzed and reported. Specifying the analysis procedures in advance ensures that appropriate analyses will be conducted and reported to address the documented measurement objectives (and thereby the information needs and objectives on which they are based). This approach also provides a check that the necessary data will in fact be collected. Typical Work Products Analysis specification and procedures Data analysis tools Subpractices Specify and prioritize the analyses that will be conducted and the reports that will be prepared. Early attention should be paid to the analyses that will be conducted and to the manner in which the results will be reported. These should meet the following criteria: Priorities may have to be set within available resources. Select appropriate data analysis methods and tools. Refer to the Select Measures and Analytic Techniques and Apply Statistical Methods to Understand Variation specific practices of the Quantitative Project Management process area for more information about the appropriate use of statistical analysis techniques and understanding variation, respectively. Issues to be considered typically include the following: Choice of visual display and other presentation techniques (e.g., pie charts, bar charts, histograms, radar charts, line graphs, scatter plots, or tables) Choice of appropriate descriptive statistics (e.g., arithmetic mean, median, or mode) Decisions about statistical sampling criteria when it is impossible or unnecessary to examine every data element Decisions about how to handle analysis in the presence of missing data elements Selection of appropriate analysis tools Descriptive statistics are typically used in data analysis to do the following: Examine distributions on the specified measures (e.g., central tendency, extent of variation, data points exhibiting unusual variation) Examine the interrelationships among the specified measures (e.g., comparisons of defects by phase of the product's life cycle or by product component) Display changes over time Specify administrative procedures for analyzing the data and communicating the results. Issues to be considered typically include the following: Identifying the persons and groups responsible for analyzing the data and presenting the results Determining the time line to analyze the data and present the results Determining the venues for communicating the results (e.g., progress reports, transmittal memos, written reports, or staff meetings) Review and update the proposed content and format of the specified analyses and reports. All of the proposed content and format are subject to review and revision, including analytic methods and tools, administrative procedures, and priorities. The relevant stakeholders consulted should include intended end users, sponsors, data analysts, and data providers. Update measures and measurement objectives as necessary. Just as measurement needs drive data analysis, clarification of analysis criteria can affect measurement. Specifications for some measures may be refined further based on the specifications established for data analysis procedures. Other measures may prove to be unnecessary, or a need for additional measures may be recognized. The exercise of specifying how measures will be analyzed and reported may also suggest the need for refining the measurement objectives themselves. Specify criteria for evaluating the utility of the analysis results, and of the conduct of the measurement and analysis activities. Criteria for evaluating the utility of the analysis might address the extent to which the following apply: The results are (1) provided on a timely basis, (2) understandable, and (3) used for decision making. The work does not cost more to perform than is justified by the benefits that it provides. Criteria for evaluating the conduct of the measurement and analysis might include the extent to which the following apply: The amount of missing data or the number of flagged inconsistencies is beyond specified thresholds. There is selection bias in sampling (e.g., only satisfied end users are surveyed to evaluate end-user satisfaction, or only unsuccessful projects are evaluated to determine overall productivity). The measurement data are repeatable (e.g., statistically reliable). Statistical assumptions have been satisfied (e.g., about the distribution of data or about appropriate measurement scales). SG 2 Provide Measurement Results Measurement results that address identified information needs and objectives are provided. The primary reason for doing measurement and analysis is to address identified information needs and objectives. Measurement results based on objective evidence can help to monitor performance, fulfill contractual obligations, make informed management and technical decisions, and enable corrective actions to be taken. SP 2.1-1 Collect Measurement Data Obtain specified measurement data. The data necessary for analysis are obtained and checked for completeness and integrity. Typical Work Products Base and derived measurement data sets Results of data integrity tests Subpractices Obtain the data for base measures. Data are collected as necessary for previously used as well as for newly specified base measures. Existing data are gathered from project records or from elsewhere in the organization. Note that data that were collected earlier may no longer be available for reuse in existing databases, paper records, or formal repositories. Generate the data for derived measures. Values are newly calculated for all derived measures. Perform data integrity checks as close to the source of the data as possible. All measurements are subject to error in specifying or recording data. It is always better to identify such errors and to identify sources of missing data early in the measurement and analysis cycle. Checks can include scans for missing data, out-of-bounds data values, and unusual patterns and correlation across measures. It is particularly important to do the following: Test and correct for inconsistency of classifications made by human judgment (i.e., to determine how frequently people make differing classification decisions based on the same information, otherwise known as "inter-coder reliability"). Empirically examine the relationships among the measures that are used to calculate additional derived measures. Doing so can ensure that important distinctions are not overlooked and that the derived measures convey their intended meanings (otherwise known as "criterion validity"). SP 2.2-1 Analyze Measurement Data Analyze and interpret measurement data. The measurement data are analyzed as planned, additional analyses are conducted as necessary, results are reviewed with relevant stakeholders, and necessary revisions for future analyses are noted. Typical Work Products Analysis results and draft reports Subpractices Conduct initial analyses, interpret the results, and draw preliminary conclusions. The results of data analyses are rarely self-evident. Criteria for interpreting the results and drawing conclusions should be stated explicitly. Conduct additional measurement and analysis as necessary, and prepare results for presentation. The results of planned analyses may suggest (or require) additional, unanticipated analyses. In addition, they may identify needs to refine existing measures, to calculate additional derived measures, or even to collect data for additional primitive measures to properly complete the planned analysis. Similarly, preparing the initial results for presentation may identify the need for additional, unanticipated analyses. Review the initial results with relevant stakeholders. It may be appropriate to review initial interpretations of the results and the way in which they are presented before disseminating and communicating them more widely. Reviewing the initial results before their release may prevent needless misunderstandings and lead to improvements in the data analysis and presentation. Relevant stakeholders with whom reviews may be conducted include intended end users and sponsors, as well as data analysts and data providers. Refine criteria for future analyses. Valuable lessons that can improve future efforts are often learned from conducting data analyses and preparing results. Similarly, ways to improve measurement specifications and data collection procedures may become apparent, as may ideas for refining identified information needs and objectives. SP 2.3-1 Store Data and Results Manage and store measurement data, measurement specifications, and analysis results. Storing measurement-related information enables the timely and cost-effective future use of historical data and results. The information also is needed to provide sufficient context for interpretation of the data, measurement criteria, and analysis results. Information stored typically includes the following: Measurement plans Specifications of measures Sets of data that have been collected Analysis reports and presentations The stored information contains or references the information needed to understand and interpret the measures and to assess them for reasonableness and applicability (e.g., measurement specifications used on different projects when comparing across projects). Data sets for derived measures typically can be recalculated and need not be stored. However, it may be appropriate to store summaries based on derived measures (e.g., charts, tables of results, or report prose). Interim analysis results need not be stored separately if they can be efficiently reconstructed. Projects may choose to store project-specific data and results in a project-specific repository. When data are shared more widely across projects, the data may reside in the organization's measurement repository. Refer to the Establish the Organization's Measurement Repository specific practice of the Organizational Process Definition process area for more information about establishing the organization's measurement repository. Refer to the Configuration Management process area for information about managing measurement work products. Typical Work Products Stored data inventory Subpractices Review the data to ensure their completeness, integrity, accuracy, and currency. Make the stored contents available for use only by appropriate groups and personnel. Prevent the stored information from being used inappropriately. | Examples of ways to prevent inappropriate use of the data and related information include controlling access to data and educating people on the appropriate use of data. |
| Examples of inappropriate use include the following: Disclosure of information that was provided in confidence Faulty interpretations based on incomplete, out-of-context, or otherwise misleading information Measures used to improperly evaluate the performance of people or to rank projects Impugning the integrity of specific individuals |
SP 2.4-1 Communicate Results Report results of measurement and analysis activities to all relevant stakeholders. The results of the measurement and analysis process are communicated to relevant stakeholders in a timely and usable fashion to support decision making and assist in taking corrective action. Relevant stakeholders include intended users, sponsors, data analysts, and data providers. Typical Work Products Delivered reports and related analysis results Contextual information or guidance to aid in the interpretation of analysis results Subpractices Keep relevant stakeholders apprised of measurement results on a timely basis. Measurement results are communicated in time to be used for their intended purposes. Reports are unlikely to be used if they are distributed with little effort to follow up with those who need to know the results. To the extent possible and as part of the normal way they do business, users of measurement results are kept personally involved in setting objectives and deciding on plans of action for measurement and analysis. The users are regularly kept apprised of progress and interim results. Refer to the Project Monitoring and Control process area for more information about the use of measurement results. Assist relevant stakeholders in understanding the results. Results are reported in a clear and concise manner appropriate to the methodological sophistication of the relevant stakeholders. They are understandable, easily interpretable, and clearly tied to identified information needs and objectives. The data are often not self-evident to practitioners who are not measurement experts. Measurement choices should be explicitly clear about the following: How and why the base and derived measures were specified How the data were obtained How to interpret the results based on the data analysis methods that were used How the results address information needs | Examples of actions to assist in understanding of results include the following: Discussing the results with the relevant stakeholders Providing a transmittal memo that provides background and explanation Briefing users on the results Providing training on the appropriate use and understanding of measurement results |
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