Cmme process domain-ma Measurement and Analysis

Measurement process framework:

Measurement and analysis process fields include:

• Describe in detail the purpose of measurement and analysis so that it is consistent with the identified information and purpose
• Detailed description of measurement, data collection, storage mechanism, analysis technology, and report and feedback mechanism
• Data collection, storage, analysis, and reporting
• Provide objective results that can be used to make reliable decisions and take appropriate corrective actions

Integrate measurement and analysis activities with other processes of the project to support:

• Objective PLANNING AND ESTIMATION
• Track actual performance based on established plans and objectives
• Identify and resolve process-related issues
• Provides the basis for combining metrics into future additional processes

Note that second-level measurements are concentrated at the project level. Projects can store specific project data and results in a dedicated project library. When data is widely shared among projects, data can reside in an organization-level measurement warehouse. To establish an organization-level measurement database, you should refer to the three-level process domain OPD organization process definition. After the measurement has been analyzed to four levels, you need to use statistical methods and tools for quantitative analysis, it involves four levels of QPM to quantify the content of the project management process domain.

SG 1 adjust measurement and analysis activities (the purpose and activity of a measurement must be consistent with the identified information and purpose)

• SP 1.1 create a Metric
• SP 1.2 detailed metric description
• SP 1.3 detailed data collection and storage procedures
• SP 1.4 detailed analysis procedure

Before performing a measurement plan and implementing a measurement, you must clearly define the purpose of the measurement. The purpose of the measurement is to improve the effectiveness of our process, improve the efficiency and quality through collected data analysis. The source of measurement goals can be management, technology, project, product or process implementation needs, from the enterprise's strategic and commercial plans, project plans, management and technical issues, process improvement plan.

The classification of measurement information can be divided

• Progress and Progress (implementation of milestones and implementation of work units)
• Resources and costs (human resources and other expenses allocated by the Project)
• Product scale and stability (software scale, software function scope and quantity change)
• Product quality (defect density, on-site defects)
• Process Performance (evaluation efficiency, defect leakage, process conformity, and nonconforming items)
• Technical effectiveness (software architecture and software reuse)
• Customer Satisfaction (the degree to which the delivered products and services meet customer expectations)

In sp1.2, the point is that the measurement itself is accurate and quantifiable. A measurement may be a basic measurement or a derived measurement. Basic metric data is obtained by direct measurements. Derived metric data comes from other data, usually composed of two or more basic measurements. For example, the number of defects is a basic measurement, and the defect density is a derived measurement.

After establishing the purpose of the measurement and determining the measurement method, go to sp1.3 to solve the problem of metric data collection and storage. It is necessary to clearly describe how data is collected, where data is collected, and when data is collected. Specifies the procedure for collecting valid data. To analyze data, data is stored in an accessible manner, and you need to determine whether it is possible to re-analyze or save it for document purposes.

After data is collected and stored, You need to select appropriate data analysis methods and tools, after QPM quantitative management, we will emphasize the statistical methods and tools used for different subprocesses.

SG 2 provides measurement results to process identified information needs and objectives

• SP 2.1 measure data acquisition: Obtain specific measure data
• SP 2.2 analyze metric data
• SP 2.3 stores data and results
• SP 2.4 exchange results

Note that in SG1, specific methods and procedures are developed, and in SP2, actual measurement execution activities are performed. In sp2.1, the execution data of the activities to be measured is collected according to the measurement procedure. After the data is collected, the integrity of the data must be checked to ensure the accuracy and effectiveness of the data. The measurement is often ineffective or does not play a practical role. The biggest reason is not the measurement methods and tools, but the data we collect is inaccurate or incorrect, the final analysis result is also incorrect.

In sp2.2, metric data is analyzed according to the plan, and additional analysis is required when necessary. The results are reviewed by relevant project personnel, and necessary revisions should be made to the analysis in the future. After collecting and analyzing metric data, we need to store the measured data as an important parameter for project planning and estimation.

The storage of metric data mainly includes:

• Measurement plan
• Specifications
• Collected Dataset
• Analysis report and statement

Metric data in level-2 projects mainly serves the needs of projects and individuals. After Level 3, the project metric data is stored in the organization-level measurement database to facilitate the establishment of measurement baselines at the organization level. The specific content is in the level-3 OPD process domain.

Dimensions recommended by SEI

• Progress performance (milestone performance, unit progress)
• Cost Performance (comparison with the plan, inconsistency)
• Workload performance (actual comparison with the plan, inconsistency)
• Demand management (added, deleted, modified, and demand variable)
• Program Scale (compare the number of lines and pages of source code with the Plan)
• Test performance (required tests, passed tests)
• Defect data status (unsolved problems, completed problems, defect density, and defect source)
• Process Performance (number of completed tasks and actions)
• Computer Resource Utilization (memory usage, CPU usage)
• Manage the performance of the planned project process (estimate, re-plan, and summarize project data based on actual progress)

In Level 3, we mainly want to increase the measurement level to the organizational level. In gg3, we also talked about the process to systematize the measurement activity to the defined organizational level, an organization can establish an organizational process capability baseline by collecting metric data of each project. In Level 4, we should pay attention to the need for measurement to reach the granularity of each sub-process we need to monitor. At the same time, we need to use statistics-related methods and tools for measurement data analysis. Specific metric requirements involved in Level 4 of CMMs:

1. Determine the project objectives based on the business objectives and the project objectives
2. Select the most valuable sub-processes for quantitative management based on the quality and performance objectives, with granularity up to sub-Processes
3. Use statistical methods and ideas instead of simply using SPC
4. QFD can be decomposed layer by layer to select measurement technologies and sub-processes.

5. measurement is the basis for process management, not just for future data collection and tracking
6. Better ppb management of current Project Performance Based on Process Capability baseline and controlled process
7. better prediction of the future based on the Process Capability Model ppm