We are a CMMI Maturity Level 5 organization and now we are preparing for our re-appraisal.
We have Process Performance Models (PPMs) with different X- prameters and good R^2, R (adjusted) & P(value).
We perform simulations to calculate the probability of achieving our organizational goal and the determination that the probability % is good enough to achieve the goal.
Now we are in our process of implementing the PPM. My question is: Shall we use the PPM to estimate the X- parameters in my projetct? Or what should I do with this model after that ?
Please advise.
I hate to say this, and I could be wrong, but reading your question it sounds like you are asking what do I need in order to be Maturity Level 5 (ML 5)? Is this equation sufficient? And by asking what do I do with the PPM, I may be misunderstanding you, but if you were really at ML 5 you wouldn’t be asking this question. I get the impression from your question that your organization doesn’t know why it is using a specific technique for the PPMs.
The best solution to your question is to ask your High Maturity Lead Appraiser for help and guidance as he or she should have enough understanding and knowledge of your organization to provide the answer.
But once again, the nature of your question gives me the uneasy feeling that your organization may not even be Maturity Level 4.
Showing posts with label Maturity Level 4. Show all posts
Showing posts with label Maturity Level 4. Show all posts
Friday, October 16, 2009
Thursday, August 7, 2008
SEI Published Appraisal Results
I have a question related to the published data in SEI web site: http://www.sei.cmu.edu/appraisal-program/profile/pdf/CMMI/2008MarCMMI.pdf Process Maturity Profile by All Reporting Organizations (Page 5):
- 1.5% or the reporting organizations are (Initial - Maturity Level 1) rating. How is a Maturity Level 1 rating achieved?
- Also, 8% of the reporting organizations indicate that a Maturity Level is Not Given. What does ‘Not Given’ mean…? Level 0 ?
In my understanding, Maturity Level is related to the Staged representation and can have
rating from ML 2 - 5.
It is great to see and hear that people are actually looking at this information and asking questions about how to interpret the data. You are on your way to understanding Measurement and Analysis!
To answer your first question, how is Maturity Level 1 provided? Obviously, an organization does not conduct a SCAMPI A appraisal to confirm that they are Maturity Level 1. So what happens in this case is the scope of the SCAMPI A appraisal is Maturity Level 2, 3, 4, or 5. But what happens is during the appraisal a serious goal impacting weakness in a Maturity Level 2 Process Area is found by the appraisal team. By the rules of the SCAMPI method then the resulting Maturity Level is 1. Since the SCAMPI A results must be submitted to the SEI, a rating of Maturity Level 1 appears. It doesn’t happen that often because most organizations take the appropriate steps to be prepared to achieve their target Maturity Level. That is why 1.5% of the reported results are for Maturity Level 1.
The Not Given category means that the organization did not report its resulting Maturity Level rating. I would hazard a guess that it probably means that they had successfully achieved Maturity Level 1. There is no Maturity Level 0, despite what many chaotic organizations say they are when first encountering the CMMI.
Tuesday, June 3, 2008
ML 2/ML 3 Measurement Objectives
For a Maturity Level 3 organization , is it acceptable if the organization sets its process performance objectives qualitatively? For example reduce testing cycle time , improve productivity, etc. and in OPF SG1, one of sub-practices states that process performance objectives may be expressed either quantitatively or qualitatively. Also would you please explain this clarification linking to ML2- MA - SP 1.1 - Establish measurement objective?
These are good questions, but the best way to receive a decent understanding of the concepts it to attend the SEI’s Introduction to the CMMI class. Intro to CMMI course description Brief answers, such as mine in this blog, will probably only raise more questions that would be better addressed in a classroom setting.
- Only for High Maturity organizations (ML 4 and 5) is there an expectation for quantitatively setting process performance objectives. It is acceptable at ML 3 for qualitative objectives. But to fully understand this distinction you really require a good discussion on the expectations for each Maturity Level, which you would receive in the Intro to CMMI class.
- A measurement objective is different from a process performance objective. The measurement objectives are the purposes for which measurement and analysis is performed and also specify what kinds of actions may be taken as a result of data analyses. In order to determine the measurement objectives, you first have to describe the information needs. An information need is an insight necessary to manage objectives, goals, issues, risks, and problems. The measurement objective is derived from the information need and it is a statement about what should be measured in order to satisfy the information need. For example, the project manager or other decision maker concerned with allocating budget and associated resources to a task may believe that productivity is related to the type of task being performed. Increasing productivity is then the measurement objective that addresses the defined information need. Determining productivity then requires that entities such as the product and the process be measured. There are many ways that productivity can be computed, but the measurement objective is unaffected by the different methods.
To fully understand these concepts you should take a class on Measurement and Analysis or Practical Software Measurement. Trying to explain these concepts in a paragraph or two does not do the subject justice.
Thursday, May 22, 2008
Selection of Processes\Subprocesses
Kindly give your comments on the following queries :
1.Say, in OPP if an organization has selected some process/subprocess (SP 1.1) for performance analysis. A critical criterion for selectionof process or subprocess is its historical stability. To ensure thisdoes the organization needs to use statistical techniques right fromthe beginning of the data collection for that process/subprocess?
2.In QPM, whether the projects have to select the subprocess fromprocess/subprocess identified in OPP or need to select based on their project specific objectives?
Let us first consider the OPP SP 1.1 question. How is it possible to know that a process, or sub-process for that matter, is stable without having already performed some sort of statistical analysis on the historical data? What I think the actual question you may be asking below is at what point does it make sense to begin using statistical techniques. Obviously, OPP SP 1.1 is where you want to be when you reach Maturity Level 4. However, it does take some time and thought before arriving here. So, as an organization begins its ML 4 journey implementing OPP SP 1.1, it may NOT have enough historical data to select the processes or sub-processes. Therefore, the organization must spend some time collecting and analyzing the data before it is smart enough to know if it has a stable process or sub-process or one that can be stabilized. As the organization's processes become more and more stable, the application of statistical techniques may prove insightful. The stabilization of process execution, as reflected in the resulting process data, provides the opportunity to apply more sophisticated analytical techniques, including statistical methods. So it is not necessary to "use statistical techniques right from the beginning of the data collection;" rather statistical techniques can be applied once the process is consistently executed as reflected by the resulting data stability. Therefore, the organization has to devote the effort to data analysis to determine if OPP SP 1.1 can be implemented.
QPM works in conjunction with OPP. The project’s quality and process performance objectives are derived from the organization’s quality and process performance objectives. And the processes and sub-processes being quantitatively and statistically managed by the project are selected from those specified in OPP. If not, what would be the value of OPP SP 1.1? OPP sets up the infrastructure to allow the projects to perform QPM. However, that being said, a project may find that it has unique characteristics or customer objectives that warrant the statistical management of one or more subprocesses for which no process performance baseline has yet been established. In such a case, the project would select that subprocess for statistical management in QPM SG2, establish spec limits for the expected process performance, and use that as its foundation for quantitative management. Once sufficient process data have been accumulated by the project, the actual Upper Control Limit (UCL) and Lower Control Limit (LCL) can be established and used (and process stability and process capability can be verified or denied). Note that this information should be fed back to OPP for potential use on future projects.
1.Say, in OPP if an organization has selected some process/subprocess (SP 1.1) for performance analysis. A critical criterion for selectionof process or subprocess is its historical stability. To ensure thisdoes the organization needs to use statistical techniques right fromthe beginning of the data collection for that process/subprocess?
2.In QPM, whether the projects have to select the subprocess fromprocess/subprocess identified in OPP or need to select based on their project specific objectives?
Let us first consider the OPP SP 1.1 question. How is it possible to know that a process, or sub-process for that matter, is stable without having already performed some sort of statistical analysis on the historical data? What I think the actual question you may be asking below is at what point does it make sense to begin using statistical techniques. Obviously, OPP SP 1.1 is where you want to be when you reach Maturity Level 4. However, it does take some time and thought before arriving here. So, as an organization begins its ML 4 journey implementing OPP SP 1.1, it may NOT have enough historical data to select the processes or sub-processes. Therefore, the organization must spend some time collecting and analyzing the data before it is smart enough to know if it has a stable process or sub-process or one that can be stabilized. As the organization's processes become more and more stable, the application of statistical techniques may prove insightful. The stabilization of process execution, as reflected in the resulting process data, provides the opportunity to apply more sophisticated analytical techniques, including statistical methods. So it is not necessary to "use statistical techniques right from the beginning of the data collection;" rather statistical techniques can be applied once the process is consistently executed as reflected by the resulting data stability. Therefore, the organization has to devote the effort to data analysis to determine if OPP SP 1.1 can be implemented.
QPM works in conjunction with OPP. The project’s quality and process performance objectives are derived from the organization’s quality and process performance objectives. And the processes and sub-processes being quantitatively and statistically managed by the project are selected from those specified in OPP. If not, what would be the value of OPP SP 1.1? OPP sets up the infrastructure to allow the projects to perform QPM. However, that being said, a project may find that it has unique characteristics or customer objectives that warrant the statistical management of one or more subprocesses for which no process performance baseline has yet been established. In such a case, the project would select that subprocess for statistical management in QPM SG2, establish spec limits for the expected process performance, and use that as its foundation for quantitative management. Once sufficient process data have been accumulated by the project, the actual Upper Control Limit (UCL) and Lower Control Limit (LCL) can be established and used (and process stability and process capability can be verified or denied). Note that this information should be fed back to OPP for potential use on future projects.
Friday, May 2, 2008
Query on ML 3 and ML 4
What is the significance of Maturity Level 3 and Maturity Level 4? And can you explain to me what is Integrated Project Management?
What broad questions! These questions really need a long in depth answer and are addressed very well in the Introduction to CMMI class. So first off I would suggest that you find an opportunity to take this class. Please visit http://www.ppqc.net/training/training.htm for more information about the class.
To briefly answer these two questions, the answer needs to address ML 2 as well. So I will start with some definitions from the CMMI book.
Process Area (PA) – a cluster of related practices in an area that, when implemented collectively, satisfy a set of goals considered important for making improvement in that area.
Maturity Level (ML) – degree of process improvement across a predefined set of process areas in which all goals in the set are attained. An ML is a defined evolutionary plateau for organization process improvement. Each ML matures an important subset of the organization’s processes, preparing it to move to the next ML.
Maturity Level 1: Initial – processes are usually ad hoc and chaotic. The organization usually does not provide a stable environment to support the process. Success in these organizations depends on the competence and heroics of the people in the organization and not on the use of proven processes.
Maturity Level 2: Managed – projects of the organization have ensured that processes are planned and executed in accordance with policy; the projects employ skilled people who have adequate resources to produce controlled outputs; involve relevant stakeholders; are monitored, controlled, and reviewed; and are evaluated for adherence to their process descriptions, The process discipline reflected by ML 2 helps to ensure that existing practices are retained during times of stress. When these practices are in place, projects are performed and managed according to their documented plans.
Maturity Level 3: Defined – processes are well characterized and understood, and are described in standards, procedures, tools, and methods. The organization’s set of standard processes, which is the basis for ML 3, is established and improved over time. These standard processes are used to establish consistency across the organization. Projects establish their defined process by tailoring the organization’s set of standard processes according to tailoring guidelines.
Maturity Level 4: Quantitatively Managed – the organization and projects establish quantitative objectives for quality and process performance and use them as criteria in managing processes. Quantitative objectives are based on the needs of the customer, end users, organization, and process implementers. Quality and process performance is understood in statistical terms and is managed throughout the life of the processes.
Maturity Level 5: Optimizing – an organization continually improves its processes based on a quantitative understanding of the common causes of variation inherent in processes.
Given these definitions and explanations, one of the fundamental differences between ML 3 and ML 4 is that at ML 3 the organization is learning how to use a standard set of processes, tailoring them to the individual project needs, and collecting enough process data such that Process Performance Baselines and Process Performance Models can be built and used at ML 4 to quantitatively manage projects and statistically manage sub-processes to achieve the organization’s quality and process performance objectives.
To answer the second question, you first need to understand the Project Planning (PP), Project Monitoring and Control (PMC), and Integrated Project Management (IPM) PAs. PP and PMC are ML 2 PAs that address the basic project management practices of planning a project, creating a project plan, and using that project plan to track and monitor the project. At ML 2, the organization typically is learning how to create accurate and realistic estimates by building estimation models. It takes time to refine these estimation models, so an ML 2 organization is expected to frequently revise and re-baseline the project plan as the projects get smarter about estimation. At ML 3, one of the project management expectations is that the project estimates are now accurate and realistic. So, rather than constantly update the estimates to match the actuals as done at ML 2, the Project Manager now manages the project to the estimates, meaning that the PM can now fairly accurately predict early on in the lifecycle whether or not the project will hit its downstream targets and take appropriate corrective action to mitigate these risks. The other differences between IPM and PP/PMC include establishing the project’s defined process by applying appropriate tailoring criteria to the organization’s standard processes, establishing the project’s work environment, integrating the various plans that comprise the project plan, managing the project using the integrated plans, and managing the project’s relevant stakeholders. In other words, IPM builds on the project management foundation established by PP and PMC.
This a lengthy explanation but only a surface treatment on these subjects. Again I strongly recommend to anyone interested in this topic that you attend an offering of the Introduction to CMMI v1.2 class. You will go into these concepts in much greater detail and you will come out with a much better understanding of the model, PAs, and MLs than I can convey in this blog.
What broad questions! These questions really need a long in depth answer and are addressed very well in the Introduction to CMMI class. So first off I would suggest that you find an opportunity to take this class. Please visit http://www.ppqc.net/training/training.htm for more information about the class.
To briefly answer these two questions, the answer needs to address ML 2 as well. So I will start with some definitions from the CMMI book.
Process Area (PA) – a cluster of related practices in an area that, when implemented collectively, satisfy a set of goals considered important for making improvement in that area.
Maturity Level (ML) – degree of process improvement across a predefined set of process areas in which all goals in the set are attained. An ML is a defined evolutionary plateau for organization process improvement. Each ML matures an important subset of the organization’s processes, preparing it to move to the next ML.
Maturity Level 1: Initial – processes are usually ad hoc and chaotic. The organization usually does not provide a stable environment to support the process. Success in these organizations depends on the competence and heroics of the people in the organization and not on the use of proven processes.
Maturity Level 2: Managed – projects of the organization have ensured that processes are planned and executed in accordance with policy; the projects employ skilled people who have adequate resources to produce controlled outputs; involve relevant stakeholders; are monitored, controlled, and reviewed; and are evaluated for adherence to their process descriptions, The process discipline reflected by ML 2 helps to ensure that existing practices are retained during times of stress. When these practices are in place, projects are performed and managed according to their documented plans.
Maturity Level 3: Defined – processes are well characterized and understood, and are described in standards, procedures, tools, and methods. The organization’s set of standard processes, which is the basis for ML 3, is established and improved over time. These standard processes are used to establish consistency across the organization. Projects establish their defined process by tailoring the organization’s set of standard processes according to tailoring guidelines.
Maturity Level 4: Quantitatively Managed – the organization and projects establish quantitative objectives for quality and process performance and use them as criteria in managing processes. Quantitative objectives are based on the needs of the customer, end users, organization, and process implementers. Quality and process performance is understood in statistical terms and is managed throughout the life of the processes.
Maturity Level 5: Optimizing – an organization continually improves its processes based on a quantitative understanding of the common causes of variation inherent in processes.
Given these definitions and explanations, one of the fundamental differences between ML 3 and ML 4 is that at ML 3 the organization is learning how to use a standard set of processes, tailoring them to the individual project needs, and collecting enough process data such that Process Performance Baselines and Process Performance Models can be built and used at ML 4 to quantitatively manage projects and statistically manage sub-processes to achieve the organization’s quality and process performance objectives.
To answer the second question, you first need to understand the Project Planning (PP), Project Monitoring and Control (PMC), and Integrated Project Management (IPM) PAs. PP and PMC are ML 2 PAs that address the basic project management practices of planning a project, creating a project plan, and using that project plan to track and monitor the project. At ML 2, the organization typically is learning how to create accurate and realistic estimates by building estimation models. It takes time to refine these estimation models, so an ML 2 organization is expected to frequently revise and re-baseline the project plan as the projects get smarter about estimation. At ML 3, one of the project management expectations is that the project estimates are now accurate and realistic. So, rather than constantly update the estimates to match the actuals as done at ML 2, the Project Manager now manages the project to the estimates, meaning that the PM can now fairly accurately predict early on in the lifecycle whether or not the project will hit its downstream targets and take appropriate corrective action to mitigate these risks. The other differences between IPM and PP/PMC include establishing the project’s defined process by applying appropriate tailoring criteria to the organization’s standard processes, establishing the project’s work environment, integrating the various plans that comprise the project plan, managing the project using the integrated plans, and managing the project’s relevant stakeholders. In other words, IPM builds on the project management foundation established by PP and PMC.
This a lengthy explanation but only a surface treatment on these subjects. Again I strongly recommend to anyone interested in this topic that you attend an offering of the Introduction to CMMI v1.2 class. You will go into these concepts in much greater detail and you will come out with a much better understanding of the model, PAs, and MLs than I can convey in this blog.
Thursday, April 10, 2008
Help! I am Totally Lost When Interpreting the QPM Specific Practices
QPM SP 1.1 states “Establish and maintain the project’s quality and process-performance objectives.” When you are starting to implement the Maturity Level 4 PAs you won’t have a Process Capability Baseline, that is ultimately the goal of being at ML 4 so the organization can then move to ML 5. One of the main thrusts of ML 4 is to analyze the process data looking for Special Causes of Variation. Once those have been analyzed, then it is possible to determine the process capability. For SP 1.1 the project’s quality and process-performance objectives (QPPOs) are set by management and are based, in part, on the organization’s objectives (OPP SP 1.3). The Process Performance Models (PPMs) are then used to determine if the QPPOs can be met. If not, the QPPOs should be appropriately adjusted.
QPM SP 1.2 states "Select the sub-processes that compose the project's defined process based on historical stability and capability datat." One of the key words in this practice statement is "historical". Sources of historical stability and capability data include the organization’s process performance baselines (PPBs) and PPMs (OPP SP 1.4 and SP 1.5). And the intent of this practice is to tailor the organization’s standard processes (OSSP) so the project’s processes will support the project’s QPPOs defined in SP 1.1.
QPM SP 1.3 states “Select the sub-processes of the project’s defined process that will be statistically managed.” The model does not say that these sub-processes MUST be statistically managed, but these WILL be statistically managed. And this practice focuses more on than just selecting sub-processes. It also focuses on identifying the attributes of each sub-process that will be used to statistically manage the sub-process.
People appear to get confused with Maturity Level 4 (ML 4) sounds when trying to understand QPM independently from the rest of the model. You cannot do that. You have to consider OPP and QPM together when looking at ML 4. OPP provides the analysis of the historical data to build the PPBs and PPMs which are then used by the projects to help them appropriately tailor the OSSP to what will meet the project’s QPPOs. QPM SP 1.2 uses the word "compose", which may contribute to some of the confusion. Since compose is not in the CMMI Glossary, then the dictionary definition is applicable. The Webster definition of compose is “To form by putting together two or more things or parts; to put together; to make up; to fashion.” So for this practice, compose means going to the OSSP and selecting the processes and sub-processes that will meet the QPPOs and then applying the necessary tailoring criteria. What this practice implies is that the OSSP may have several different processes for each Process Area (PA) so the project manager can choose the most appropriate one when composing the project's defined process.
Another ML 4 concept that may be the cause of confusion is the notion of Quantitative Management vs. Statistical Management. QPM SG 1 is all about quantitatively managing the project, which means the Project Manager must be periodically reviewing progress, performance, and risks using the PPMs to determine/predict if the project will meet its QPPOs. If not, then appropriate correctives actions must be taken to address the deficiencies in achieving the project’s QPPOs (QPM SP 1.4) Statistical Management is covered by QPM SG 2. The intent is for the project to statistically manage those sub-processes that are critical to achieving the project’s QPPOs. There are only a small set of sub-processes that are critical to achieving the project’s QPPOs. If the organization were to statistically manage all processes, that would be insane. This approach would mean that the organization would need PPBs and PPMs for EVERY process, regardless of their importance to the QPPOs. And then the shear overhead of collecting, analyzing, and reporting data on every process would most likely bring the organization to its knees. Work would come to a standstill because it was taking far too much time to statistically manage each process and taking corrective actions that may not be necessary. Unless you have an infinite budget and dedicated staff to perform these analyses, that is why the model states to statistically manage SELECTED sub-processes.
QPM SP 1.2 states "Select the sub-processes that compose the project's defined process based on historical stability and capability datat." One of the key words in this practice statement is "historical". Sources of historical stability and capability data include the organization’s process performance baselines (PPBs) and PPMs (OPP SP 1.4 and SP 1.5). And the intent of this practice is to tailor the organization’s standard processes (OSSP) so the project’s processes will support the project’s QPPOs defined in SP 1.1.
QPM SP 1.3 states “Select the sub-processes of the project’s defined process that will be statistically managed.” The model does not say that these sub-processes MUST be statistically managed, but these WILL be statistically managed. And this practice focuses more on than just selecting sub-processes. It also focuses on identifying the attributes of each sub-process that will be used to statistically manage the sub-process.
People appear to get confused with Maturity Level 4 (ML 4) sounds when trying to understand QPM independently from the rest of the model. You cannot do that. You have to consider OPP and QPM together when looking at ML 4. OPP provides the analysis of the historical data to build the PPBs and PPMs which are then used by the projects to help them appropriately tailor the OSSP to what will meet the project’s QPPOs. QPM SP 1.2 uses the word "compose", which may contribute to some of the confusion. Since compose is not in the CMMI Glossary, then the dictionary definition is applicable. The Webster definition of compose is “To form by putting together two or more things or parts; to put together; to make up; to fashion.” So for this practice, compose means going to the OSSP and selecting the processes and sub-processes that will meet the QPPOs and then applying the necessary tailoring criteria. What this practice implies is that the OSSP may have several different processes for each Process Area (PA) so the project manager can choose the most appropriate one when composing the project's defined process.
Another ML 4 concept that may be the cause of confusion is the notion of Quantitative Management vs. Statistical Management. QPM SG 1 is all about quantitatively managing the project, which means the Project Manager must be periodically reviewing progress, performance, and risks using the PPMs to determine/predict if the project will meet its QPPOs. If not, then appropriate correctives actions must be taken to address the deficiencies in achieving the project’s QPPOs (QPM SP 1.4) Statistical Management is covered by QPM SG 2. The intent is for the project to statistically manage those sub-processes that are critical to achieving the project’s QPPOs. There are only a small set of sub-processes that are critical to achieving the project’s QPPOs. If the organization were to statistically manage all processes, that would be insane. This approach would mean that the organization would need PPBs and PPMs for EVERY process, regardless of their importance to the QPPOs. And then the shear overhead of collecting, analyzing, and reporting data on every process would most likely bring the organization to its knees. Work would come to a standstill because it was taking far too much time to statistically manage each process and taking corrective actions that may not be necessary. Unless you have an infinite budget and dedicated staff to perform these analyses, that is why the model states to statistically manage SELECTED sub-processes.
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