There's a lot of "noise" being made about the SEI's "High Road" view on level 4 and 5, although the model itself hasn't changed much for these 4 PA's. My company, a past Level 5 achiever is ready for a CMMI ML5 renewal and there's lots of moaning and groaning and questions about this "High Road".What's really the new emphasis (or activities or requirements) that the SEI is imposing at Levels 4 and 5?
This is an AWESOME question. Thank you! There certainly has been quite a bit of conversation about this in the past two years, and while the practices have not changed all that much, the informative material has, and that material forms the basis for understanding the meaning of the practices. So, let's explore it.
The short answer is, too many organizations (along with their Lead Appraisers) were achieving ML4/5 without understanding the basic requirement to monitor and control selected sub-processes using statistical techniques, and using that as a foundation to improve the process and organizational performance. This includes the introduction of new ideas and innovations - which at ML5 should be, at least in part, based on statistical data about process performance.
Here is my "high-road" interperpation of the PAs. Keep in mind that there is a lot of detail in these and I am speaking at the 30,000 foot level.
OPP - the foundation of all HM practices is Organizational Process Performance. It is meant to establish a monitoring and prediction capability using statistical techniques. Here we select which sub-processes we want to include in our baselines, we set objectives that are within the natural process limits based on historical data ("voice of the process") and we model "what ifs" based on that voice (and other objectives). It is expected that you will use a variety of techniques (for example process performance charts, histograms, Pareto analysis, et al) to understand process performance. Just metrics isn't enough. You need to be identifying "assignable causes" or "special cause" of variation using these techniques.
Think of this as the "single-source of truth" when it comes to process performance.
QPM - Here we will task projects with using the data from OPP to set, and hopefully achieve, the objectives for the project. While OPP is focused on the meta-data (organizational), projects focus on the "micro-data," meaning what is going on at the phase or iteration level of their project. They compose their process based on the set of standard process using the baseline data from OPP to help them selected the sub-processes and set objectives for "what is possible" on their project (again "voice of the process"). They determine what THEY will statistically monitor, using similar techniques, like process performance charts to identify variation, and they monitor process performance, taking corrective action if this data appears to tell them they are not going to meet their process and quality objectives. Actual performance data is then used to update the baseline process performance data that OPP is monitoring and tracking.
Think of this as the projects benefiting from past projects (using OPP), and then passing that benefit fo future projects (QPM to OPP).
CAR - Causal Analysis and Resolution is a (mostly) project-based PA that analyzes statistical data (provided by both OPP and QPM (through OPP)) to identify defects or problems (process and product) and examines possible causes using techniques such as mind-mapping, fish-bone diagramming, and the "five-whys." Proposals for correction are made, these proposals are implemented, the "correction" is evaluated, and the data is recorded so that OPP can use it by updating their baselines with actual performance data.
Think of this as a way to know which problems you should be attacking in which sequence, and then ensuring that you actually solved it.
OID - Organizational Innovation and Deployment is an organizational level PA that is similar to OPF in some ways, in that it strives to understand process needs, meet organizational objectives, and implement action plans, but it's far more deliberate AND is based on statisticdal data. Proposals are collected, and the feasibility of those proposals is analyzed, using data and modeling provided by way of OPP and CAR. The deployment of new processes is also more cautious than OPF, in OID pilots are used, effects of the change are evaluated, and deployment is managed all within the context of meeting the objectives of the business.
Think of OID as a more cautious, deliberate, and focused way to improve the process, with a higher degree of certainty that the improvements will not just be "different" but will enable us to better achieve process and quality objectives.
You can think of High Maturity as a set of techniques to bring the "Voice of the Process" (the actual performance results, within limits, of a stable process being performed) and the "Voice of the Customer," the specification that is set as a goal for us to achieve.
Hope this helps!