Process Metrics

Process metrics need to lead to the most appropriate behaviors. Processes have variability and may or may not have specifications.

Performance measurements for processes need to provide direction to the most appropriate behaviors considering both process variability and any specification that may exist. The output of processes can have both common-cause variability and special-cause variability.

In process metric reporting, typical process variability is separated from unusual events or trends. Traditionally this separation is make using statistical process control (SPC) charts such as x-bar and R charts and p-charts. How a process is performing for an in-control process relative to specifications traditionally involves techniques such as process capability indices.

However, traditional control charting and process capability reporting have mathematical issues. An Integrated Enterprise Excellence (IEE) 30,000-foot-level reporting format addresses these issues. IEE 30,000-foot-level reporting provides both a process stability assessment and predictive statement for stable processes in one chart.

How to Report Performance Measures with Analyses, a Diabetes Illustration

ASQ Quality Progress January 2017 published article titled “Monitor and Manage: Diabetes measurement tracking at the 30,000-foot-level.” Described is an Integrated Enterprise Excellence (IEE) approach for diabetes measurement tracking and understanding improvement opportunities. Techniques apply to business key performance indicators (KPIs) as well; e.g., in an operational excellence business management system.

Enhanced Process Capability Reporting: Description and Webinar

For a given process, do you think everyone would create a similar looking control chart and make a comparable statement relative to its control and capability? Not necessarily. Process statements are not only a function of procedural characteristics and sampling chance differences but can also be very dependent upon sampling approach. The implication of this is that one person could describe a process as being out of control, which would lead to activities that immediately address process perturbations as abnormalities, while another person could describe the process as being in control. For this second interpretation, the perturbations are perceived as fluctuations typically expected within the process, where any long-lasting improvement effort involves looking at the whole process. During this session, issues with traditional control charting techniques (e.g., x-bar and R charts) and process capability indices statements (e.g., Cp, Cpk, Pp, and Ppk) will be discussed. An enhanced alternative predictive performance measurement system will then be described that not only provides resolution to these issues but can also provide a predictive statement, which everyone can understand.

Enhanced Approach for How to Show Process Improvement

With a high-level process-output tracking at the 30,000-foot-level, there will be an infrequent subgrouping/sampling plan such that the typical variability from input variables that could affect the response will occur between these subgroupings. An infrequent subgrouping/sampling interval could be day, week, or month, where responses from differing people, departments, machines, and so forth would be captured within each subgroup. 30,000-foot-level charting does not offer timely identification of process changes but instead provides a high-level view of how the process is performing from a customer-of-the-process point of view.

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