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.

Transforming Individuals Control Chart Data and Process Capability Reporting in One Chart

Transforming individuals control chart data is an important consideration to avoid common cause variability appearing as special cause events.  The transformation of data (for situations that make physical sense) is easily accomplished in 30,000-foot-level tracking metric report-outs, which also can provide a predictive process capability statement — in one chart.

Process Capability Problems and Solutions: Resolving Process Capability Index Issues for Cp, Cpk, Pp, Ppk

Process capability problems and solutions to those issues is very important for an organization. Another way to state this need is resolving the process capability index issues of Cp, Cpk, Pp, and Ppk is essential so that organizations will take appropriate actions from their process capability reporting.   The solution to this problem is easily …

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Quantifying Process Improvement

Quantifying process improvement impact using a 30,000-foot-level chart is very beneficial for a Lean Six Sigma project or Kaizen event deployments.     Quantifying Process Improvement and 30,000-foot-level Predictability Statements   Note: Content of this webpage is from Chapters 12 and 13 of Integrated Enterprise Excellence Volume III – Improvement Project Execution: A Management and …

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Enhanced Control Chart that Includes Process Capability in One Chart

A enhanced control chart that includes a process capability statement (that is easy to understand) is provided in a 30,000-foot-level report-out.  Organizational 30,000-foot-level metrics can be integrated with their processes via a value chain in the Integrated Enterprise Excellence (IEE) Business Management System.

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.