How to Report Performance Metrics of Non-conformance Rates

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How to report performance metrics of non-conformance rates so that the right behavior occurs is a crucial question addressed in this video.

This video uses an example provided in the book Management 2.0: Discovery of Integrated Enterprise Excellence to show the use of a free KPI report-out app that gets organizations out of the firefighting mode. This Integrated Enterprise Excellence (IEE) performance metric app focuses on reporting so that the right behavior occurs when tracking corporate failure rates or non-process conformance rates.

How to Report Performance Metrics of Non-conformance Rates Video

 

How to Report Performance Metrics of Non-conformance Rates and the Benefits

There is no value in a report if management and operational teams cannot transition data into the most appropriate actions or non-actions. It is essential to give care so that key performance indicators (KPIs) are wisely determined and tracked, so the most appropriate behaviors occur. Reports must be formatted so that they are easy to understand, and managers or executives know what action to take.

However, it is unfortunate that organizations do not often report KPI metrics using the best methodology.  Often organizations react to up-and-down charting variation as though these charting movements are unusual events; however, more often than not, these up and down variations are noise from the system’s response. Care needs to be given when creating and examining KPI reporting.  There is variation in most process responses; KPI reporting needs to include variation in report-outs. If the variation of a process response is not included in the reporting, the most appropriate decision often will not occur.

There is a need for organizations to have a system for predictive KPI performance reporting for achieving the most appropriate action or non-action for a given situation? Terrible behaviors can result from having KPI performance tracking against point-in-time organizational goals (e.g., next month or quarter). For example, reacting to common-cause variability as though a measured response that did not meet a target were a special-cause event and should receive special attention can result in much wasted firefighting efforts.

This video shows the application of a free metrics app that separates special-cause events from the common cause response output noise of the system. A prediction statement will be provided by the app when only common-cause variability exists.  When the prediction statement response provided by this app is undesirable (e.g., a non-conformance rate is too high), this metric enhancement needs “pulls” for the creation of process-improvement work.

There is evidence that process-improvement work was beneficial (enhancing a metric’s performance response) when the app’s KPI predictive statement transitions to an improved performance level (e.g., non-conformance rate transitions from an unacceptable to an acceptable rate).

Contact Us to set up a time for a discussion on how your organization might gain much from the concepts described in this video. 

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