Performance Measurements

Organizations often use a performance metrics system that only provides point to point comparisons. For example, the currently monthly profitability of a business might be compared to last month. Any movement that is not desirable often leads to a search for what happened.

This what-happened investigation can result in the treatment of common cause variability as though it were special cause. Wasteful firefighting often is a result of traditional metric report-outs and nothing positive happens relative to making a metric improve over time.

A 30,000-foot-level predictive reporting methodology addresses this traditional metric reporting format shortcoming. With 30,000-foot-level metric reporting, a predictive statement assessment is made. If a process output performance is stable and the futuristic response is undesirable, this metric desirable shortcoming pulls for the creation of a process improvement effort that enhances the measurement’s response.

Enterprise Performance Reporting System (EPRS) software provides a means to easily create 30,000-foot-level report outs. A statistical shift in the time-series portion of a 30,000-foot-level metric is an indicator that the process output changed, either to the betterment or degradation. When this happens a new predictive process statement can then be made using this software.

Process Performance and KPI Tracking 2.0: Diabetes Measurement and Improvement Example

This process performance and KPI Tracking 2.0 example uses a colleague’s diabetes measurement data to illustrate an enhanced statistical-based process performance and Key Performance Indicator (KPI) tracking methodology that encourages and displays results from process enhancement efforts.

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KPI and Process Performance Metrics 2.0: No Specification or Goal Required

This KPI and process performance metrics example describes an enhanced measurement reporting technique that requires no goal or specification. The described method can provide more insight into what is happening in a process (and what to do differently to improve its response) than ever seen before with a traditional measurement report-out.

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