Performance Management System Metrics Examples

The initial performance management system metrics examples that will be shown will reference the application of a dashboard reporting methodology that transitions the following historic management reports to predictive performance reporting; i.e., numbers in a table, stoplight scorecards, and time-series plots. Next will be describe is a situation where a table of numbers for process yield reporting was converted to a predictive performance dashboard.

The described concepts in these examples can be applied to other process outputs such as the execution duration for a transaction and defective rates.

Predictive Performance Management System Metrics Examples

Previous blogs provided predictive performance management system metrics examples for:

These performance management system metrics examples showed how to reduce firefighting and provide a system where metric improvement needs ″pull″ for the creation of projects that benefited the enterprise as a whole.

Process Yield versus Process Wastage

The situation that will be described in this blog is the reporting of production yield. In this addition to the other previously described performance management system metrics examples case studies that were used with permission, a table of numbers reporting wastage is transitioned to predictive performance metric reporting.

When reporting yield, typically there will be values approaching 100%. This can present technical problems since with the predictive performance reporting of at the 30,000-foot-level there can be a need for making a data transformation because of lack of data normality. Such a transformation can easily be done when the boundary condition is zero but cannot be easily addressed with a boundary condition of 100%. Because of this, the more desirable response and the one that will be addressed in this article, is wastage percent; i.e., 100 – yield percent.

Monthly Executive Wastage Percent Report-out

Every month executives have been receiving a spreadsheet that contains the current status of their metrics. One of the reported measurements is wastage, where lower numbers are better. An example performance management system executive report for this metric is:

 

Executive report of wastage using a traditional performance management system

Executive report of wastage using a traditional performance management system

 

When one examines this performance management system report-out, the following questions could be asked:

  • Why only show results in a monthly fashion and include a year to date value? Wastage doesn’t magical change after the first day of the year. Also, if something changed between weeks two and three of a month, the impact of this change would be present in the results from two months. This can lead to deception and/or confusion. This form of tabular monthly reporting discourages the thought process that the output of the process is the result of its inputs and processes. Where, if the common-cause output response of a process is undesirable, then something needs to be done to enhance the process.
  • Can one determine if anything changed over time from this table? This is difficult to determine within this type of performance management system metrics examples reporting.
  • Why do executives need to wait until the end of the month to see how their metrics are performing? A more frequently updated reporting would have its benefits where executives and others could access up-to-date information at any time that they desire. This would also save labor in the creation of these charts.
  • Does this form of metric reporting lead to the most appropriate actionable or non-actionable activities? Typically the answer is no. Often only ″stories″ are provided describing typical up and down variability occurrences in the process. In addition, this form of reporting could lead to firefighting where one is to take action trying to answer the question why a performance number is worse this month than last. These types of activities are not linked to process thinking and may not lead to the most appropriate actionable or non-actionable activities.

Predictive Performance Management System Report Out of Wastage

Yield and wastage data are attribute responses; hence, we should not attempt to quantify the amount of variability in this response over time in the selected time-series reporting frequency. Examining an attribute response as a continuous response can lead to confusion. For example, a decrease in reporting frequency from monthly to quarterly will have a reduction in between-reporting-period process variation. The reason for this is that the variability difference indication is really affected by the quarterly sample size being larger than a weekly reporting sample.

Wastage Percentage ″Predictive Performance″ Reporting Illustration from our Set of Performance Management System Metrics Examples

A 30,000-foot-level predictive performance report-out for overall wastage for this process is

 

30,000-foot-level predictive performance reporting for attribute data from a set of performance management system metrics examples

30,000-foot-level predictive performance reporting for attribute data from a set of performance management system metrics examples

 

From this set of our performance management system metrics examples, we note the following, which was not prevalent from the initial annual table summary presented:

  • A special cause condition occurred, which was highlighted as a red dot with the number 1. This point should be addressed relative to determining a causal condition.
  • Individual points within the upper control limit (UCL) and lower control limit (LCL) should not be examined individually for causes. However, data in this region could be examined collectively relative to testing hypotheses for improvement opportunities; e.g., differences between days of the week, departments, and machines.
  • An improvement was demonstrated from the new method as a stage. Currently the last three weeks are performing at this enhanced level of performance.
  • Since the current new process is determined stable using a 30,000-foot-level reporting methodology, the three recent points are used to provide an estimate of the future, which is reported automatically at the bottom of the plot; i.e., 4.3 percent wastage.

A predictive measurement is reported, with the understanding that if the prediction is not desirable then something needs to be done to enhance the process. Gartner points out the importance of having predictive measurements in organizations in their article ″Gartner Says Organizations Using Predictive Business Performance Metrics Will Increase Their Profitability 20 Percent by 2017

Executive Management Predictive Performance Management System Metrics Examples Report-out

The following comments are similar to those made in the other referenced 30,000-foot-level reporting illustrations (table of numbers given continuous data, red-yellow-green stoplight reporting, and time-series chart reporting)

Additional dashboard conversions to predictive reporting illustrations are available in the article Transitioning Frequently used Dashboards to Predictive 30,000-foot-level Metric Reporting Examples.

Additional Resources on this Predictive Performance Management System Metrics

Additional information about 30,000-foot-level reporting can be found:

Illustrating the Application of Predictive 30,000-foot-level reporting in Your Organization

If one believes that 30,000-foot-level performance metric reporting could benefit an organization, they should contact me to discuss the potential application of these techniques in your work environment. One of your current report-outs could be examined and transitioned into a 30,000-foot-level report, which could be shared or discussed with others. My contact information is Forrest@SmarterSolutions.com , 512-918-0280.

Hopefully you found this blog on ″Performance Management System Metrics Examples″ to be beneficial, if you did get some benefits from this article, thank you for noting this in the Twitter, Facebook, and Linkedin social links associated with this page.

I am looking forward to seeing your thoughts about the concepts that were presented in this blog through your comments.

2 Comments

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