KPI Report Example: Applying a Free Enhanced KPI Reporting App for Subgrouped Data

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Provided is a Key Performance Indicator KPI report example that illustrates a solution to the complaint that an organization’s current KPI table of numbers and red-yellow-green scorecard reporting is ineffective and does not lead to the best behaviors; e.g., is there a current issue that needs resolving or should a process improvement effort be undertaken.

The described approach is an enhancement to traditional Key Performance Indicator (KPI) reporting. A free illustrated software app will show the creation of a 30,000-foot-level response that results in better organizational process understanding resulting in better behaviors than traditional KPI reporting techniques provide.

The dataset used in this KPI reporting illustration is Example 12.2 from Integrated Enterprise Excellence Volume III – Improvement Project Execution: A Management and Black Belt Guide for Going Beyond Lean Six Sigma and the Balanced Scorecard.

 

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The following figure shows a screenshot of IEE Volume III, which describes potential application examples of the described KPI report example methodology.

 

KPI Report Example Applications

 

The KPI data set used in this KPI report example is:

 

KPI Report Example: Data Set

 

For this process, there is a customer requirement (specification) of 95,000 to 105,000.

 

A time series plot of the process-output response over time (Dataset Column C) is:

 

KPI Report Example: Time series analysis

 

This KPI reporting format shows much up and down variation. For this KPI reporting, what should an organization do relative to the consistent achievement of the customer product specification of 95,000 to 105,000? This KPI time-series reporting alternative provides no direction.

Upon examination of the dataset, one notes the daily collecting of five product responses for the reporting.  The traditional Statistical Process Control (SPC) charting methodology for this type of collected data suggests using an x-bar and R control chart for the data.  There would be a subgrouping of the five data points taken in each day for this Shewhart chart, SPC quality response tracking.

This type of x-bar and R KPI reporting leads to Figure 12.7 of IEE Volume III, which is:

 

 

This plot shows many responses beyond the data-calculated upper and lower control limits (UCL and LCL) signals. This report-out indicates the process is out-of-control. Traditional SPC methods state that points or trends relative to exceeding UCL and LCL limits should be addressed first as a next step.

However, as an alternative, someone could have selected only one data value for each day (e.g., Column E, “Sample 1” from the data set). SPC traditional reporting approaches suggest creating an individuals control chart for this data-response situation, which would lead to the KPI reporting format shown in Figure 12.8 of the IEE Volume III book, which is:

 

 

This individuals chart does not show any out-of-control signals, unlike an x-bar and R charting, from the output of the same process! The implication is that the process sampling methodology can impact whether a process is considered in control or not.  Why can this dependence occur when sampling from a dataset? The answer is that for an x-bar and R chart, the variability between subgroups has NO impact on the calculate SPC upper and lower control limits (UCL and LCL). With high-level control charting of a process-output response, the variability between subgroups needs to be considered as a source of common-cause (typical process-response) variability. For mathematical explanation of this truism, see Issues And Resolution To Xbar And R Chart Formula Problems.

In addition, there is no reference in these SPC charts as to how well the process is performing relative to fulfillment of a customer-needs specification.

 

KPI Report Example: A Reporting Alternative

A 30,000-foot-level KPI reporting format alternative provides resolution to all of the above-described issues.

Figure 12.9 of the IEE Volume III book shows a 30,000-foot-level report-out for this data. Included in this figure is a formal process capability statement of Cp, Cpk, Pp, and Ppk values (lower left chart):

 

 

Cp, Cpk, Pp, and Ppk process capability values are not easy to understand relative to the fulfillment of internal or external customer specifications needs and have many technical issues.  The article “Process Capability Problems And Solutions: Resolving Process Capability Index Issues For Cp, Cpk, Pp, Ppk” describes technical and other issues with this form of reporting.

A 30,000-foot-level metric reporting of an estimated non-conformance rate is much easier to understand and provides more process insight.

The following figure illustrates the result of applying a free app (that anyone can use for tracking the output of their processes) to create a 30,000-foot-level report-out, similar to Figure 12.9 in Integrated Enterprise Excellence (IEE) Volume III

 

KPI Report Example: Applying a Free Enhanced KPI Reporting App for Subgrouped Data

 

KPI Metrics Example Applications: IEE Volume II and III

 

There are descriptions of applying 30,000-foot-level process-output failure rate reporting for both Lean Six Sigma project metrics AND business KPI reporting in a 4-book IEE Series. The IEE Volume II in the set provides details for applying KPI reporting techniques at the business level. The IEE Volume III describes using the above process-output-response-metric-reporting techniques at the Lean Six Sigma improvement project execution level. A project’s metric baseline would occur in the measure phase of the Define-Measure-Analyze-Improve-Control (DMAIC) roadmap.

 

KPI Report Example: Applying a Free Enhanced KPI Reporting App for Subgrouped Books
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Over 140 Datasets and Solutions Manual

 

The  IEE Volume III Solutions Manual provides over 140 datasets. One can use the above-described app to re-create the 30,000-foot-level metric report-outs in the IEE Volume II and IEE Volume III books, i.e., as described in the above process performance indicators example.

 

 

DMAIC Tools Integration

 

In applying Lean and Six Sigma, it is vital to use the right tool at the right time. The book Lean Six Sigma Project Execution Guide: The Integrated Enterprise Excellence (IEE) Process Improvement Project Roadmap provides a Roadmap for accomplishing this essential objective.

 

 

Summary

What additional process insight could you gain from the application of the above described 30,000-foot-level reporting app?  This amount of understanding could be huge.

Contact us to schedule a free Zoom session now to see how much you and your organization could benefit from this free 30,000-foot-level reporting app.

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