A Business Metrics Dashboard that Resolves Commonplace Metric Reporting Problems

A PDF article describes commonplace organizational metric reporting problems and an alternative business metrics dashboard format that resolves these issues.

In the dynamic landscape of modern business, the intent of Key Performance Indicators (KPIs) and other dashboard reporting formats is to serve as compass points, guiding organizations toward their strategic objectives. However, like any journey, the path to success has its challenges. Amidst data collection, analysis, and interpretation complexities, businesses often grapple with KPI and metric reporting problems that lead to wasteful firefighting and hinder their ability to gain meaningful insights, make informed decisions, and make significant process improvements.

This article provides a system for addressing these challenges. This article offers a better approach to metric tracking, goal setting, and process improvement.

Organizations need to address the elephant in the room with commonplace metric reporting.

Metric Reporting Problems

This article uses red-yellow-green reporting to illustrate commonplace metric reporting problems. With a red-yellow-green reporting format, if an individual metric response value color is:

• Green, the metric response, performs well relative to its goal or specification.
• Yellow, the metric response, performs close to its goal or specification.
• Red, the metric response, is not performing consistently with its goal or specification, and action is needed to resolve the issue.

Let's study an organization's red-yellow-green scorecard reported in a leadership meeting:

For Finance Metric B, like many other metrics in this report, the metric's color changes, sometimes frequently. With this form of reporting, one typically presumes that a color change from green to red indicates an undesirable problem that needs resolution; however, a metric color can often change back to green from red when there was no previous corrective action.

One does not expect a process measurement output response to be the same value for each reporting period. There will be process-output variation noise for most measurement responses. Red-yellow-green scorecards and other commonplace dashboards do not structurally include this typical process variation in their reporting.

For Finance metric B, we observe that red occurred 38 percent of the time and green occurred 46 percent of the time. When examining an individual red-colored measurement to determine whether the organization should undertake an immediate causal problem investigation (or not), one should consider whether this metric variation is from a typical metric-response variation or an unusual event.

Suppose there is a red-colored metric response, and the response is from a typical process-output variation. In that case, one should not react to this undesirable individual point as an unusual event. If, instead of not reacting, there is a causal investigation for this situation, much wasteful firefighting can occur to determine why a particular value is unsatisfactory when the response value is only a typical variation from the process output's responses.

A process's output is Y, a function of its inputs, Xs, i.e., Y=F(X).

Commonplace organizational metric dashboards (including red-yellow-green scorecards) do not encourage improving the Xs of a process to enhance a future process output response. Commonplace metric dashboards attempt to manage the Ys of organizational processes. This Y-management approach can lead to unhealthy, if not destructive, behaviors, e.g., a major bank's bogus accounts scandal when employees created fake accounts attempting to meet a leadership metric goal (i.e., Y response) .

A 30,000-foot-level Reporting Format Resolution to Commonplace Scorecard Reporting Problems

Organizations gain much when they incorporate metric reports that:

• View the enterprise as a system of processes
• Acknowledge the effect of variability
• Support long-lasting systematic process improvement

The Integrated Enterprise Excellence (IEE) business management system provides the vehicle to achieve these objectives with its 30,000-foot-level format for metric reporting. This article will next describe 30,000-foot-level reporting and how to create a 30,000-foot-level chart for your dataset.

An individuals chart plot of the red-yellow-green scorecard Finance Metric B data indicates no statistical change in the magnitude of the metric response over time, i.e., the process response is stable.

Note: Mathematically, this individuals chart's creation is the same as a Statistical Process Control (SPC) individuals control chart creation; however, the frequency of data reporting with a 30,000-foot-level report is less frequent (monthly in this case) than a traditional control chart (which can be many measurements in one day), and the chart's purpose is not to control a process. The purpose of a 30,000-foot-level ?individuals chart is to provide a high-level, time-series perspective of a process's output for assessing its stability, i.e., not unlike looking at the terrain below from the window of an airplane in flight at 30,000 feet.

With 30,000-foot-level reporting, a prediction statement can be made for stable processes. If a process output response is predictable, one can consider that data from the recent stability region are a random future sample. One can display this future sample projection as a histogram.

A display of this histogram's individuals chart data in a normal probability plot format provides a better view of how the process performs relative to a goal, where the y-axis of the probability plot is "percent less than" and the x-axis is the response magnitude. This probability plot provides the expectation that approximately 32.6% of the months will be below a 2.2 criterion.

With 30,000-foot-level reporting, there are two steps for creating the report.

• Step 1 determines whether the process response is stable, i.e., no unusual events beyond its typical process-response noise.
• Step 2 presents data for creating a futuristic statement if the process response is stable.

IEE reporting assesses predictability and provides a prediction statement (at the bottom of the report) for predictable response processes from the probability plot

A free 30,000-foot-level reporting app created the following report-out for this red-yellow-green scorecard Finance Metric B dataset. This app can create a 30,000-foot-level chart for continuous (subgrouped or non-subgrouped) and attribute data for your Excel spreadsheet datasets . This link also provides video instructions on how to use this app.

Unlike the red-yellow-green scorecard, this report-out indicates that Finance Metric B had no improvements during the reported period. To improve the Finance Metric B response so that its non-conformance rate "below 2.2" decreases from a 32.6% future expectation, one needs to enhance the process (Xs) that impacts the Finance Metric B (Y).

To improve this Finance B metric, one can follow a Lean Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) process , a Lean Kaizen event, or another improvement methodology. The approach to make process improvements (Xs) to a 30,000-foot-level metric's response (Y) should depend upon the situation. A critical item when considering improving a metric's response is not the approach to improve the metric's processes.

Another Example of 30,000-foot-level Reporting and Its Benefits

"KPI Management: KPI Metric Reports that Lead to the Best Behaviors" uses a commute time from home to work dataset to illustrate smart goal setting, metric tracking, process improvement, and quantifying process-improvement work benefits.

Enterprise Implementation of 30,000-foot-level reporting

Organizations benefit when they have 30,000-foot-level reporting throughout their organization. This 30,000-foot-level reporting objective (and more) is available via IEE Enterprise Performance Reporting System (EPRS) software, which offers automated updates of 30,000-foot-level reports, e.g., daily.

The article “A Business Process Management (BPM) Model That Would Resolve Boeing’s Quality Problems ” summarizes the benefits of the IEE methodology with its EPRS software and how to implement it.

Next Step

To discuss and see the application and benefits of 30,000-foot-level reporting to your data, contact Forrest Breyfogle [email protected] . You can schedule a video meeting session with Forrest through the link https://smartersolutions.com/schedule-zoom-session/ if you want to discuss the described methodology application or have any questions.