Quality Metrics Reporting that Leads to the Best Behaviors

Quality metrics reporting includes reporting organizational costs, on-time delivery, non-conformance rates, lead times, cycle times, and profit.

Organizations benefit when quality metric reporting occurs at the executive, operational, and supplier levels so that the best organizational actions or non-actions happen; however, this often does not occur.

Commonplace reporting formats often provide the status of Y-responses (e.g., a table of numbers) at one point in time, where there may be comparisons to a previous time or a goal.


Quality metrics IEE needed


The forms of reporting shown in the above figure can be inconsistent and confusing in an organization. This form of quality metrics reporting can lead to Y management, resulting in unhealthy, if not destructive, behaviors.

Over the years, many reported instances where an arbitrarily set organizational measurement goal led to unethical or even illegal behaviors. Y-management form of reporting does not structurally encourage process improvement efforts so that the big-picture benefits. That is, improving the Xs in the Y=f(X) relationship so that Y will improve in the future.

To illustrate this commonplace reporting problem, consider that a monthly Y goal in an organization is the number of units shipped. Consider next that a current month’s goal is not being met. For this situation, to meet this current-month goal, future orders are pulled into the current month at great expense to the organization to achieve the monthly objective. The general organizational consensus is that we will worry about next month’s goal when next month arrives. This commonplace practice can create much administrative chaos and negatively impact the organization’s overall financials.

Traditional quality metrics reporting formats do not encourage improving the X’s in a process so that the Y response will be better in the future. For the previous shipment-numbers-goal illustration, perhaps the organization should undertake to enhance its marketing and sales processes so it can, in the future, ship more products monthly without robbing from future-placed orders to achieve a current month goal.

30,000-foot-level reporting resolves all these issues. 30,000-foot-level metric reporting is reporting so that the best actions or non-actions occur in an organization. 30,000-foot-level is the reporting of process-output responses from a high-level point of view (not unlike looking at the terrain below from the window of an airplane in flight) that often can provide a predictive statement. If a futuristic message for a process-output response is undesirable from this reporting, there is a need for process improvement.

Organizational Quality Metrics

Metrics are reported and can typically have several report-out formats at various levels in an organization.


For IEE metric reporting, there is the referencing of satellite-level metrics for financial and 30,000-foot-level for operational metrics.


quality metrics satellite and 30,000-foot-level reporting


The following video describes how to use a free app to create 30,000-foot-level and satellite-level reports; however, Enterprise Performance Reporting System (EPRS) software can provide automatic updates of 30,000-foot-level metrics as an organization-wide KPI dashboard behind an organization’s firewall.



This video describes the issues and how 30,000-foot-level reports address the shortcomings of the commonplace practices of:

  • Process-performance metrics
  • Key Performance Indices (KPIs) reporting

This video also addresses issues with the following methodologies and how 30,000-foot-level quality metric reporting addresses these problems:

  • Control charts for a Y response in the relationship Y=f(x)
  • Process capability indices (Cp, Cpk, Pp, and Ppk)

Quality Metrics Reporting of Control Charts and Process Capability Indices

Control charts and process capability indices are one form of quality metrics reporting that appears in the hierarchy of corporate metric reporting:


Control Charts Issues and Resolution

Often there are issues with how organizations use control charts, leading to much-wasted efforts and untended consequences.

The primary purpose of control charts is to timely identify out-of-control signals or special cause events so the organization can take appropriate action to resolve an unusual process response.

Control charts provide no insight into how well a process performs relative to specifications or customer requirements.

Control charts can create false out-of-control signals, especially when process-output tracking at a high Y-level in the relationship Y=f(x).

It is essential to understand the UCL and LCL basics listed below for a control chart:

  1. The use of data determined control chart’s Upper Control Limit (UCL) and Lower Control Limit (LCL) values provides guidance to whether a special-cause situation has occurred in a tracked response.
  2. When data are within UCL and LCL limits, one infers that the process is in control and only exhibits common-cause variation or noise for a process-output response. Values outside UCL and LCL limits can originate from special cause events, where corrective action may be appropriate.
  3. A question for one to consider: When calculating UCL and LCL values for a control chart that tracks a process from a high-level perspective, should the variability between adjacent time-series values or subgroups be considered a source of common-cause or special-cause variation? Before responding to this question, consider that an organization receives a new supplier shipment every day. The question is: should the variation between days be considered a source of common-cause variation or not? Most say this day-to-day source of variation should be considered common-cause. Only an individuals-control-chart mathematically considers “between subgroup variation” a source of common causes variation. X-bar & R, P-charts, and C-charts do not.

The articles below and a book (Chapters 10 – 13 of Integrated Enterprise Excellence Volume III) describe why only individuals control charts tracks between adjacent reported values as common-cause variation sources. And, how there are issues with the traditional high-level reporting of metrics using control charts:

The video describes the use of a  free app to create 30,000-foot-level reports that address these issues.

Process Capability/Performance Reporting Issues and Resolution

Process Capability or Performance Indices explain how a process is performing relative to specifications in Cp, Cpk, Pp, and Ppk units when a process is in control.

Reported Cp, Cpk, Pp, and Ppk values are hard to interpret and dependent upon how samples are collected. Process capability indices determined from x-bar and R chart data can be quite different than if the determination of indices were from an individuals-control chart dataset from the same process.

Process capability indices reporting provide only a snapshot report-out of values for an arbitrarily selected period, perhaps the current year, where the process may or may not be in control.

Organizations need to understand how a process output response is currently performing from a high-level point of view, whether a specification exists or not, in terms that are easily understood.

Traditional process capability and performance indices do not address this need for many reasons.

Reported Cp, Cpk, Pp, and Ppk values:

  1. Are only appropriate if a process is stable or “in-control”; however, a process capability report-out statement does not provide this assessment in the same chart.
  2. Are valid if the data are from a normal distribution or an appropriate data transformation is made.
  3. Are difficult to understand
  4. Values are dependent upon how data are collected, e.g., data from an x-bar and R chart can provide a much different set of values than an individuals chart from the same process
  5. The calculation requires a specification; however, often, process outputs do not have a specification; e.g., work in process or WIP
  6. Calculated at one point in time and is not automatically updated.
  7. Reported values do not provide a prediction statement
  8. Reporting doesn’t encourage process improvement.

The article below and a book (Chapters 10 – 13 of Integrated Enterprise Excellence Volume III) describe why item number 4 in the above list is valid and how there are issues with the traditional reporting of process capability/performance indices:

The video describes the use of a  free app to create 30,000-foot-level reports that address these issues.


business management system meeting


Contact Us through an e-mail or telephone call to set up a time for a discussion on how your organization might gain much from an Integrated Enterprise Excellence Business Process Management system. Or, a Zoom meeting can be schedule directly:

E-mail ([email protected]) or call us (+1.512.918.0280), if you encounter difficulties setting up a Zoom session directly or want to schedule another time that is not available in the Zoom-meeting calendar.

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