A enhanced control chart that includes a process capability statement (that is easy to understand) is provided in a 30,000-foot-level report-out. Organizational 30,000-foot-level metrics can be integrated with their processes via a value chain in the Integrated Enterprise Excellence (IEE) Business Management System.
Below is a description of control chart issues and 30,000-foot-level resolution techniques that can be used to reduce firefighting and enhance organizational improvement efforts.
Control Chart Issues and 30,000-foot-level Resolution
Content of this webpage is from Chapters 12 and 13 of Integrated Enterprise Excellence Volume III – Improvement Project Execution: A Management and Black Belt Guide for Going Beyond Lean Six Sigma and the Balanced Scorecard, Forrest W. Breyfogle III.
A Control chart can be used to timely identify out-of-control or special-cause conditions so that the appropriate action can be taken; e.g.,
- and R control charts (x-bar and R control charts) are used for continuous data where there are multiple samples in a subgroup.
- P-chart is used for failure-rate tracking.
- C-chart is used for count-data tracking.
As a complement to control charting, process capability statements describe how a process is performing relative to meeting customer specification needs.
However, there are issues in how the and R control chart, p-chart, and c-chart are often created and applied. Also there are some issues with how traditional process capability statements are made. These shortcomings and an alternative methodology for creating control charts and process capability statements will be addressed in this article and its links.
Control charting and process capability statements have traditionally been applied in manufacturing applications. With the advent of the Lean Six Sigma techniques for process improvement, control chart and process capability techniques have also been applied within transactional processes. However, traditional control chart and process capability training for both manufacturing and transactional environments often fail to emphasize that the approach used to create a control chart and its sampling plan can dramatically impact conclusions about the type of action that should be taken in a process or whether any action should be taken at all.
What this implies is that one person could describe a process to be out of control, which would lead to activities that immediately address process perturbations as abnormalities, while another person could describe the same process as being in control. This is a very important point, which will be resolved with the described methodology. A 30,000-foot-level reporting methodology provides a means to get around this problem
Separating Special Cause from Common Cause Events in a Control Chart
The control chart terms “common-cause” and “special-cause” variability can lead to different interpretations and action plans. To address this, a so-called Shewhart approach will be presented and then a Deming approach. Elaboration will then be made on a preferred methodology, along with an explanation of how it can be integrated with a Lean Six Sigma project-by-project improvement strategy.
In the 1920s, Walter Shewhart of Bell Laboratories developed a theory that there are two components to variation: a steady component from random variation and intermittent variation due to assignable causes.1 Shewhart’s improvement approach was that assignable causes could be removed with an effective diagnostic program, while random causes could not be removed without making basic process changes.
From this work, Shewhart developed the standard control chart. This control chart used three standard deviation limits of the sampling distribution to separate steady components from assignable causes. Shewhart’s control charts came into wide use in the 1940s because of war production efforts. Western Electric was later credited with adding sequence and runs tests to control charts.2
W. Edwards Deming later gained fame for his work with Japan in its process improvement efforts after World War II. Later in his career, he made significant headway helping American industries become more competitive. Within his work, Deming noted:3
- “A fault in the interpretation of observations, seen everywhere, is to suppose that every event (defect, mistake, accident) is attributable to someone (usually the one nearest at hand), or is related to some special event.
- “We shall speak of faults of the system as common causes of trouble, and faults from fleeting events as special causes.
- “Confusion between common causes and special causes leads to frustration of everyone, and leads to greater variability and higher costs, exactly contrary to what is needed.
- “I should estimate that in my experience most troubles and most possibilities for improvement add up to proportions something like this: 94% belong to the system (responsibility of management), 6% [are] special.”
From these authoritative descriptions, we could paraphrase their conclusions as:
- Shewhart: A special cause is an assignable cause that could be internal or external to the system.
- Deming: A special cause is an unusual event external to the system.
This basic philosophic difference between Shewhart and Deming impacts process tracking. Consider, for example, that a key process input variable (KPIV) affects a process output. You might not know how this KPIV affects your process or even whether it adversely impacts the output of the process relative to customer needs. This type of KPIV could be created from differences between daily raw material batches or the number of daily phone calls received by a call center, which differ by day of the week.
The question is: Should these KPIVs (raw material batches or day of the week) be considered special cause? A Deming approach would view normal output levels from these KPIVs as common cause; however, since these variables are assignable, a Shewhart approach would consider their impact to the process as special cause.
The distinction between the two approaches is not trivial; a business would approach the solution differently depending on which approach was indicated. Therefore, it is important to understand the implications of the two alternatives before making a procedure selection.
What is suggested is an approach that builds upon the strengths of Lean Six Sigma for process improvement and is in alignment with Deming’s philosophy. This enhanced methodology will be referred to as Integrated Enterprise Excellence (IEE). With this approach, the organization will be tracked using high level metrics so that typical response levels from inputs within the system (even though they are assignable) will be reported as common-cause variability.
For this to occur, an infrequent subgrouping/sampling plan is needed so that potential input variables, which can affect the response, occur between these subgrouping categories. A control chart will then be created so the between-subgroup variability magnitude affects the lower control limit (LCL) and upper control limit (UCL) calculations.
With this approach, high level business metrics such as revenue and profit would typically be tracked using a monthly infrequent subgrouping/sampling plan. High-level operational metrics such as cycle time, inventory, a critical part dimension and defective rates might have a daily or weekly infrequent subgrouping/sampling plan.4
Within the IEE approach, high-level business metrics, which are not bounded by typical annual or quarterly boundaries, are referred to as satellite level metrics. High-level operational or key process output variable (KPOV) metrics are referred to as 30,000-foot-level metrics.4
30,000-foot-level Chart as an Alternative to a Traditional Control Chart
The traditional control chart methodology is designed primarily for manufacturing so that timely interventions are made for the inputs to a process. This can be a satisfactory approach in certain situation; however, often traditional control charting is used outside these specific applications. This point is addressed in the following where issues with traditional control charting techniques and their transformation to 30,000-foot-level reporting are described in:
- X-bar and R Control Chart: Issues and Resolution
- P-chart: Issues and Resolution
- C-chart: Issues and Resolution
Issues with traditional process capability statements and resolution are described in
The IEE 30,000-foot-level control chart and process capability alternative addresses the common place business scorecard issues described in a 1-minute video:
- Walter A. Shewhart, Economic Control of Quality of Manufactured Product, ASQ Quality Press, 1931, reprinted in 1980.
- Western Electric, Statistical Quality Control Handbook, Western Electric Co., 1956.
- W. Edwards Deming, Out of the Crisis, MIT Press, 1986.
- Forrest W. Breyfogle III, Integrated Enterprise Excellence Volume III – Improvement Project Execution: A Management and Black Belt Guide for Going Beyond Lean Six Sigma and the Balanced Scorecard, Bridgeway Books/Citius Publishing, 2008
Contact Us to set up a time to discuss with Forrest Breyfogle how your organization might gain much from an Integrated Enterprise Excellence (IEE) Business Process Management System and its enhanced control chart and process capability reporting methodology.