A control chart can identify one of two types of variation: assignable cause (also known as a special cause) and common cause. Let’s look at what assignable cause variation looks like and compare it to common cause variation. This article will explain how to determine if your control signals, and how to respond if it does.

What is an assignable cause?

A control diagram shows two types of variation. common cause variation is a random variation that results from process components or 6Ms. Special cause variation can be assigned.

If your control chart has plotted points that are not within the limit or show a non-random pattern in variation, this is considered assignable cause variation. You should be able to cause it. Special cause variation is unpredicted and caused by something other than randomness.

Your process variable is considered unstable or out of control when your control chart signals assignable causes variation. The Western Electric rules can help you identify signals of assignable cause variation. They include:

  • One point beyond the upper limit or below limit
  • A trend that has 6 or 7 points consecutively increasing or decreasing
  • A repeating or cycle
  • A series of 8 or more points consecutively on either side of the average or center line.

Assignable cause variation may be due to a defect or fault, mistake, delay in processing, accident, or shortage. It could also be due to a unique combination of factors that work together to improve the process. Your process can be unpredictable if there are no assignable causes. Your process may have been improved by your assignable cause. If so, you should incorporate it into your process to ensure that improvement is maintained and retained.

A case study from the industry of an assignable cause

Overbilling began to be a problem for the accounts receivable department at a retail chain. The department manager had taken part in Lean Six Sigma training at the company and was using a control chart to correct errors.

On closer inspection, she discovered that Fridays were the most common day for errors. The chart revealed that nearly all data points exceeded the upper limit on Fridays. She was worried that no one was recognizing that as a sign of special cause.

To determine the cause of this, she assembled a small group of clerks. It was Friday’s extra work load that was the cause.

To better balance the work week, the team suggested a change to the procedure. The problem was found and fixed by continued monitoring. An all-hands meeting was also held to discuss the importance of not ignoring signals of special cause variation, the need to search for an assignable cause, and the necessary action to take.