Special Cause vs. Common Cause Variation
What is the variation?
Whatever measurement we take, there is always a variation between these measurements. No two items or measurements are precisely the same.
Quality Management Course
FREE! Subscribe to get 52 weekly lessons. Every week you get an email that explains a quality concept, provides you with the study resources, test quizzes, tips and special discounts on our other e-learning courses.
The problem with the variation is that it is the enemy of quality. Variation and quality do not go hand in hand. Variation reduction is one of the significant challenges of quality professionals.
Two types of variation, and why is it important to differentiate?
When dealing with variation, the challenge quality professionals face when to act and when not to act. Because if you act on each and every variation in the process and adjust the process, this will be a never-ending process. Dr. Deming called this "tempering the process." Rather than improving the quality, tempering, in fact, reduces the quality. Deming demonstrated the effect of tempering with the help of a funnel experiment.
The causes of variation can be classified into two categories:
- Common Causes
- Special Causes
Root Cause Analysis - Online Training
Common Cause Vs Special Cause: Types of Variation
Common cause variation is the natural variation in the process. It is a part of the process. There are "many" causes of this type of variation, and it is not easy to identify and remove these. You will need to live with them unless drastic action is taken, such as process re-engineering.
Common causes are also called natural causes, noise, non-assignable and random causes.
Special cause variation, on the other hand, is the unexpected variation in the process. There is a specific cause that can be assigned to the variation. For that reason, this is also called as the assignable cause. You are required to take action to address these variations.
Special causes are also called assignable causes.
Seven Basic Quality Tools
Control Charts to identify special causes
If the measurements of a process are normally distributed, then there is a 99.73% chance that the measurement will be within plus and minus three standard deviations. This is the basis of control charts.
If you plot the measurements on a Control Chart, then any measurements which are outside the plus and minus three standard deviation limits are expected to be because of a special cause. These limits are called as the Upper Control Limit (UCL) and the Lower Control Limits (LCL), Once you get such measurement, you are expected to investigate, do the root cause analysis, find out the reason for such deviation and take necessary actions.