What is the key difference between Common and Special Cause?

The difference between successful people and others is how long they spend time feeling sorry for themselves: Barbara Corcoran


There is a distinct difference between reality and illusion. Reality is a fact like Sunrises from the east and sets in the west direction. The illusion is an imaginary thing that trees are also running with us when we are traveling by train. The more we are clear about its difference, the wise person we can be.   


In the statistical studies, Walter Shewhart and W Edward Deming have done tremendous work to understand the variation in the process and its causes through statistical studies (mean, range, UCL, LCL, Cp, Cpk, Pp, Ppk, p, np, c, u). The understanding of these variations is important to improve quality, increase productivity and reduce cost (QCD).

There are 2 key causes of variations that are always acting on the process. They are Common Cause and Special Cause (assignable). By understanding these variations and taking suitable actions, the process can be brought under statistical control.



Common Cause: Variations that are consistently acting on the process. Produce a stable and repeatable distribution over time (in a state of statistical control) 

Special Cause (Assignable causes): Variations that affect only some part of the process output. Often intermittent and unpredictable.


Detailed Information

There is a fundamental law of nature that no two products or characteristics are exactly alike as processes contain many sources of variation. The differences may be immeasurably small or large, but they will always be there.

The sources of variation (example: a Machine Shaft) could be (6M) due to variation in the

  • Machine
  • Man (Operator)
  • Machine (Maintenance)
  • Material (Tool, Component)
  • Method (Competence)
  • Measurement (Error in measuring instrument)
  • Mother Environment (Temperature, Humidity)

These changes/variations may occur

  • Gradually (between piece to piece)
  • Stepwise (tool wear over time)
  • Irregularly (environmental change, power surge)

Based on the pattern of the changes, the organization should decide the frequency of measurement so that variation in the process can be captured and action can be taken before the process goes out of control.

The above changes result in the following 3 key types of variation in the process

  1. Location (mean/central value)
  2. Spread (width/span)
  3. Shape (pattern of variation-skewed, asymmetrical, etc.)

The goal should be to maintain the location to the target value and with minimal variability.

There are 2 key types of causes for the variation in the process

  1. Common Cause: Cough, Cold, Malaria, etc.
  2. Special Cause (Assignable causes): COVID!

Dr. Walter Shewhart developed the first control chart in the 1920s to describe common and special causes for Detection (tolerates waste) and Prevention (avoid waste)

Following are some of the key difference between Common and Special Cause:

S.No. Common Cause (chance cause) Special Cause (Assignable)
1 Natural Pattern, Variation within historical experience base Unusual Pattern, Variation outside historical experience base
2 Consistently act on the process Affect only some of the process output
3 A stable and repeatable distribution over time Intermittent and unpredictable
4 In a state of statistical control Signaled by one or more point outside the control limit
5 Yields a stable system of chance cause Non-random pattern of points within control limit
6 The process is predictable Process output will never be stable over a while
7 Requires more detailed analysis to isolate from the process Can be identified quickly. It could be either detrimental or beneficial
    If beneficial should be understood and made part of the process
    If detrimental should be understood and removed
8 Actions on the system to reduce variation due to common causes Local actions by people close to the process to eliminate it
9 Generally requires management action (supplier selection, Machine accuracy) to in-process. Can correct 85% of the process problems Can correct 15% of the process problems
10 Example: Inappropriate procedure, poor design, poor maintenance of the machine, ambient temperature and humidity, etc. Example: Faulty adjustment of machine, operator falls asleep, computer crash, broken part, the deficient batch of raw material, etc.


Present Challenges:

  1. How often the user of statistical techniques is aware of the difference between Common and Special causes?
  2. How often special causes are eliminated before calculating the process capability and process performance (Cp, Cpk)?
  3. How often common causes are misinterpreted as special causes and vice versa?


IATF 16949: 2016

SPC Manual (AIAG) 2nd Edition

Industry Experts


This is the 107th article of this Quality Management series. Every weekend, you will find useful information that will make your Management System journey Productive. Please share it with your colleagues too.

Your genuine feedback and response are extremely valuable. Please suggest topics for the coming weeks.

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Ashok Ratra
Ashok Ratra
2 years ago

Knowledge able. Please suggest ideas to develop poka yoke for every process, every machine