A review of the two main types of variation that can affect a process – common cause variation and special cause variation.

1. Section & Lesson #:
Pre-Requisite Lessons:
Complex Tools + Clear Teaching = Powerful Results
Variation Causes (Common vs. Special)
Six Sigma-Measure – Lesson 14
A review of the two main types of variation that can affect a process –
common cause variation and special cause variation.
Six Sigma-Measure #13 – Comparing Distributions and using
the Graphical Summary
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted by any means
(electronic, mechanical, photographic, photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.

2. o Variation measures how data are spread around the central tendency (mean/median).
• For two processes of throwing darts, which process would you prefer to have?
• Process A yields a higher score, but Process B is more consistent & predictable (less variation)
o Variation reflects where we have less control and where we feel the most pain
• The degree of variation affects the degree of difficulty to correct/fix.
• The degree of predictability affects the degree of control and comfort.
 Thermostat calibration
 A teenage child’s curfew
 Prices at discount stores (“Always low prices…Always”)
Reviewing the Concept of Variation
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Process A: Process B:
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.

3. o Not all variation is necessarily bad – as long as it’s controlled.
• Process variation can be related to the amount of control you have for that process.
• If we can understand and control our variation, we can have more control of the process.
o There are two types of variation: Common vs. Special.
• In the illustration at right, the
two left darts may be worth the
same points as the others, but
their variation suggests something
influenced their process:
Types of Variation: Common vs. Special
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Common Cause Variation:
The distance between these
darts may represent natural,
random variation in the process.
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Characteristics Common Cause Variation Special Cause Variation
Also Known As Noise Signal or Anomaly
Variation Type Natural & Random Unnatural & Erratic
Distribution Type Normal Non-Normal
Source of Process “Pain” Secondary Primary
Process Impact Generally from within the process Generally from outside the process
Examples •Poor design
•Normal wear and tear
•Poor environment (moisture, temp, etc.)
•Poor maintenance
•Power surge
•Extreme weather conditions
•System/computer malfunction
•Poor batch of raw materials
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.
Special Cause Variation:
Their distance from the other darts may
represent unnatural variation in the
process causing them to land so far away.

4. Practical Application
o Identify at least 3 critical metrics used by your organization that tend to have volatility.
• Ask yourself the following for each metric:
 What has the variation been like for the metric for the last year?
 How does the organization typically respond to the variation? (E.g., over-react by quickly taking action, or
over-analyzing by being slow to take action, etc.)
 What has generally been the reason(s) for the variation observed in the metric?
 Are the reasons more often common cause variation or special cause variation?
– For example, many organizational leaders tend to find a reason for certain jumps or drops in a metric and in that sense
are looking for a special cause; but in actuality, it may be a common cause that may not be so easy to identify and fix.
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.
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