A review of why the Measure phase is so important to the DMAIC process and why it’s so often neglected.

1. Section & Lesson #:
Pre-Requisite Lessons:
Complex Tools + Clear Teaching = Powerful Results
The Necessity of the Measure Phase
Six Sigma-Measure – Lesson 2
A review of why the Measure phase is so important to the DMAIC process
and why it’s so often neglected.
Six Sigma-Overview #01 – Problem Resolution using DMAIC
Six Sigma-Overview #02 – Risk Analysis
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. The Necessity of the Measure Phase
o Remember, we’re solving a problem that requires gathering reliable information.
• In the Define phase, you should have a clear understanding of the problem’s severity & scope.
• Now in the Measure phase, you need to gather reliable information that you can trust.
 The analysis and improvements are only as good as the data on which they’re based.
o The Measure phase is probably the most critical and yet most neglected phase.
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.
Problem Resolution: 6 Sigma DMAIC:
Understand
the problem
Gather
reliable info
Identify
root cause
Fix
root cause
Sustain
Improvement
Define
Measure
Analyze
Improve
Control
Why Is Measure the most
essential phase in DMAIC?
•What if your data is wrong?
•How does it affect your…
• analysis to find the root cause?
• improvements to fix the root cause?
• controls to sustain the improvements?

3. Why is the Measure Phase Often Neglected?
o Remember the jelly bean example from the lesson on risk analysis?
• Question: How many red jelly beans are in the jar?
 Method 1: Empty out all of the jelly beans and manually count the red ones.
– Advantage: More Accurate vs. Disadvantage: More Time
 Method 2: Count the red ones in a small sample & multiply by the jar’s volume.
– Advantage: Less Time vs. Disadvantage: Less Accurate
o Which method of counting the jelly beans is best?
• Neither, because both are equally valid methods for counting the red jelly beans.
• What makes one method “better” than another at the moment depends on RISK vs. REWARD.
• Risk is determined by the disadvantages for each method:
 Method 1: Is the reward worth the risk of taking “more time” to use this method?
– If the reward was $1M, then perhaps the risk of more time is worth ensuring we’re more accurate.
 Method 2: Is the reward worth the risk of being “less accurate” to use this method?
– If the reward was a t-shirt, then perhaps the risk of being less accurate is worth it taking less time.
o What does this have to do with the Measure phase being often neglected?
• To validate the data, the Measure phase may require more time that we’re not willing to invest.
 Do we regard time (speed of resolution) as a higher priority than accuracy (the right solution)?
– How can we appropriately balance speed vs. accuracy in the jelly bean example?
– What if the analysis was for testing health risks for new medicines? Or testing safety in new cars?
• Remember, the goal is not to eliminate risk, but to balance risk with rewards.
 The pre-assessment in the Define phase can help us predict the potential benefits (reward).
– If the benefits are low, then risk is probably low; therefore, the speed of analysis may be more important.
– If the benefits are high, then risk is probably high; therefore, the accuracy of analysis may be more important.
 Always validate the risks vs. rewards with the Sponsor; this will help in planning your analysis timeline.
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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4. Practical Application
o Think of at least 3 prior situations you’ve worked that required some data analysis.
• For each situation, try to answer the following questions:
 When the situation began, which was more important: getting quick results or getting accurate results?
– Who determined that level of importance?
– If it was not you, then do you agree with that level of importance?
 How much time was spent collecting the data and validating it before you began analyzing it?
 After you began to analyze the data, did you find that any of it was wrong or incomplete?
– If so, how much extra time was spent re-collecting and validating the data?
– How much time could have been saved if you had more thoroughly collected and validated the data the first time?
 After the situation was completed, did the priorities change between quick or accurate results?
– If so, why did it change?
– Did the priority really change, or was the risk neither fully understood nor fully communicated from the beginning?
– What would you do differently next time if you suspect the priority between quick or accurate results may change?
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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