Quality Progress - May 2017 - 53

The question of whether
the solution is known or
Thomas Kuhn noted that the
unknown is a key conneed for a new paradigm
sideration in choosing a
is recognized when the list
method.
of problems not solved by
The important point is
existing paradigms becomes
that Six Sigma was not
too large to ignore.
needed, and perhaps
not even helpful, for this
installation. Some type of formal project management system
and possibly database protocols were needed to ensure success.
The integration of lean into Six Sigma helps avoid forcefitting Six Sigma because lean may be an appropriate method
for a given problem when Six Sigma is not. For example, lean
has proven principles that provide excellent guidance on
solution-known problems.18 However, just as Six Sigma is not
appropriate for all problems, neither is lean.
Any time you select the problem-solving method before you
have clearly documented the problem, you are prone to force
fitting. Shouldn't you learn about the problem first, and only then
determine the best approach to finding a solution? Who would
continue to see a physician who recommends treatment prior to
learning about the patient's condition?
Similarly, lean Six Sigma 1.3 does not incorporate routine problem solving. That is, suppose a manufacturing line begins leaking
oil at 3:30 a.m. This is not the time to put together a Six Sigma
team to gather data and study the problem for a few months;
someone needs to stop the leak ASAP. By routine problem solving we mean the day-to-day problem solving that occurs in all
organizations, typically in real time.
Some problems are not easily solved on a routine basis.
For example, suppose this is the fifth time this year one of the
machines in the plant has begun leaking oil. Why is this problem
recurring? Is the fundamental root cause the oil itself, the equipment, the way we are operating the equipment, the way we are
maintaining the equipment, or something else?
To solve this higher-level problem, a team and some formal
method, perhaps Six Sigma, will likely be needed. The point is
that routine problem solving is an important aspect of continuous improvement; however, you typically do not need lean

Ronald D. Snee is president of Snee
Associates LLC in Newark, DE. He has a
doctorate in applied and mathematical
statistics from Rutgers University in
New Brunswick, NJ. Snee has received
ASQ's Shewhart, Grant and Distinguished
Service Medals. He is an ASQ fellow and an
academician in the International Academy
for Quality.

Six Sigma-nor is there time-to conduct a lengthy
project. Immediate solutions are needed.
Fundamentally, lean Six Sigma 1.3 is a project-based
method for driving improvement, but it is not a complete quality management system (QMS). That is, it
does not replace ISO 9000 quality systems or provide
the same breadth as national quality awards, such as
the Baldrige award. For example, individual Six Sigma
projects may lead to calibrating measurement equipment in a lab in the measure phase, but they would
not provide an overall lab calibration system.
In our view, minor adjustments to lean Six Sigma
1.3 will not address these limitations. Rather, a new
paradigm will be needed. Thomas Kuhn noted that
the need for a new paradigm is recognized when the
list of problems not solved by existing paradigms
becomes too large to ignore.19 For the reasons noted
earlier, we feel lean Six Sigma 1.3 is now at this place.

Time to make the leap?

Some time has passed since Six Sigma was introduced and lean Six Sigma was developed. In the
meantime, the world and its needs have changed.
As a result, quality improvement must adopt a new
paradigm-one of holistic improvement called lean
Six Sigma 2.0.
This approach must incorporate various improvement methods for different types of problems,
integrate with an overall QMS, and address the other
limitations of lean Six Sigma 1.3 noted in Table 3.
Next month's Statistics Spotlight will elaborate
on what such a system might look like, including
consideration of large, complex and unstructured
problems, the emergence of big data analytics, and
the increased importance of risk management in
today's world. 
© 2017 Ronald D. Snee and Roger W. Hoerl

EDITOR'S NOTE
The references listed in this article can be found on the Statistics
Spotlight's webpage at www.qualityprogress.com.

Roger W. Hoerl is a Brate-Peschel assistant
professor of statistics at Union College
in Schenectady, NY. He has a doctorate
in applied statistics from the University
of Delaware in Newark. Hoerl is an ASQ
fellow, a recipient of ASQ's Shewhart
Medal and Brumbaugh Award, and an
academician in the International Academy
for Quality.

qualityprogress.com ❘ May 2017

QP 53


http://www.qualityprogress.com http://www.qualityprogress.com

Table of Contents for the Digital Edition of Quality Progress - May 2017

Seen and Heard
Expert Answers
Progress Report
Mr. Pareto Head
Field Notes
Mind the Gaps
Solid Footing
Are These the Same?
New Tricks for an Old Tool
Innovation Imperative
Experience More
Career Coach
Statistics Spotlight
Standard Issues
Marketplace
Footnotes
Back to Basics
Quality Progress - May 2017 - intro
Quality Progress - May 2017 - cover1
Quality Progress - May 2017 - cover2
Quality Progress - May 2017 - 1
Quality Progress - May 2017 - 2
Quality Progress - May 2017 - 3
Quality Progress - May 2017 - 4
Quality Progress - May 2017 - 5
Quality Progress - May 2017 - Seen and Heard
Quality Progress - May 2017 - Expert Answers
Quality Progress - May 2017 - Progress Report
Quality Progress - May 2017 - Mr. Pareto Head
Quality Progress - May 2017 - 10
Quality Progress - May 2017 - 11
Quality Progress - May 2017 - Field Notes
Quality Progress - May 2017 - 13
Quality Progress - May 2017 - 14
Quality Progress - May 2017 - 15
Quality Progress - May 2017 - Mind the Gaps
Quality Progress - May 2017 - 17
Quality Progress - May 2017 - 18
Quality Progress - May 2017 - 19
Quality Progress - May 2017 - 20
Quality Progress - May 2017 - 21
Quality Progress - May 2017 - 22
Quality Progress - May 2017 - 23
Quality Progress - May 2017 - Solid Footing
Quality Progress - May 2017 - 25
Quality Progress - May 2017 - 26
Quality Progress - May 2017 - 27
Quality Progress - May 2017 - 28
Quality Progress - May 2017 - 29
Quality Progress - May 2017 - Are These the Same?
Quality Progress - May 2017 - 31
Quality Progress - May 2017 - 32
Quality Progress - May 2017 - 33
Quality Progress - May 2017 - 34
Quality Progress - May 2017 - 35
Quality Progress - May 2017 - New Tricks for an Old Tool
Quality Progress - May 2017 - 37
Quality Progress - May 2017 - 38
Quality Progress - May 2017 - 39
Quality Progress - May 2017 - 40
Quality Progress - May 2017 - 41
Quality Progress - May 2017 - 42
Quality Progress - May 2017 - 43
Quality Progress - May 2017 - Innovation Imperative
Quality Progress - May 2017 - 45
Quality Progress - May 2017 - 46
Quality Progress - May 2017 - Career Coach
Quality Progress - May 2017 - 48
Quality Progress - May 2017 - 49
Quality Progress - May 2017 - Statistics Spotlight
Quality Progress - May 2017 - 51
Quality Progress - May 2017 - 52
Quality Progress - May 2017 - 53
Quality Progress - May 2017 - Standard Issues
Quality Progress - May 2017 - 55
Quality Progress - May 2017 - 56
Quality Progress - May 2017 - 57
Quality Progress - May 2017 - Marketplace
Quality Progress - May 2017 - 59
Quality Progress - May 2017 - Footnotes
Quality Progress - May 2017 - 61
Quality Progress - May 2017 - 62
Quality Progress - May 2017 - 63
Quality Progress - May 2017 - Back to Basics
Quality Progress - May 2017 - cover3
Quality Progress - May 2017 - cover4
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