Quality Progress - March 2017 - 56

A refresher on a quality
tool, concept or method

Shedding
More Light

The scientific method can help
root cause analysis

TA B L E   1

The scientific method
Step

by Matthew Barsalou
The scientific method is used in science; however, it's
also appropriate when performing a root cause analysis.
Using the scientific method can help ensure that the true
cause of a failure is identified. Identifying the cause of a failure is essential because corrective actions will be ineffective
if they are not based on the root cause of the problem.
According to Stephen Tramel, there is no one scientific
method. There are, however, six steps that are commonly
used to test and evaluate the hypotheses (see Table 1).1
The first and last steps are empirical: They are based
on observations by using senses such as touch, hearing
or sight, and perhaps through measuring devices such as
calipers.
Observations are made and data collected during the
first step. Next, data are analyzed. In this example, an
analysis of the data indicates that all failures are occurring on parts produced on night shift. Then you must
generalize beyond the available data to form a hypothesis. In this case, the hypothesis is: "Only parts produced
during the night shift are failing."
The fourth step is assuming the hypothesis is true
for the sake of testing. Next, test results are predicted
based on the assumption that the hypothesis is true. The
hypothesis is tested during this final step. Parts from the
day and night shifts are completely inspected for a week.
Only night-shift parts should have failures if the hypothesis is correct. In this example, there is an approximately
equal number of failures between the two shifts, so the
hypothesis is rejected.
George E.P. Box, Stuart Hunter and William G. Hunter
explain that induction and deduction are used in forming
and evaluating hypotheses.2 To form a hypothesis,

Type of action

Actions

1

Empirical

Make observations and collect data.

2

Conceptual

Analyze the data.

3

Conceptual

Form a hypothesis that extends
beyond the available data.

4

Conceptual

Assume the hypothesis is true for
the sake of testing.

5

Conceptual

Predict what the test results would
be if the hypothesis is true.

6

Empirical

Test the hypothesis.

Source: Stephen Tramel, "Explanatory Hypotheses and the Scientific
Method," Ways of Knowing in Comparative Perspective: The WKCP
Companion and Anthology, Copley Custom Textbooks, 2006.

observed, and any known theories and uses. The hypothesis is tested. If it fails the testing, induction is used to
go from the results to a theory that fits the results, and a
new hypothesis is formed and tested.3
This process can be repeated until a hypothesis is
robust enough to survive testing. Using the earlier
example, you may hypothesize: "The failure occurs at an
equal rate between shifts, but the night shift was better
at detecting the failure."
The root cause still has not been found, but investigators now better understand the issue and are closer to
finding the root cause because they
are no longer examining nonexistent
REFERENCES
variation between shifts.
1. Stephen Tramel,
"Explanatory Hypotheses
The scientific method can help
and the Scientific
Method," Ways of
Perspective: The
tion to be being useful for researchers
WKCP Companion
and scientists, the method can apply
and Anthology, Copley
when investigating a quality failure.
Custom Textbooks, 2006.

Matthew Barsalou is a statistical problem resolution Master Black
Belt (MBB) at BorgWarner Turbo Systems Engineering GmbH in
Kirchheimbolanden, Germany. He has a master's degree in business
administration and engineering from Wilhem Büchner Hoschschule in
Darmstadt, Germany, and a master's degree in liberal studies from Fort
Hays State University in Hays, KS. Barsalou is an ASQ member and holds
several certifications.

56 QP

March 2017 ❘ qualityprogress.com

2. George E.P. Box, Stuart
Hunter and William
G. Hunter, Statistics
for Experimenters: An
Introduction to Design,
Data Analysis and Model
Building, second edition,
John Wiley & Sons, 2005.
3. Ibid.

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Seen and Heard
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Innovation Imperative
Hard Wired
Propel Forward
Life After Disruption
Work Smarter, Not Harder
Statistics Spotlight
Standard Issues
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Footnotes
Back to Basics
Quality Progress - March 2017 - cover1
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Quality Progress - March 2017 - Propel Forward
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Quality Progress - March 2017 - Life After Disruption
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Quality Progress - March 2017 - Work Smarter, Not Harder
Quality Progress - March 2017 - 41
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Quality Progress - March 2017 - Statistics Spotlight
Quality Progress - March 2017 - 45
Quality Progress - March 2017 - 46
Quality Progress - March 2017 - 47
Quality Progress - March 2017 - Standard Issues
Quality Progress - March 2017 - 49
Quality Progress - March 2017 - Marketplace
Quality Progress - March 2017 - 51
Quality Progress - March 2017 - Footnotes
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Quality Progress - March 2017 - 55
Quality Progress - March 2017 - Back to Basics
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