Quality Progress - September 2017 - 39

initial set of data is collected during this phase.15
Organizations make, buy or build decisions at this
stage. They perform cost-benefit analysis and may
choose to procure commercial advanced analytics tools
or have an internal IT department develop or customize
appropriate analytics tools or use open-source advanced
analytics tools. As researchers Robert Nisbet, John F.
Elder and Gary Miner wrote, a 90% solution performed
by a relatively cheap tool might be more cost effective
than using "the best tool" that is expensive.16
Analyze: This stage involves creating descriptive,
diagnostic, predictive and prescriptive models using
advanced analytics integrated with statistical process
control tools and operational data reporting tools.
Improve: This stage involves identifying, evaluating,
implementing and optimizing models and solutions.
Models and solutions are optimized or improved, and
data sources and tools to develop models are reviewed
and enhanced.
Control: This stage involves setting up short-term and
long-term plans to sustain improvements.

Quality knowledge infrastructure

Organizations can collaborate with educational institutions to educate and train their workforces to build the
necessary quality knowledge infrastructure required to
integrate advanced quality analytics with lean Six Sigma
methods. For instance, a new course on data mining
applications in quality management was developed in
the department of engineering technologies at Bowling
Green State University in Ohio as part of the school's
quality systems educational collaboration (QSEC)
program. The QSEC program is designed to address
workforce needs in industries such as manufacturing,
construction, healthcare, service, government, education, retail and nonprofit.17
Because advanced analytics supplements and complements lean Six Sigma methods, it seems quite natural
to include advanced analytics courses as part of the
existing quality knowledge infrastructure.
The aim of this new course is to teach statistical
analysis and data mining concepts, methods, tools and
techniques so students can gain valuable knowledge
that can be applied to industrial situations.
Course content includes:
+ Historical and theoretical background for statistical
analysis and data mining.
+ Integration with data preparation and discovery operations necessary to perform modeling.
+ Basic algorithms and applications in which data mining
technology is commonly used.

+ Creating cost-effective
data mining models.
Organizations can benefit
+ Tips for avoiding misby leveraging the latest
takes of data mining
innovations in IT, such as
practice.
advanced analytics, to be
Learning activities
competitive in the global
include:
marketplace.
+ Gaining knowledge in
statistical analysis and
data mining concepts, methods, tools and techniques, and creating big ideas.
+ Working effectively in teams to present big
ideas.
+ Presenting big ideas to stakeholders (other
students and instructors), understanding perspectives and obtaining feedback to improve the
overall knowledge.
+ Critiquing the work of other students with the intent of
improving overall knowledge.
+ Applying planning, leadership, teamwork, critical
thinking, problem solving and interpersonal skills.
Expected learning outcomes of the course include:
+ Acquiring knowledge on statistical analysis and data
mining concepts, methods, tools and techniques.
+ Working in teams to develop plans, analyze problems
and present solutions and ideas to stakeholders in a
clear and concise manner both orally and in writing.
+ Demonstrating ethical and professional behavior.

Adding to the lean Six Sigma toolkit

As author Greg S. Nelson wrote, the opportunities for
improving our methods of decision making will continue to grow as we seek to improve our effectiveness
and efficiency by combining information, visualization
techniques, social networking and new models of
collaboration.18 Executives, managers and workers no
longer need to make decisions based on intuition or
instinct.19
Organizations can benefit by leveraging the latest
innovations in IT, such as advanced analytics, to be
competitive in the global marketplace.20 Organizations
that fail to leverage these new opportunities will not stay
competitive and they will fall behind.21
All sectors-including government, healthcare, education, manufacturing and services-can benefit from
these new opportunities. For example, a U.S. federal
agency-the Intelligence Advanced Research Projects
Activity-assumed the task of analyzing massive public
data sets to help government officials predict significant
events, such as political unrest, disease outbreaks or
natural disasters.22

qualityprogress.com ❘ September 2017

QP 39


http://www.qualityprogress.com

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

Seen and Heard
Progress Report
Mr. Pareto Head
Career Coach
Expert Answers
Field Notes
Data Disruption
The Deal With Big Data
Better Intelligence
A Study in Measurement
Innovation Imperative
Statistics Spotlight
Standard Issues
ASQ's 2017 Quality Resource Guide
Marketplace
Footnotes
Back to Basics
Quality Progress - September 2017 - Intro
Quality Progress - September 2017 - cover1
Quality Progress - September 2017 - cover2
Quality Progress - September 2017 - 1
Quality Progress - September 2017 - 2
Quality Progress - September 2017 - 3
Quality Progress - September 2017 - 4
Quality Progress - September 2017 - 5
Quality Progress - September 2017 - Seen and Heard
Quality Progress - September 2017 - 7
Quality Progress - September 2017 - Progress Report
Quality Progress - September 2017 - 9
Quality Progress - September 2017 - Mr. Pareto Head
Quality Progress - September 2017 - 11
Quality Progress - September 2017 - Career Coach
Quality Progress - September 2017 - 13
Quality Progress - September 2017 - 14
Quality Progress - September 2017 - Expert Answers
Quality Progress - September 2017 - Field Notes
Quality Progress - September 2017 - 17
Quality Progress - September 2017 - 18
Quality Progress - September 2017 - 19
Quality Progress - September 2017 - Data Disruption
Quality Progress - September 2017 - 21
Quality Progress - September 2017 - 22
Quality Progress - September 2017 - 23
Quality Progress - September 2017 - 24
Quality Progress - September 2017 - 25
Quality Progress - September 2017 - The Deal With Big Data
Quality Progress - September 2017 - 27
Quality Progress - September 2017 - 28
Quality Progress - September 2017 - 29
Quality Progress - September 2017 - 30
Quality Progress - September 2017 - 31
Quality Progress - September 2017 - 32
Quality Progress - September 2017 - 33
Quality Progress - September 2017 - Better Intelligence
Quality Progress - September 2017 - 35
Quality Progress - September 2017 - 36
Quality Progress - September 2017 - 37
Quality Progress - September 2017 - 38
Quality Progress - September 2017 - 39
Quality Progress - September 2017 - 40
Quality Progress - September 2017 - 41
Quality Progress - September 2017 - A Study in Measurement
Quality Progress - September 2017 - 43
Quality Progress - September 2017 - 44
Quality Progress - September 2017 - 45
Quality Progress - September 2017 - 46
Quality Progress - September 2017 - 47
Quality Progress - September 2017 - Innovation Imperative
Quality Progress - September 2017 - 49
Quality Progress - September 2017 - 50
Quality Progress - September 2017 - Statistics Spotlight
Quality Progress - September 2017 - 52
Quality Progress - September 2017 - 53
Quality Progress - September 2017 - Standard Issues
Quality Progress - September 2017 - 55
Quality Progress - September 2017 - 56
Quality Progress - September 2017 - 57
Quality Progress - September 2017 - ASQ's 2017 Quality Resource Guide
Quality Progress - September 2017 - 59
Quality Progress - September 2017 - 60
Quality Progress - September 2017 - 61
Quality Progress - September 2017 - 62
Quality Progress - September 2017 - 63
Quality Progress - September 2017 - 64
Quality Progress - September 2017 - 65
Quality Progress - September 2017 - 66
Quality Progress - September 2017 - 67
Quality Progress - September 2017 - Marketplace
Quality Progress - September 2017 - 69
Quality Progress - September 2017 - Footnotes
Quality Progress - September 2017 - 71
Quality Progress - September 2017 - Back to Basics
Quality Progress - September 2017 - cover3
Quality Progress - September 2017 - cover4
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