Analytics Strategic Approaches V3_1-7-15

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Business
Analytics
Strategic
Approaches
PROVEN. RESULTS.
FASTER.
University of Tennessee
© Bradley, Miles and Pannell
Session Objectives

To review the definition of business analytics

To introduce five approaches to business analytics
Analytics Strategic Approaches
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What is Business Analytics?
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Blindfolded Men Describe Elephant
It’s a
Bridge
It’s a Snake
It’s a
Spear
It’s a
Blanket
It’s a
Python
It’s a Tree
Trunk
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Business
Blindfolded Men Describe Elephant
Analytics
It’s
Computer
Science
It’s
Statistics
It’s Data
Warehousing
It’s SAS
Software
It’s 6
Sigma all
over
again!
It’s
Executive
Dashboards
It’s
Mathematical
Models
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Davenport – Competing on Analytics
“The extensive use of data, statistical and
quantitative analysis, explanatory and predictive
models, and fact-based management to drive
decisions and actions”.
Re-quoted from Competing on Analytics
Enterprise Analytics. Thomas Davenport. Pearson Publishing. 2013. Page 9.
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Been There …… Done That?
TQM (1980’s)
Fact-based decision making. In order to know how well an organization is performing, data
on performance measures are necessary. TQM requires that an organization continually collect
and analyze data in order to improve decision making accuracy, achieve consensus, and allow
prediction based on past history.
Six Sigma (1990’s)
Features that set Six Sigma apart from previous quality improvement initiatives include:




A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma
project.
An increased emphasis on strong and passionate management leadership and support.
A special infrastructure of "Champions", "Master Black Belts", "Black Belts", "Green Belts", etc.
to lead and implement the Six Sigma approach.
A clear commitment to making decisions on the basis of verifiable data and
statistical methods, rather than assumptions and guesswork.
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Differences We See




Big Data
Real-Time use of data
Selling data
Decision-Based data
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The Best Definition
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Allen’s Definition of Business Analytics
Utilizing Data to Increase
Shareholder Value
Data =
 Big and Small
 Internal and External
 Structured and Non-structured
 Traditional and “New”
 “Free” and Purchased
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Allen’s Definition of Business Analytics
Utilizing Data to Increase
Shareholder Value
Utilizing =
 Determine Business Needs
 Capture and Store
 Ensure Quality
 Access and Format
 Analyze and Summarize
 Gain Insight and Produce Action
 and …….. ‘Sell’ It
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Types of Questions and Analytics
Descriptive
Questions What happened?
What’s happening?
What actions are
needed?
What exactly is the
problem?
What actions are
needed?
Enablers
•
•
•
•
Ad hoc Reports
Dashboards
Data Warehousing
Alerts
Outcomes Well defined business
problems and
PROVEN.
RESULTS. FASTER.
opportunities
Predictive
Prescriptive
Why is this happening?
What will happen next?
Why will it happen?
What should I do?
Why should I do it?
What’s the best that can
happen?
What if we try this?
•
•
•
•
•
•
•
•
Data Mining
Text Mining
Web/Media Mining
Forecasting
Accurate projections of
the future states and
conditions
Optimization
Simulation
Decision Modeling
Randomized Testing
Best possible business
decisions and transactions
Possible Strategies for Business Analytics
1.
2.
3.
4.
5.
Competing ON Analytics
 Analytics is THE key competitive advantage
 Target Result – Sustainable competitive advantage
Competing WITH Analytics
 Focus on one business process
 Target result – Incremental profits
Improving With Analytics
 Culture of analytics
 Target result – Continuous improvement
Revenue Through Analytics
 “Sell” data as a secondary product
 Improved margins or market share
Persevering Through Analytics
 Do what the competition does
 The price of entry
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Which Strategy?

Our Mission:
CareerBuilder's mission is to empower employment.
We are striving to organize all the world's human
capital data and make it meaningful for society
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Analytics Practices…Who’s Doing What?
1%
5%
4%
8%
12%
19%
51%
Improving with Analytics
(Incrementalists)
Competing with Analytics
(Internists)
Revenue through Analytics
(Industrialists)
Competing on Analytics
(Intensivists)
Persevering though Analytics
(Idlers)
Are you kidding me…I have no
idea!
Other
N=95 firms
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