TOP: BUSINESS ANALYTICS
MGT 2206 001
Welcome!
Matthew J. Liberatore
Fall 2009
Introduction
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Many firms are awash in data
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Enterprise Resource Planning (ERP) Systems
provide voluminous business data
The internet offers customer and market data
and the opportunity to experiment with
different product, promotion, and pricing plans
RFID devices will be placed on virtually every
pallet or carton generating vast amounts of
new data
Introduction
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These trends are leading firms to use and
analyze data to improve business
performance and make better decisions
Competing on Analytics by Davenport and
Harris: some firms use analytics as a
competitive weapon
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Consider some examples, many from our
research
Analytics Competitor: Netflix
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Movie recommendation engine
“throttling”: infrequent-use customers
(most profitable) given priority in shipping
Paying for distribution rights of DVDs (look
at success of related movies)
Analytics Competitors in Sports
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Moneyball by Michael Lewis
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Boston Red Sox
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A’s consistently make the playoffs despite a low
overall payroll
New metrics for player selection: “on-base
percentage” and “on-base plus slugging percentage”
Example: Martinez easier for opposing batters after 7
innings or 105 pitches (ALCS 2003)
New England Patriots: analytics both on and off
the field
Analytics Competitor:
Harrah’s Entertainment
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Customer loyalty card data used in nearreal time to optimize yield, set prices for
slots and rooms, and design traffic
through the casinos
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Predict the “pain point” and pull you away
from the slot machine
Which marketing initiatives to move
through which channels
HR analytics used in recruiting process
Vanguard
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Dashboards have non-financial metrics
and line of sight that roll up to a corporate
dashboard to drive outcomes
Customer analytics is a major focus where
data mining is used to score clients and
track problems
Six sigma and analytics combined to
improve business processes
Wyeth
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“metrics feed strategy and strategy feeds
metrics”
Ten high level enterprise metrics are
integrated and reviewed by the CEO and
top management
Analytics and six sigma help to manage
and improve all of their global processes:
innovation, sales and marketing, supply
chain, management, support
KPMG
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Metrics are key and help to understand
how strategy is being executed
Focusing on “electronic data discovery” –
how to build associations across data
Examples: bad debt chasing, payroll
process, SOX audit controls in vendor
sourcing and pricing, fraud discovery
Rohm and Haas
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Implementing an executive dashboard
Providing business managers with
operational metrics
Focusing analytics in supply chain,
customer relationships, working capital
reduction
FTI Consulting
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Analytics used in corporate finance,
economic consulting, forensic and
litigation consulting, as well as brand
management and strategic
communications in general
Focus on leading and predictive metrics
Nordstrom
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Analytics used at store level for merchandising
(ID trends/styles), and by upper management to
track customer interactions
Heavy use in determining who should receive
emails and catalogs in their multi-channel
operation
Lots of “test versus control” uses in the Direct
Marketing aspects of their business
Scorecards used to measure performance of
new predictive models against current ones
Air Products
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Extracts value from a single instance SAP system
enabling their supply chains via dashboards,
data accessibility via business warehouse cubes
Analytics integrates with their lean/six sigma and
other initiatives to drive customer and
shareholder value
Make visible data that is strategic such as
customer metrics like Perfect Order Fulfillment
Colgate
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Use data (financial, sales now R&D, shared
services coming) generated from global ERP
system to run the company
Most managers can “drill down” into data to
answer questions like “what did we buy today”
Measure the back end of sophisticated
marketing promotions to see what part worked
Marriott
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Marriott Rewards used analytics to predict
customer acquisition and retention
Realized, expected, and potential
customer value is measured
Predict each customer’s likelihood of
visiting a location on a weekday or
weekend in the next year
APQC Study
on Process Measures and Analytics
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Five participating companies: Wyeth, ING,
Marriott International, General Electric,
Caterpillar
Key findings:
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Analytics are applied within processes as early
warning indicators
Value of analytics greatly enhanced when integrated
into day to day processes
Integrating process analytics with continuous
improvement techniques such as Six Sigma and Lean
drives action and bottom line results
What Companies Are Telling Us
About Analytics
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“We are helping clients harness their vast amounts of
customer and operational data”
“We cannot find enough new grads with the right
quantitative skills”
“We compete on the basis of better knowledge of their
customers, using analytics”
“The riskier our business problems the more we rely on
analytics”
“After implementing our ERP system we are mining that
data, and using data better in different ways”
What Business Leaders Are
Saying…
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“In God we trust, all others bring data”
“Do you think that, or do you know that?”
“Those who succeed with six sigma, and
then advance in our company, have the
better quantitative skills”
“We are basing our strategy on analytics,
especially customer analytics”
What is Business Analytics?
Analytics has been defined as “the extensive
use of data, statistical and quantitative
analysis, explanatory and predictive
models, and fact-based management to
drive decisions and actions” (Davenport
and Harris, Competing on Analytics, 2007)
What is Business Analytics?
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Some authors view analytics as a subset
of business intelligence (BI): “a set of
technologies and processes that use data
to understand and analyze business
performance ” and “includes both data
access and reporting, and analytics”
(Davenport and Harris, Competing on
Analytics, 2007)
What is Business Analytics?
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For the purposes of this course, we will
not make any distinctions between
business analytics and BI
We consider business analytics to include
the access, reporting, and analysis of data
supported by software to drive business
performance and decision making
Introduction to Business Analytics:
Course Topics
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Overview of Business Analytics
Data Warehousing
Business Analytics and Data Visualization
Performance Management
Introduction to Data, Text, and Web
Mining
Data Mining Methods and Applications