Business Intelligence and How to Teach It
Hugh J. Watson
Terry College of Business
University of Georgia
Topics
Terminology, frameworks, and concepts
What’ s new in BI
Different BI targets
Exemplars of BI-based organizations
Requirements for being successful with BI and analytics
What I teach in my BI courses
Using the Teradata University Network to teach BI

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What Is Business Intelligence?
Its roots go back to the late 1960s
In the 1970s, there were decision support systems (DSS)
In the 1980s, there were EIS, OLAP, GIS, and more
Data warehousing and dashboards/scorecards became popular in the 1990s

What Is Business Intelligence?
Howard Dresner, a Gartner analyst, coined the BI term in the early 1990s
Today there is much discussion of analytics
There are many BI definitions, but the following is useful

What Is Meant by Analytics?
A new term for BI
Just the data analysis part of BI
Rocket science algorithms
Three kinds of analytics

A single or a few applications
A point solution
May be departmental
Serves a specific business need
A possible entry point

Enterprise analytical capabilities
The infrastructure is created for enterprise-wide analytics
Analytics are used throughout the organization
Analytics are key to business success
Organizational transformation
Brought about by opportunity or necessity
The firm adopts a new business model enabled by analytics
Analytics are a competitive requirement

Conditions that Lead to Analytics-based Organizations
The nature of the industry
Seizing an opportunity
Responding to a problem

Complex Systems versus Volume Operations
A distinction made by
Geoffrey Moore
Helps in understanding
what kinds of organizations
are most likely to be
analytics based
Complex Systems
Tackle complex problems and provide individualized solutions
Products and services are organized around the needs of individual customers
Dollar value of interactions with each customer is high
There is considerable interaction with each customer
Examples: IBM, World Bank, Halliburton
Volume Operations
Serves high-volume markets through standardized products and services
Each customer interaction has a low dollar value
Customer interactions are generally conducted through technology rather than person-to-person
Are likely to be analytics-based
Examples: Amazon.com, eBay, Hertz

The nature of the industry: Online Retailers
BI Applications
Analysis of clickstream data
Customer profitability analysis
Customer segmentation analysis
Product recommendations
Campaign management
Pricing
Forecasting
Dashboards

Seizing an Opportunity: Harrah’ s
In 1993, the gaming laws changed
Harrah’ s decided to compete and expand using a brand and customer loyalty strategy
Implemented WINet with an ODS and DW
Offered the industry’ s first customer loyalty program, Total Rewards

Seizing an Opportunity: Harrah’ s
Fact based decision making replaced Harrahisms
Today it is the largest gaming company in the world
Recently renamed Caesars
Responding to a problem: First American Corporation
The bank was failing
A new management team stopped the bleeding
A customer intimacy strategy was implemented, Tailored Client Solutions

Responding to a problem: First American Corporation
The business strategy was enable by a data warehouse and BI

Responding to a problem: First American Corporation
External talent was brought in as needed
Applications using VISION were developed for every component of TCS
The bank was transformed from banking by intuition to banking by information and analysis

Creating a Fact Based Culture
Things that senior management needs to do:
Recognize that some people can’ t or won’ t adjust
Be a vocal supporter
Stress that outdated methods must be discontinued
Ask to see what analytics went into decisions
Link incentives and compensation to desired behaviors

Where to put the analytics team?
Spread throughout the organization
In a standalone unit
In some form of an Analytics Competency Center
What I Teach in My BI Course

Teradata University Network

A premier, free online educational resource for university professors around the world who teach classes on data warehousing, DSS/business intelligence, and database.
Current Membership
Over 3,000 registered faculty members
Representing 1,641 universities
In 90 countries
Thousands of students

An international community, led by academics, whose members share their ideas, experiences, and resources with others

www.teradatauniversitynetwork.com

Using the Teradata University Network
Faculty apply for membership, and are authenticated
Faculty have access to course syllabi, articles, cases, projects, assignments, presentations, software (Teradata, MicroStrategy) various datasets, web seminars, and more.
Faculty have the ability to post and share their favorite content
Faculty send students to TUN to access course-related materials

References
Brynjolfsson, Hitt, and Kim, Strength in Numbers: How does data-driven decision-making affect firm performance?, Social Science Research Network (SSRN), April 2011.
Cooper, Watson, Wixom, and Goodhue, “Data Warehousing Supports Corporate Strategy at First American Corporation,” MIS Quarterly, December 2000.
Eckerson, Big Data Analytics, BeyeNetwork, September 2011.
Davenport, Harris, and Morison, Analytics at Work: Smarter Decisions, Better Results, Harvard Business School Press, 2010.

References
Davenport and Harris, Competing on Analytics: The New Science of Winning , Harvard Business School Press, 2007.
Eckerson, W. (2011). Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations. BeyeNetwork.
www.beyeresearch.com/executive/15546
LaValle, et al., Analytics: The New Path to Value, IBM, MIT Sloan Management Review, 2010, public.dhe.ibm.com/common/ssi/ecm/en/gbe03371usen/GBE03371USEN.PDF
References
Moore, Crossing the Chasm: Marketing and Selling High-tech Products to Mainstream Customers, HarperBusiness Essentials, 2002.
Moore, Inside the Tornado, HarperBusiness Essentials, 2004.
Watson, Business Analytics Insight: Hype or Here to Stay? Business Intelligence Journal, March 2011.
Watson and Volonino, Harrah’ s High Payoff from Customer Information, Printed in Eckerson and Watson, Harnessing Customer Information for Strategic Advantage: Technical Challenges and Business Solutions, TDWI, 2000.
References
White paper, The Current State of Business Analytics: Where Do We Go From Here? Bloomberg BusinessWeek Research Services, 2011.
Williams, Assessing BI Readiness: A Key to BI ROI, Business Intelligence Journal, Summer 2004.

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