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

l

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

Business intelligence (BI) is a broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions.

Things Are Getting More Complex

• Source systems include social media, machine sensing, and clickstream data (Big Data)• The cloud, Hadoop/Reduce, and appliances are being used as data stores• Advanced analytics are growing in popularity and importance

Master Data Management

BI Competency Centers

Pervasive BI

Advanced Data VisualizationBI Governance

SaaS

Open Source BI Software

Data Appliances

Predictive Analytics

Rules Engines

BI Based Organizations

Real Time BI

Big Data

BI 2.0 Software BI Search

Hadoop/MapReduce

Mobile BI

Event Analytics

BI in the Cloud

In-Memory Analytics

Columnar Databases

Text Analytics

Data Scientists

Agile

What Is Meant by Analytics?

• A new term for BI

• Just the data analysis part of BI

• “Rocket science” algorithms

• Three kinds of analytics

Descriptive Analytics

What has occurred?

Predictive Analytics

What will occur?

Prescriptive Analytics

What should occur?

There are different “targets” for BI

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

For BI-based organizations, the use of BI/analytics is a

requirement for successfully competing in the marketplace.

5-6%Firms thatemphasizedata and analytics

ProductivityReturn on equityMarket value

2011 Academic Research

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 RetailersBI Applications• Analysis of clickstream data • Customer profitability analysis• Customer segmentation analysis• Product recommendations• Campaign management• Pricing• Forecasting• Dashboards

“We are a business intelligence company”

Patrick Byrne, CEO, Overstock.com

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

FirstAmerican

Responding to a problem: First American Corporation

• The business strategy was enable by a data warehouse and BI

FirstAmerican

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”

FirstAmerican

1. What is special about advanced analytics?

2. What are the requirements for being a BI or analytics-based organization?

Let’s Answer Two Questions

A clear business need

Strong, committed sponsorship

Alignment between the business and IT strategy

A fact-based decision making culture

Creating a Fact Based Culture

• Things that senior management needs to do:Recognize that some people can’t or won’t

adjustBe a vocal supporterStress that outdated methods must be

discontinuedAsk to see what analytics went into decisionsLink incentives and compensation to desired

behaviors

A strong data infrastructure

Source: Eckerson, 2011

The right analytical tools

New tools and architectures may be needed

Strong analytical personnel in an appropriate organizational

structure

Knowledge Requirements for Advanced Analytics

Business Domain

ModelingData

Business AnalystUses BI tools and applications to understand business conditions and drive business processes

Data Scientist

Uses advanced algorithms and interactive exploration tools to uncover non-obvious patterns in data

ModelingModeling

Business Analyst Data Scientist

Business Domain Business Domain

Data Data

Business Analyst Data Scientist

Education: BBA, MBA MS, PhD

Tools: Cognos, Hyperion KXEN, SAS

Analytics: OLAP Neural networks

Focus: Business Analytics

Scope: Departmental Enterprise-wide

Value: High Exceptionally high

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

• Concepts, terms, and definitions• Making the business case for BI• Development methodology for BI • Data and data warehousing• BI software• Interface design• BI applications (e.g., dashboards)• Analytics• Best practices case studies• Organizational issues• Determining the ROI for BI• Implementing BI enterprise wide• Future directions for BI

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

Resources from TUN

• Articles Current state of BI Business analytics Big data Future directions for BI software Understanding users value proposition Decision support sweet spot Dashboards and scorecards Dashboard design Data warehousing Data profiling Data quality Data mining primer Assessing BI readiness Business schools need to change what they teach

Resources from TUN

• Cases Harrah’s First American Corporation Continental Airlines Retailstore.com Catalina Marketing Norfolk Southern Railway Spokane Teachers Credit Union U.S. Xpress

• Videos Applebee’s Nationwide Continental Airlines BSI: Retail Tweeters

Resources from TUN

• Assignments 1-800 CONTACTS Genericorp

• Software Teradata SQL Web Assistant MicroStrategy Tableau

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.http://www.beyeresearch.com/executive/15546

• LaValle, et al., “Analytics: The New Path to Value,” IBM, MIT Sloan Management Review, 2010, http://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.

Dr. Hugh J. Watson is a Professor of MIS and a holder of a C. Herman and Mary Virginia Terry Chair of Business Administration in the Terry College of Business at the University of Georgia. Hugh has authored 23 books and over 150 scholarly journal articles. He is a Fellow of the Association for Information Systems and The Data Warehousing Institute and is the Senior Editor of the Business Intelligence Journal. For the past 20 years, Hugh has been the consulting editor for John Wiley & Sons’ MIS series. He can be contacted at hwatson@uga.edu