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Case 1-1 Opening Case iii
Information
Technology
for Management
Digital Strategies for Insight, Action,
and Sustainable Performance
10th
Edition
EFRAIM TURBAN
LINDA VOLONINO, Canisius College
GREGORY R. WOOD, Canisius College
Contributing authors:
JANICE C. SIPIOR, Villanova University
GUY H. GESSNER, Canisius College
FMTOC.indd Page iii 18/11/14 2:20 PM f-391
/208/WB01490/9781118897782/fmmatter/text_s
VP & EXECUTIVE PUBLISHER: Don Fowley
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MARKETING ASSISTANT: Elisa Wong
SENIOR CONTENT MANAGER: Ellinor Wagner

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BRIEF CONTENTS
1 Doing Business in Digital Times 1
2 Data Governance and IT Architecture Support Long-Term
Performance 33
3 Data Management, Big Data Analytics, and Records
Management 70
4 Networks for Efficient Operations and Sustainability 110
5 Cybersecurity and Risk Management 141
6 Attracting Buyers with Search, Semantic, and
Recommendation
Technology 181
7 Social Networking, Engagement, and Social Metrics 221
8 Retail, E-commerce, and Mobile Commerce Technology 264
9 Effective and Efficient Business Functions 297
10 Strategic Technology and Enterprise Systems 331
11 Data Visualization and Geographic Information Systems 367
12 IT Strategy and Balanced Scorecard 389
13 Project Management and SDLC 412
14 Ethical Risks and Responsibilities of IT Innovations 438
Glossary G-1

Organizational Index O-1
Name Index N-1
Subject Index S-1
Part 1
Part 2
Part 3
Part 4
Digital Technology
Trends Transforming
How Business Is Done
Winning, Engaging, and
Retaining Consumers
with Technology
Optimizing Performance
with Enterprise Systems
and Analytics
Managing Business
Relationships, Projects,
and Codes of Ethics
v
FMTOC.indd Page v 18/11/14 2:20 PM f-391

FMTOC.indd Page vi 18/11/14 2:20 PM f-391
CONTENTS
Part 1
Digital Technology Trends Transforming
How Business Is Done
1 Doing Business in Digital Times 1
Case 1.1, Opening Case: McCain Foods’s Success Factors:
Dashboards, Innovation, and Ethics 2
1.1 Every Business Is a Digital Business 6
1.2 Business Process Management and Improvement 15
1.3 The Power of Competitive Advantage 19
1.4 Enterprise Technology Trends 25
1.5 How Your IT Expertise Adds Value to Your Performance
and Career 27
Case 1.2, Business Case: Restaurant Creates Opportunities to
Engage Customers 31
Case 1.3, Video Case: What Is the Value of Knowing More and
Doing More? 32
2 Data Governance and IT Architecture Support
Long-Term Performance 33
Case 2.1, Opening Case: Detoxing Dirty Data with Data
Governance at Intel Security 34
2.1 Information Management 37

2.2 Enterprise Architecture and Data Governance 42
2.3 Information Systems: The Basics 47
2.4 Data Centers, Cloud Computing, and Virtualization 53
2.5 Cloud Services Add Agility 62
Case 2.2, Business Case: Data Chaos Creates Risk 67
Case 2.3, Video Case: Cloud Computing: Three Case Studies
69
3 Data Management, Big Data Analytics, and
Records Management 70
Case 3.1, Opening Case: Coca-Cola Manages at the Point That
Makes a Difference 71
3.1 Database Management Systems 75
3.2 Data Warehouse and Big Data Analytics 86
3.3 Data and Text Mining 96
3.4 Business Intelligence 99
3.5 Electronic Records Management 102
Case 3.2, Business Case: Financial Intelligence Fights Fraud
108
Case 3.3, Video Case: Hertz Finds Gold in Integrated Data 108
4 Networks for Efficient Operations and
Sustainability 110
Case 4.1, Opening Case: Sony Builds an IPv6 Network to
Fortify
Competitive Edge 111
4.1 Data Networks, IP Addresses, and APIs 113
4.2 Wireless Networks and Mobile Infrastructure 123
4.3 Collaboration and Communication Technologies 127
4.4 Sustainability and Ethical Issues 130
Case 4.2, Business Case: Google Maps API for Business 139

Case 4.3, Video Case: Fresh Direct Connects for Success 140
5 Cybersecurity and Risk Management 141
Case 5.1, Opening Case: BlackPOS Malware Steals Target’s
Customer Data 142
5.1 The Face and Future of Cyberthreats 144
5.2 Cyber Risk Management 152
5.3 Mobile, App, and Cloud Security 163
5.4 Defending Against Fraud 166
5.5 Compliance and Internal Control 169
Case 5.2, Business Case: Lax Security at LinkedIn Exposed 177
Case 5.3, Video Case: Botnets, Malware Security, and
Capturing
Cybercriminals 179
vii
Part 2
Winning, Engaging, and Retaining Consumers
with Technology
6 Attracting Buyers with Search, Semantic, and
Recommendation Technology 181
Case 6.1, Opening Case: Nike Golf Drives Web Traffic with
Search
Engine Optimization 182
6.1 Using Search Technology for Business Success 186
6.2 Organic Search and Search Engine Optimization 198
6.3 Pay-Per-Click and Paid Search Strategies 203
6.4 A Search for Meaning—Semantic Technology 205
6.5 Recommendation Engines 209
Case 6.2, Business Case: Recommending Wine to Online

Customers 217
Case 6.3, Video Case: Power Searching with Google 218
7 Social Networking, Engagement, and Social
Metrics 221
Case 7.1, Opening Case: The Connected Generation Influences
Banking Strategy 222
7.1 Web 2.0—The Social Web 225
7.2 Social Networking Services and Communities 235
7.3 Engaging Consumers with Blogs and
Microblogs 245
7.4 Mashups, Social Metrics, and Monitoring
Tools 250
7.5 Knowledge Sharing in the Social
Workplace 255
Case 7.2, Business Case: Social Customer Service 259
Case 7.3, Video Case: Viral Marketing: Will It Blend? 261
FMTOC.indd Page vii 18/11/14 2:20 PM f-391
8 Retail, E-commerce, and Mobile Commerce
Technology 264
Case 8.1, Opening Case: Macy’s Races Ahead with Mobile
Retail
Strategies 265
8.1 Retailing Technology 268
8.2 Business to Consumer (B2C) E-commerce 271
8.3 Business to Business (B2B) E-commerce and
E-procurement 277
8.4 Mobile Commerce 279
8.5 Mobile Transactions and Financial Services 286
Case 8.2, Business Case: Chegg’s Mobile Strategy 293
Case 8.3, Video Case: Searching with Pictures Using MVS 294

11.4 Geospatial Data and Geographic Information
Systems 384
Case 11.2, Visualization Case: Are You Ready for Football?
387
Case 11.3, Video Case: The Beauty of Data Visualization 387
viii Contents
Part 3
Optimizing Performance with Enterprise
Systems and Analytics
9 Effective and Efficient Business Functions 297
Case 9.1, Opening Case: Ducati Redesigns Its Operations 299
9.1 Solving Business Challenges at All Management
Levels 302
9.2 Manufacturing, Production, and Transportation
Management Systems 306
9.3 Sales and Marketing Systems 312
9.4 Accounting, Finance, and Regulatory Systems 315
9.5 Human Resources Systems, Compliance,
and Ethics 323
Case 9.2, Business Case: HSBC Combats Fraud in Split-second
Decisions 329
Case 9.3, Video Case: United Rentals Optimizes Its Workforce
with
Human Capital Management 330
10 Strategic Technology and Enterprise
Systems 331
Case 10.1, Opening Case: Strategic Technology Trend—
3D Printing 332
10.1 Enterprise Systems 337
10.2 Enterprise Social Platforms 341
10.3 Enterprise Resource Planning Systems 346

10.4 Supply Chain Management Systems 352
10.5 Customer Relationship Management Systems 358
Case 10.2, Business Case: Avon’s Failed SAP Implementation:
Enterprise System Gone Wrong 364
Case 10.3, Video Case: Procter & Gamble: Creating
Conversations
in the Cloud with 4.8 Billion Consumers 365
11 Data Visualization and Geographic Information
Systems 367
Case 11.1, Opening Case: Safeway and PepsiCo Apply Data
Visualization to Supply Chain 369
11.1 Data Visualization and Learning 371
11.2 Enterprise Data Mashups 377
11.3 Digital Dashboards 380
Part 4
Managing Business Relationships, Projects,
and Codes of Ethics
12 IT Strategy and Balanced Scorecard 389
Case 12.1, Opening Case: Intel’s IT Strategic Planning
Process 390
12.1 IT Strategy and the Strategic Planning
Process 392
12.2 Aligning IT with Business Strategy 397
12.3 Balanced Scorecard 400
12.4 IT Sourcing and Cloud Strategy 403
Case 12.2, Business Case: AstraZeneca Terminates $1.4B
Outsourcing Contract with IBM 409
Case 12.3, Data Analysis: Third-Party versus Company-Owned
Offshoring 410
13 Project Management and SDLC 412
Case 13.1, Opening Case: Keeping Your Project on Track,
Knowing

When It Is Doomed, and DIA Baggage System Failure 413
13.1 Project Management Concepts 417
13.2 Project Planning, Execution, and Budget 421
13.3 Project Monitoring, Control, and Closing 428
13.4 System Development Life Cycle 432
Case 13.2, Business Case: Steve Jobs’ Shared Vision Project
Management Style 436
Case 13.3, Demo Case: Mavenlink Project Management and
Planning Software 437
14 Ethical Risks and Responsibilities of IT
Innovations 438
Case 14.1, Opening Case: Google Glass and Risk, Privacy, and
Piracy Challenges 439
14.1 Privacy Paradox, Privacy, and Civil Rights 442
14.2 Responsible Conduct 448
14.3 Technology Addictions and the Emerging Trend of
Focus Management 453
14.4 Six Technology Trends Transforming Business 454
Case 14.2, Business Case: Apple’s CarPlay Gets
Intelligent 458
Case 14.3, Video Case: Vehicle-to-Vehicle Technology to
Prevent
Collisions 459
Glossary G-1
Organizational Index O-1
Name Index N-1
Subject Index S-1
FMTOC.indd Page viii 18/11/14 2:20 PM f-391

Business strategy and operations are driven by data, digi-
tal technologies, and devices. Five years from now, we will
look back upon today as the start of a new era in business
and technology. Just like the way e-business started with
the emergence of the Web, this new era is created by the
convergence of social, mobile, big data, analytics, cloud,
sensor, software-as-a-service, and data visualization tech-
nologies. These technologies enable real-time insights,
business decisions, and actions. Examples of how they
determine tomorrow’s business outcomes are:
• Insight. Combining the latest capabilities in big
data analytics, reporting, collaboration, search, and
machine-to-machine (M2M) communication helps
enterprises build an agility advantage, cut costs, and
achieve their visions.
• Action. Fully leveraging real-time data about opera-
tions, supply chains, and customers enables managers
to make decisions and take action in the moment.
• Sustainable performance. Deploying cloud services,
managing projects and sourcing agreements, respect-
ing privacy and the planet, and engaging customers
across channels are now fundamental to sustaining
business growth.
• Business optimization. Embedding digital capability
into products, services, machines, and business pro-
cesses optimizes business performance—and creates
strategic weapons.

In this tenth edition, students learn, explore, and analyze
the three dimensions of business performance improve-
ment: digital technology, business processes, and people.
What Is New in the Tenth
Edition—and Why It Matters
Most Relevant Content. Prior to and during the writing
process, we attended practitioner conferences and con-
sulted with managers who are hands-on users of leading
technologies, vendors, and IT professionals to learn about
their IT/business successes, challenges, experiences, and
recommendations. For example, during an in-person
interview with a Las Vegas pit boss, we learned how
real-time monitoring and data analytics recommend
the minimum bets in order to maximize revenue per
minute at gaming tables. Experts outlined opportunities
and strategies to leverage cloud services and big data
PREFACE
to capture customer loyalty and wallet share and justify
significant investments in leading IT.
More Project Management with Templates. In response
to reviewers’ requests, we have greatly increased cover-
age of project management and systems development
lifecycle (SDLC). Students are given templates for writing
a project business case, statement of work (SOW), and
work breakdown structure (WBS). Rarely covered, but
critical project management issues included in this edition
are project post-mortem, responsibility matrix, go/no go
decision factors, and the role of the user community.
New Technologies and Expanded Topics. New to this
edition are 3D printing and bioprinting, project portfolio
management, the privacy paradox, IPv6, outsource rela-

tionship management (ORM), and balanced scorecard.
With more purchases and transactions starting online
and attention being a scarce resource, students learn how
search, semantic, and recommendation technologies func-
tion to improve revenue. The value of Internet of Things
(IoT) has grown significantly as a result of the compound
impact of connecting people, processes, data, and things.
Easier to Grasp Concepts. A lot of effort went into mak-
ing learning easier and longer-lasting by outlining content
with models and text graphics for each opening case (our
version of infographics) as shown in Figure P-1—from the
Chapter 12 opening case.
Engaging Students to
Assure Learning
The tenth edition of Information Technology for
Management engages students with up-to-date cover-
age of the most important IT trends today. Over the
years, this IT textbook had distinguished itself with an
emphasis on illustrating the use of cutting edge business
technologies for achieving managerial goals and objec-
tives. The tenth edition continues this tradition with more
hands-on activities and analyses.
Each chapter contains numerous case studies and
real world examples illustrating how businesses increase
productivity, improve efficiency, enhance communica-
tion and collaboration, and gain a competitive edge
through the use of ITs. Faculty will appreciate a variety
of options for reinforcing student learning, that include
three Case Studies per chapter, including an opening
case, a business case and a video case.
ix
FMTOC.indd Page ix 18/11/14 2:20 PM f-391

x Preface
Throughout each chapter are various learning aids,
which include the following:
• Learning Outcomes are listed at the beginning of each
chapter to help students focus their efforts and alert
them to the important concepts that will be discussed.
• The Chapter Snapshot provides students with an over-
view of the chapter content.
• IT at Work boxes spotlight real-world cases and inno-
vative uses of IT.
• Definitions of Key Terms appear in the margins
throughout the book.
• Tech Note boxes explore topics such as “4G and
5G Networks in 2018” and “Data transfers to main-
frames.”
• Career Insight boxes highlight different jobs in the IT
for management field.
At the end of each chapter are a variety of features
designed to assure student learning:
• Critical Thinking Questions are designed to facilitate
student discussion.
• Online and Interactive Exercises encourage students

to explore additional topics.
• Analyze and Decide questions help students apply IT
concepts to business decisions.
Details of New and Enhanced
Features of the Tenth Edition
The textbook consists of fourteen chapters organized
into four parts. All chapters have new sections as well as
updated sections, as shown in Table P-1.
Strategic
directional
statements
Strategic
plan
gic
egic
2. Technology & Business Outlook. A team of
senior management, IT, and business unit
representatives develop the two-to-five-year
business outlook & technology outlook.
3. Current State Assessment & Gap Analysis.
Analysis of the current state of IT, enterprise
systems, & processes, which are compared with
results of step 2 to identify gaps and necessary
adjustments to IT investment plans.
4. Strategic Imperatives, Strategies, & Budget for
Next Year. Develop next year’s priorities, road

map, budget, & investment plan. Annual budget
approved.
5. Governance Decisions & IT Road Map. The
budget guides the governance process, including
supplier selection and sourcing.
6. Balanced Scorecard Reviews.
Performance is measured monthly.
1. Enterprise Vision. Senior management &
leaders develop & communicate the enterprise’s
two-to-five-year strategic vision & mission and
identify the direction & focus for upcoming year.
Figure P-1 Model of Intel’s
6-step IT strategic planning
process, from Chapter 12.
FMTOC.indd Page x 18/11/14 2:20 PM f-391
Preface xi
TABLE P-1 Overview of New and Expanded IT Topics and
Innovative Enterprises Discussed
in the Chapters
Chapter New and Expanded IT and Business Topics
Enterprises in a Wide
Range of Industries
1: Doing Business in
Digital Times

• Era of Mobile-Social-Cloud-Big Data
• Digital connectivity and convergence
• Internet of Things (IoT), or machine-to-machine
(M2M) technology
• Farm-to-fork traceability
• Business process management
• Near-fi eld communication (NFC)
• McCain Foods Ltd
• Zipcar
• Pei Wei Asian Diner
• Teradata
2: Data Governance and
IT Architecture Support
Long-Term Performance
• Data governance and quality
• Master data management (MDM)
• Cloud services
• Collaboration
• Virtualization and business continuity
• software-, platform-, infrastructure-, and data-
as-a-service
• Intel Security
• Liberty Wines
• Unilever
• Vanderbilt University
Medical Center
3: Data Management,

Big Data Analytics and
Records Management
• Big data analytics and machine-generated data
• Business intelligence (BI)
• Hadoop
• NoSQL systems
• Active data warehouse apps
• Compliance
• Coca-Cola
• Hertz
• First Wind
• Argo Corp.
• Wal-Mart
• McDonalds
• Infi nity Insurance
• Quicken Loans, Inc.
• U.S. military
• CarMax
4: Networks for Effi cient
Operations and Sustain-
ability
• IPv6
• API
• 4G and 5G networks
• Net neutrality
• Location-aware technologies
• Climate change
• Mobile infrastructure
• Sustainable development
• Sony
• Google Maps

• Fresh Direct
• Apple
• Spotify
• Caterpillar, Inc.
5: Cyber Security and
Risk Management
• BYOD and social risks
• Advanced persistent threats (APT), malware,
and botnets
• IT governance
• Cloud security
• Fraud detection and prevention
• Target
• LinkedIn
• Boeing
6: Attracting Buyers with
Search, Semantic and
Recommendation
Technology
• Search technology
• Search engine optimization (SEO)
• Google Analytics
• Paid search strategies
• Nike
• Netfl ix
• Wine.com
(continued)

FMTOC.indd Page xi 18/11/14 2:20 PM f-391
xii Preface
in the Chapters (continued)
Range of Industries
7: Social Networking,
Engagement and Social
Metrics
• Social network services (SNS)
• Web 2.0 tools for business collaboration
• Crowdfunding
• Privacy
• Citibank
• American Express
• Facebook
• Twitter
• Cisco
8: Retail, E-commerce
and Mobile Commerce
Technology
• Innovation in traditional and web-based retail
• Omni-channel retailing

• Visual search
• Mobile payment systems
• Macys
• Chegg
• Amazon
9: Effective and Effi cient
Business Functions
• Customer experience (CX)
• eXtensible Business Reporting Language
(XBRL)
• Order fulfi llment process
• Transportation management systems
• Computer-integrated manufacturing (CIM)
• SaaS
• TQM
• Auditing information systems
• Ducati Motor Holding
• HSBC
• SAS
• United Rentals
• First Choice Ski
10: Strategic Technology
and Enterprise Systems
• 3D printing, additive manufacturing
• Enterprise social platforms
• Yammer, SharePoint, and Microsoft Cloud
• Avon
• Procter & Gamble

• Organic Valley Family
of Farms
• Red Robin Gourmet
Burgers, Inc.
• Salesforce.com
• Food and Drug Administra-
tion (FDA)
• U.S. Army Materiel
Command (AMC)
• 1-800-Flowers
11: Data Visualization
and Geographic Informa-
tion Systems
• Data visualization
• Mobile dashboards
• Geospatial data and geocoding
• Geographic Information Systems (GIS)
• Supply chain visibility
• Reporting tools; analytical tools
• Self-service mashup capabilities
• Safeway
• PepsiCo
• eBay
• Tableau
• Hartford Hospital
• General Motors (GM)
12: IT Strategy and
Balanced Scorecard

• IT strategic planning process
• Value drivers
• Outsource relationship management (ORM)
• Service level agreements (SLAs)
• Outsourcing lifecycle
• Applications portfolio
• Intel
• AstraZeneca
• IBM
• Commonwealth Bank of
Australia (CBA)
(continued)
FMTOC.indd Page xii 18/11/14 2:20 PM f-391
Preface xiii
in the Chapters (continued)
Range of Industries
13: Project Management
and SDLC
• Project management lifecycle

• Project Portfolio Management (PPM)
• Project business case
• Project business case, statement of work (SOW),
work breakdown structure (WBS), milestone
schedule, and Gantt chart
• Triple constraint
• Critical path
• Systems feasibility studies
• Denver International
Airport
• U.S. Census
• Mavenlink Project
Management and Planning
Software
14: Ethical Risks and
Responsibilities of IT
Innovations
• Privacy paradox
• Social recruitment and discrimination
• Responsible conduct
• Vehicle-to-vehicle (V2V) technology
• Ethics of 3D printing and bioprinting
• Tech addictions
• Tech trends
• Google Glass
• Apple’s CarPlay
• SnapChat
• Target

Supplementary Materials
An extensive package of instructional materials is avail-
able to support this tenth edition. These materials are
accessible from the book companion Web site at www.
wiley.com/college/turban.
• Instructor’s Manual. The Instructor’s Manual presents
objectives from the text with additional information
to make them more appropriate and useful for the
instructor. The manual also includes practical applica-
tions of concepts, case study elaboration, answers to
end-of-chapter questions, questions for review, ques-
tions for discussion, and Internet exercises.
• Test Bank. The test bank contains over 1,000 ques-
tions and problems (about 75 per chapter) consisting
of multiple-choice, short answer, fill-ins, and critical
thinking/essay questions.
• Respondus Test Bank. This electronic test bank is
a powerful tool for creating and managing exams
that can be printed on paper or published directly
to Blackboard, ANGEL, Desire2Learn, Moodle, and
other learning systems. Exams can be created offline
using a familiar Windows environment, or moved from
one LMS to another.
• PowerPoint Presentation. A series of slides designed
around the content of the text incorporates key points
from the text and illustrations where appropriate.
E-book
Wiley E-Textbooks offer students the complete content of
the printed textbook on the device of their preference—
computer, iPad, tablet, or smartphone—giving students

the freedom to read or study anytime, anywhere. Students
can search across content, take notes, and highlight key
materials. For more information, go to www.wiley.com/
college/turban.
Acknowledgments
Many individuals participated in focus groups or review-
ers. Our sincere thanks to the following reviewers of the
tenth edition who provided valuable feedback, insights,
and suggestions that improved the quality of this text:
Joni Adkins, Northwest Missouri State University
Ahmad Al-Omari, Dakota State University
Rigoberto Chinchilla, Eastern Illinois University
Michael Donahue, Towson University
Samuel Elko, Seton Hill University
Robert Goble, Dallas Baptist University
Eileen Griffin, Canisius College
Binshan Lin, Louisiana State University in Shreveport
Thomas MacMullen, Eastern Illinois University
James Moore, Canisius College
Beverly S. Motich, Messiah College
FMTOC.indd Page xiii 18/11/14 2:20 PM f-391
http://www.wiley.com/college/turban
xiv Preface
Barin Nag, Towson University
Luis A. Otero, Inter-American University of Puerto

Rico, Metropolitan Campus
John Pearson, Southern Illinois University
Daniel Riding, Florida Institute of Technology
Josie Schneider, Columbia Southern University
Derek Sedlack, South University
Eric Weinstein, The University of La Verne
Patricia White, Columbia Southern University
Gene A. Wright, University of Wisconsin–Milwaukee
We are very thankful to our assistants, Samantha
Palisano and Olena Azarova. Samantha devoted many
hours of research, provided clerical support, and con-
tributed to the writing of Chapter 6. Olena assisted with
research and development of graphics for Chapter 7.
We are fortunate and thankful for the expert and encour-
aging leadership of Margaret Barrett, Beth Golub, Ellen
Keohane, and Mary O’Sullivan. To them we extend our
sincere thanks for your guidance, patience, humor, and
support during the development of this most recent ver-
sion of the book. Finally, we wish to thank our families
and colleagues for their encouragement, support, and
understanding as we dedicated time and effort to cre-
ating this new edition of Information Technology for
Management.
Linda Volonino
Greg Wood
FMTOC.indd Page xiv 18/11/14 2:20 PM f-391
Chapter Snapshot

Make no mistake. Businesses are experiencing a digital
transformation as digital technology enables changes
unimaginable a decade ago. High-performance organi-
zations are taking advantage of what is newly possible
from innovations in mobile, social, cloud, big data, data
analytics, and visualization technologies. These digital
forces enable unprecedented levels of connectivity, or
connectedness, as listed in Figure 1.1.
Think how much of your day you have your phone
nearby—and how many times you check it. Nearly
80 percent of people carry their phone for all but two
hours of their day; and 25 per cent of 18- to 44-year-olds
cannot remember not having their phone with them
(Cooper, 2013).
As a business leader, you will want to know what
steps to take to get a jump on the mobile, social, cloud,
Doing Business
in Digital Times1
Chapter
1. Describe the use of digital technology in every facet of
business and how digital channels are being leveraged.
2. Explain the types, sources, characteristics, and control
of enterprise data, and what can be accomplished with
near real time data.
3. Identify the five forces of competitive advantage and
evaluate how they are reinforced by IT.
4. Describe enterprise technology trends and explain how
they influence strategy and operations.

5. Assess how IT adds value to your career path and per-
formance, and the positive outlook for IT management
careers.
Learning Outcomes
1
Digital Technology Trends Transforming
How Business Is DonePart 1
Chapter Snapshot
Case 1.1 Opening Case: McCain Foods’ Success
Factors—Dashboards, Innovation, and Ethics
1.1 Every Business Is a Digital Business
1.2 Business Process Management and
Improvement
1.3 The Power of Competitive Advantage
1.4 Enterprise Technology Trends
1.5 How Your IT Expertise Adds Value to Your
Performance and Career
Key Terms
Assuring Your Learning
• Discuss: Critical Thinking Questions
• Explore: Online and Interactive Exercises
• Analyze & Decide: Apply IT Concepts
to Business Decisions

Case 1.2 Business Case: Restaurant Creates
Opportunities to Engage Customers
Case 1.3 Video Case: What Is the Value of
Knowing More and Doing More?
References
c01DoingBusinessinDigitalTimes.indd Page 1 11/3/14 7:31
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big data, analytics, and visualization technologies that will
move your businesses
forward. Faced with opportunities and challenges, you need to
know how to lever-
age them before or better than your competitors.
In this opening chapter, you read about the powerful impacts of
digital technol-
ogy on management, business, government, entertainment,
society, and those it will
have on the future. You learn of the latest digital trends taking
place across indus-
tries and organizations—small and medium businesses,
multinational corporations,
government agencies, the health-care industry, and nonprofits.
Big data are datasets whose
size and speed are beyond
the ability of typical database
software tools to capture,
store, manage, and analyze.
Examples are machine-
generated data and social

media texts.
Data analytics refers to the
use of software and statistics
to find meaningful insight
in the data, or better under-
stand the data.
Data visualization (viz) tools
make it easier to understand
data at a glance by display-
ing data in summarized
formats, such as dashboards
and maps, and by enabling
drill-down to the detailed
data.
Figure 1.1 We are in
the era of mobile-social-
cloud-big data that
shape business strate-
gies and day-to-day
operations.
CASE 1.1 OPENING CASE
McCain Foods’ Success Factors: Dashboards, Innovation, and
Ethics
COMPANY OVERVIEW You most likely have eaten McCain
Foods products (Figure 1.2, Table 1.1). McCain
is a market leader in the frozen food industry—producing one-
third of the world’s
supply of french fries. The company manufactures, distributes,
and sells more than
Figure 1.2 McCain Foods,

Ltd. overview.
2
An estimated 15 billion
devices are connected to
the Internet—forecasted
to hit 50 billion by 2020
as more devices connect
via mobile networks.
Over 1 million websites
engage in Facebook
e-commerce.
Over 200 million social
media users are mobile
only, never accessing it
from a desktop or laptop.
Mobile use generates 30%
of Facebook’s ad revenue.
More data are collected in
a day now than existed in
the world 10 years ago.
Half of all data are in the
cloud and generated
by mobile and social
activities—known as big
data.
Sales offices in 110 countries
55 production plants on
6 continents

22,000 employees
Global Reach
Good ethics is good
business.
Good food, better life.
Corporate Culture
Dashboards
Data analytics
Real time reporting systems
Digital Technology
Frozen food manufacturer
Market leader in french
fries
Brand
McCain Foods, Ltd.
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CASE 1.1 Opening Case 3
TABLE 1.1 Opening Case Overview

Company McCain Foods, Ltd. www.mccain.com
Industry The global company manufactures, sells, and
distributes frozen
food products.
Product lines More than 100 oven-ready frozen food products
Digital technology Dashboards are implemented throughout the
organization
from boardrooms to factory fl oors. Dashboards have drill-down
capabilities.
Business challenges The frozen food industry faced tough
challenges from health
and nutrition trends that are emphasizing fresh foods. Industry
is highly competitive because it is expected to experience slow
growth through 2018.
Taglines “Good food. Better life.” and “It’s all good.”
Figure 1.3 Frozen food is
one of the most dynamic
and largest sectors of the
food industry.
100 oven-ready frozen foods—pizzas, appetizers, meals, and
vegetables. McCain is
a global business-to-business (B2B) manufacturer with 55
production facilities on 6
continents. The company sells frozen foods to other
businesses—wholesalers, retail-
ers, and restaurants from sales offices in 110 countries. McCain
supplies frozen fries
to Burger King and supermarket chains (Figure 1.3).

Business-to-business (B2B)
commerce. The selling of
products and services to
other businesses.
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4 Chapter 1 Doing Business in Digital Times
Food manufacturers must be able to trace all ingredients along
their supply
chain in case of contamination. Achieving end-to-end
traceability is complex given

the number of players in food supply chains. Several
communication and tracking
technologies make up McCain’s supply chain management
(SCM) system to keep
workers informed of actual and potential problems with food
quality, inventory,
and shipping as they occur. McCain’s SCM system ensures
delivery of the best
products possible at the best value to customers. In addition, the
company strives
to prevent food shortages worldwide by analyzing huge volumes
of data to predict
crop yields.
Supply chain. All businesses
involved in the production
and distribution of a product
or service.
FROZEN FOOD
INDUSTRY CHALLENGES
McCain Foods had to deal with three major challenges and
threats:
1. Drop in demand for frozen foods. McCain operated in an
industry that was
facing tougher competition. Health-conscious trends were
shifting customer
demand toward fresh food, which was slowing growth in the
frozen foods
market.
2. Perishable inventory. Of all the types of manufacturing, food
manufacturers face
unique inventory management challenges and regulatory

requirements. Their
inventory of raw materials and fi nished goods can spoil, losing
all their value, or
food can become contaminated. Regulators require food
manufacturers to able
to do recalls quickly and effectively. Food recalls have
destroyed brands and
been fi nancially devastating.
3. Technology-dependent. Food manufacturers face the
pressures that are
common to all manufacturers. They need information reporting
systems and
digital devices to manage and automate operations, track
inventory, keep
the right people informed, support decisions, and collaborate
with business
partners.
McCain Foods worked with Burger King (BK) to develop lower-
calorie fries
called Satisfries (Figure 1.4). These crinkle-cut fries have 30
percent less fat and
20 percent fewer calories than BK’s classic fries. This food
innovation has shaken
up the fast-food industry and given BK an advantage with end-
consumers who are
demanding healthier options.
Figure 1.4 McCain Foods
and Burger King jointly
developed Satisfries—a
french fry innovation with
30 percent less fat and
20 percent fewer calories
than BK’s current fries and

40 percent less fat and
30 percent fewer calories
than McDonald’s fries.
MCCAIN FOODS’
BUSINESS AND IT
STRATEGIES
The McCain brothers, who founded the company, follow this
simple philosophy:
“Good ethics is good business.” McCain prides itself on the
quality and conve-
nience of its products, which is reflected in the It’s All Good
brand image. The It’s
All Good branding effort was launched in 2010 after surveys
found that customers
were concerned about the quality and nutrition of frozen foods.
Since then, many of
products have been improved and manufactured in healthier
versions.
Managing with Digital Technology McCain had integrated its
diverse
sources of data into a single environment for analysis. Insights
gained from its data
analytics helped improve manufacturing processes, innovation,
and competitive
advantage.
McCain Foods invested in data analytics and visualization
technologies to
maximize its capability to innovate and gain insights from its
huge volumes of data.
The company tracks, aggregates, and analyzes data from
operations and business
customers in order to identify opportunities for innovation in

every area of the busi-
ness. The results of data analytics are made available across the
organization—from
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Figure 1.5 Data visualizations
of KPIs make them easy to
understand at a glance.
executive boardrooms to the factory floors—on dashboards.

Dashboards are data
visualizations (data viz) that display the current status of key
performance indica-
tors (KPIs) in easy-to-understand formats (Figure 1.5). KPIs are
business metrics
used to evaluate performance in terms of critical success
factors, or strategic and
operational goals.
Dashboards Create Productive Competition Among Factory
Workers
McCain implemented 22,000 reports and 3,000 personal
reporting systems that
include dashboards. Dashboards display summarized data
graphically in a clear and
concise way. By clicking a graph, the user can drill down to the
detailed data. The
dashboards reach most of McCain’s 18,000 employees
worldwide.
Dashboards have created healthy competition that has led to
better perfor-
mance. Ten-foot dashboards hang on factory walls of plants
around the world. They
are strategically placed near the cafeteria so employees can see
the KPIs and per-
formance metrics of every plant. With this visibility, everyone
can know in near real
time exactly how well they are doing compared to other plants.
The competition
among factories has totally transformed the work environment—
and organizational
culture—in the plants and increased production performance.
Better Predictions, Better Results The CEO, other executives,
and managers

view their dashboards from mobile devices or computers. They
are able to monitor
operations in factories and farms around the globe. Dashboards
keep management
informed because they can discover answers to their own
questions by drilling
down. Data are used to forecast and predict crop yields—and
ultimately combine
weather and geopolitical data to predict and avoid food
shortages. By integrating
all of its data into one environment and making the results
available in near real
time to those who need it, the organization is increasing its
bottom line and driving
innovation.
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Questions
1. All it takes is one compromised ingredient to contaminate
food and
to put human lives at risk. Delays in communicating
contaminated food
increase the health risk and fi nes for violating the Food Safety
Mod-
ernization Act. How can the SCM system help McCain Foods
reduce
the risks related to low-quality or contaminated frozen foods
reaching
consumers?
2. What three challenges or threats facing McCain Foods and
what is the
reason for each challenge or threat?
3. How have dashboards on the factory fl oors impacted
performance at
McCain Foods?
4. What might be the KPIs of a frozen food manufacturer such
as McCain
Foods?
5. Explain how visibility about operations and performance
created
healthy competition among McCain’s factory workers.
6. Being able to make reliable predictions can improve business

perfor-
mance. Explain why.
Sources: Compiled from Smith (2013), Transparency Market
Research (2013), and McCain Foods
Teradata video (2013).
Digital business is a social,
mobile, and Web-focused
business.
Business model is how a
business makes money.
Digital business model
defines how a business
makes money digitally.
Customer experience (CX)
is about building the digital
infrastructure that allows cus-
tomers to do whatever they
want to do, through whatever
channel they choose to do it.
Today, a top concern of well-established corporations, global
financial institutions,
born-on-the-Web retailers, and government agencies is how to
design their digital
business models in order to:
• deliver an incredible customer experience;
• turn a profit;
• increase market share; and

• engage their employees.
In the digital (online) space, the customer experience (CX) must
measure up
to the very best the Web has to offer. Stakes are high for those
who get it right—or
get it wrong. Forrester research repeatedly confirms there is a
strong relationship
between the quality of a firm’s CX and loyalty, which in turn
increases revenue
(Schmidt-Subramanian et al., 2013).
This section introduces the most disruptive and valuable digital
technologies,
which you will continue to read about throughout this book.
1.1 Every Business Is a Digital Business
DIGITAL TECHNOLOGIES
OF THE 2010S—IN THE
CLOUD, HANDHELD,
AND WEARABLE
Consumers expect to interact with businesses anytime anywhere
via mobile
apps or social channels using technology they carry in their
pockets. Mobile apps
have changed how, when, and where work is done. Employees
can be more produc-
tive when they work and collaborate effortlessly from their
handheld or wearable
devices.
Cloud Computing
Enterprises can acquire the latest apps and digital services as

they are needed and
without large upfront investments by switching from owning IT
resources to cloud
computing (Figure 1.6). Cloud computing ranges from storing
your files in Dropbox
to advanced cloud services. In short, with the cloud, resources
no longer depend
on buying that resource. For example, Amazon Elastic Compute
Cloud, known as
Cloud computing is a style
of computing in which IT
services are delivered on-
demand and accessible via
the Internet. Common exam-
ples are Dropbox, Gmail,
and Google Drive.
Food Safety Modernization
Act (FSMA), signed into law
in early 2011, requires all
companies in food supply
chains to be able to trace
foods back to the point of
origin (farm) and forward to
the consumer’s plate (fork).
The term for the effort is
farm-to-fork traceability.
Public health is the chief con-
cern, followed by potential
liability and brand protection
issues.
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Figure 1.6 Cloud computing is an important evolution in data
storage, software, apps, and
delivery of IT services. An example is Apple iCloud—a cloud
service used for online storage and
synchronization of mail, media fi les, contacts, calendar, and
more.
EC2, eliminates the need to invest in hardware up front, so
companies can develop
and deploy applications faster. EC2 enables companies to
quickly add storage
capacity as their computing requirements change. EC2 reduces
the time it takes to
acquire server space from weeks to minutes.
Machine-to-Machine Technology
Sensors can be embedded in most products. Objects that connect
themselves to
the Internet include cars, heart monitors, stoplights, and
appliances. Sensors are
designed to detect and react, such as Ford’s rain-sensing front
wipers that use
an advanced optical sensor to detect the intensity of rain or
snowfall and adjust
wiper speed accordingly. Machine-to-machine (M2M)
technology enables sensor-
embedded products to share reliable real time data via radio
signals. M2M and
the Internet of Things (IoT) are widely used to automate
business processes in
industries ranging from transportation to health care. By adding

sensors to trucks,
turbines, roadways, utility meters, heart monitors, vending
machines, and other
equipment they sell, companies can track and manage their
products remotely.
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Internet of things (IoT)
refers to a set of capabilities
enabled when physical things
are connected to the Internet
via sensors.
TECH NOTE 1.1 The Internet of Things
The phrase Internet of Things was coined by Kevin Ashton in
1999 while he was em-
ployed at Procter & Gamble. It refers to objects (e.g., cars,
refrigerators, roadways)
that can sense aspects of the physical world, such as movement,
temperature, light-
ing, or the presence or absence of people or objects, and then
either act on it or re-
port it. Instead of most data (text, audio, video) on the Internet
being produced and
used by people, more data are generated and used by machines
communicating with
other machines—or M2M, as you read at the start of this
chapter. Smart devices use
IP addresses and Internet technologies like Wi-Fi to
communicate with each other
or directly with the cloud. Recent advances in storage and
computing power avail-
able via cloud computing are facilitating adoption of the IoT.

The IoT opens new frontiers for improving processes in retail,
health care,
manufacturing, energy, and oil and gas exploration. For
instance, manufacturing
processes with embedded sensors can be controlled more
precisely or monitored
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Big Data
There is no question that the increasing volume of data can be
valuable, but only if
they are processed and available when and where they are
needed. The problem is
that the amount, variety, structure, and speed of data being
generated or collected
by enterprises differ significantly from traditional data. Big
data are what high-
volume, mostly text data are called. Big data stream in from
multiple channels and
sources, including:
• mobile devices and M2M sensors embedded in everything
from airport
runways to casino chips. Later in this chapter, you will read
more about the
Internet of Things.
• social content from texts, tweets, posts, blogs.

• clickstream data from the Web and Internet searches.
• video data and photos from retail and user-generated content.
• financial, medical, research, customer, and B2B transactions.
Big data are 80 to 90 per cent unstructured. Unstructured data
do not have a pre-
dictable format like a credit card application form. Huge
volumes of unstructured data
flooding into an enterprise are too much for traditional
technology to process and ana-
lyze quickly. Big data tend to be more time-sensitive than
traditional (or small) data.
The exploding field of big data and analytics is called data
science. Data sci-
ence involves managing and analyzing massive sets of data for
purposes such as
target marketing, trend analysis, and the creation of individually
tailored products
and services. Enterprises that want to take advantage of big data
use real time data
from tweets, sensors, and their big data sources to gain insights
into their custom-
ers’ interests and preference, to create new products and
services, and to respond
to changes in usage patterns as they occur. Big data analytics
has increased the
demand for data scientists, as described in Career Insight 1.1.
for hazards and then take corrective action, which reduces
injuries, damage, and
costs. IoT combined with big data analytics can help
manufacturers improve the
effi ciency of their machinery and minimize energy

consumption, which often is the
manufacturing industry’s second-biggest expense.
The health sector is another area where IoT can help signifi
cantly. For example,
a person with a wearable device that carries all records of his
health could be monitored
constantly. This connectivity enables health services to take
necessary measures for
maintaining the wellbeing of the person.
Data Scientist
Big data, analytics tools, powerful networks, and greater
processing power have contributed to growth of the
field of data science. Enterprises need people who are
capable of analyzing and finding insights in data cap-
tured from sensors, M2M apps, social media, wearable
technology, medical testing, and so on. Demand for data
scientists is outpacing the supply of talent. It is projected
that the data scientist career option will grow 19 per
cent by 2020—surpassed only by video game design-
ers. Talent scarcity has driven up salaries. According to
CAREER INSIGHT 1 . 1 HOT CAREER
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Glassdoor data (glassdoor.com, 2014), the median salary
for data scientists in the United States is $117,500. By

contrast, a business analyst earns an average of $61,000.
Profiles of Data Scientists at Facebook, LinkedIn,
and Bitly
• Facebook’s Jeff Hammerbacher. Jeff helped
Facebook make sense out of huge volumes of user
data when he joined the company in 2006. Facebook’s
data science team analyzes the self-reported data on
each user’s Facebook page in order to target ads
based on things the user actually likes.
• LinkedIn’s DJ Patil. DJ worked at LinkedIn as
chief data scientist. Many of the cool products on
LinkedIn were built using data from self-reporting
and machine learning.
• Bitly’s Hilary Mason. Hilary was chief scientist at
Bitly, which offers URL shortening and redirec-
tion services with real time link tracking. Bitly sees
behavior from billions of people a month by analyz-
ing tens of millions of links shared per day, which are
clicked hundreds of millions times. The clickstreams
generate an enormous amount of real time data.
Using data analytics, Hillary and her team detected
and solved business problems that were not evident.
Data Science Is Both an Art and a Science
In their 2012 Harvard Business Review article titled
“Data Scientist: The Sexiest Job of the 21st Century,”
authors Thomas Davenport and D. J. Patil define a data
scientist as a “high-ranking professional with the train-
ing and curiosity to make discoveries in the world of big
data” (Davenport & Patil, 2012). They described how
data scientist Jonathan Goldman transformed LinkedIn

after joining the company in 2006. At that time, LinkedIn
had less than 8 million members. Goldman noticed that
existing members were inviting their friends and col-
leagues to join, but they were not making connections
with other members at the rate executives had expected.
A LinkedIn manager said, “It was like arriving at a con-
ference reception and realizing you don’t know anyone.
So you just stand in the corner sipping your drink—and
you probably leave early.” Goldman began analyzing
the data from user profiles and looked for patterns that
to predict whose networks a given profile would land
in. While most LinkedIn managers saw no value in
Goldman’s work, Reid Hoffman, LinkedIn’s cofounder
and CEO at the time, understood the power of analytics
because of his experiences at PayPal. With Hoffman’s
approval, Goldman applied data analytics to test what
would happen if member were presented with names
of other members they had not yet connected with, but
seemed likely to know. He displayed the three best new
matches for each member based on his or her LinkedIn
profile. Within days, the click-through rate on those
matches skyrocketed and things really took off. Thanks
to this one feature, LinkedIn’s growth increased dra-
matically.
The LinkedIn example shows that good data sci-
entists do much more than simply try to solve obvious
business problems. Creative and critical thinking are
part of their job—that is, part analyst and part artist.
They dig through incoming data with the goal of dis-
covering previously hidden insights that could lead to
a competitive advantage or detect a business crisis in
enough time to prevent it. Data scientists often need
to evaluate and select those opportunities and threats
that would be of greatest value to the enterprise or

brand.
Sources: Kelly (2013), Lockhard & Wolf (2012), Davenport &
Patil (2012), U.S. Department of Labor, Bureau of Labor
Statistics (2014).
SOCIAL-MOBILE-CLOUD
MODEL
The relationship among social, mobile, and cloud technologies
is shown in
Figure 1.7. The cloud consists of huge data centers accessible
via the Internet and
forms the core by providing 24/7 access to storage, apps, and
services. Handhelds
and wearables, such as Google Glass, Pebble, and Sony
Smartwatch (Figure 1.8),
and their users form the edge. Social channels connect the core
and edge. The
SoMoClo integration creates the technical and services
infrastructure needed for
digital business. This infrastructure makes it possible to meet
the expectations of
employees, customers, and business partners given that almost
everyone is con-
nected (social), everywhere they go (mobile), and has 24/7
access to data, apps, and
other services (cloud).
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Here are three examples of their influence:
1. Powerful social infl uences impact advertising and
marketing: Connections and
feedback via social networks have changed the balance of infl
uence. Consum-
ers are more likely to trust tweets from ordinary people than
recommendations
made by celebrity endorsements. And, negative sentiments
posted or tweeted
can damage brands.
2. Consumer devices go digital and offer new services. The
Nike Fuel-
band wristband helps customers track their exercise activities
and calories
burned. The device links to a mobile app that lets users post
their progress
on Facebook.
3. eBay’s move to cloud technology improves sellers’ and
buyers’ experiences.
The world’s largest online marketplace, eBay, moved its IT
infrastructure to the
cloud. With cloud computing, eBay is able to introduce new
types of landing
pages and customer experiences without the delay associated
with having to buy
additional computing resources.
The balance of power has shifted as business is increasingly
driven by individu-
als for whom mobiles are an extension of their body and mind.
They expect to use
location-aware services, apps, alerts, social networks, and the
latest digital capabili-

ties at work and outside work. To a growing extent, customer
loyalty and revenue
growth depend on a business’s ability to offer unique customer
experiences that
wow customers more than competitors can.
Figure 1.7 Model of the
integration of cloud, mobile,
and social technologies. The
cloud forms the core. Mobile
devices are the endpoints.
Social networks create the
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Figure 1.8 Strong interest in
smart wearable technology
refl ects growing consumer
desire to be more digitally
connected at all times using
a collection of multiple
devices. A smartwatch used
at work, such as in a retail
store, can provide shop fl oor
staff with a screen to check
stock availability.
DIGITAL BUSINESS
MODELS
Business models are the ways enterprises generate revenue or
sustain themselves.
Digital business models define how businesses make money via
digital technology.
Companies that adopt digital business models are better
positioned to take advan-
tage of business opportunities and survive, according to the
Accenture Technology
Vision 2013 report (Accenture, 2013). Figure 1.9 contains
examples of new tech-
nologies that destroyed old business models and created new
ones.
Figure 1.9 Digital business
models refer to how
companies engage their
customers digitally to
create value via websites,
social channels, and mobile
devices.

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Location-aware technologies
track items through
production and delivery to
reduce wasted time and
inefficiency in supply chains
and other business-to-
business (B2B) transactions.
Twitter dominates the
reporting of news and events
as they are still happening.
Facebook became the most
powerful sharing network
in the world.

Smartphones, tablets, other
touch devices, and their apps
reshaped how organizations
interact with customers—and
how customers want
businesses to interact with
them.
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The ways in which market leaders are transitioning to digital
business models
include the following:
• Amazon gains a competitive edge with high-tech tech support.
Amazon
is well known for radically changing online shopping and e-
book reading
experiences. Amazon’s CEO Jeffrey Bezos set a new standard
for tech sup-
port with MayDay (Figure 1.10). Within 15 seconds of touching
the MayDay
button on their Kindle Fire HDX tablet, customers get free,
24/7/365 tech
support via video chat. MayDay works by integrating all
customer data and
instantly displaying the results to a tech agent when a customer
presses the
MayDay button. Plus, tech agents can control and write on a
customer’s Fire

screen. By circling and underlining various buttons on the
display, it is dead
simple for new Fire owners to become expert with their devices.
Amazon’s
objective is to educate the consumer rather than just fix the
problem. In the
highly competitive tablet wars, Amazon has successfully
differentiated its
tablet from those of big players like Apple, Samsung, and Asus
(manufac-
turer of Google’s Nexus 7) with the MayDay button.
• NBA talent scouts rely on sports analytics and advanced
scouting systems.
NBA talent scouts used to crunch players’ stats, watch live
player perfor-
mances, and review hours of tapes to create player profiles
(Figure 1.11).
Now software that tracks player performance has changed how
basketball
and soccer players are evaluated. For example, STATS’
SportVU tech-
nology is revolutionizing the way sports contests are viewed,
understood,
played, and enjoyed. SportVU uses six palm-sized digital
cameras that
track the movement of every player on the court, record ball
movement
25 times per second, and convert movements into statistics.
SportVU
produces real time and highly complex statistics to complement
the tra-
ditional play-by-play. Predictive sport analytics can provide a
360-degree
view of a player’s performance and help teams make trading
decisions.

Figure 1.10 MayDay video
chat tech support.
Figure 1.11 Sports analytics
and advanced scouting
systems evaluate talent
and performance for the
NBA—offering teams a
slight but critical competitive
advantage.
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Sports analytics bring about small competitive advantages that
can shift
games and even playoff series.
• Dashboards keep casino floor staff informed of player
demand. Competition

in the gaming industry is fierce, particularly during bad
economic condi-
tions. The use of manual spreadsheets and gut-feeling decisions
did not lead
to optimal results. Casino operators facing pressure to increase
their bottom
line have invested in analytic tools, such as Tangam’s Yield
Management
solution (TYM). TYM is used to increase the yield
(profitability) of black-
jack, craps, and other table games played in the pit (Figure
1.12). The
analysis and insights from real time apps are used to improve
the gaming
experience and comfort of players.
Figure 1.12 Casinos are
improving the profi tability of
table games by monitoring
and analyzing betting in real
time.
THE RECENT PAST AND
NEAR FUTURE—2010S
DECADE
We have seen great advances in digital technology since the
start of this decade.
Figure 1.13 shows releases by tech leaders that are shaping
business and everyday
life. Compare the role of your mobiles, apps, social media, and
so on in your per-
sonal life and work in 2010 to how you use them today. You can
expect greater
changes going forward to the end of this decade with the
expansion of no-touch

interfaces, mobility, wearable technology, and the IoT.
Companies are looking for ways to take advantage of new
opportunities in
mobile, big data, social, and cloud services to optimize their
business processes.
The role of the IT function within the enterprise has changed
significantly—and
will evolve rapidly over the next five years. As you will read
throughout this book,
the IT function has taken on key strategic and operational roles
that determine the
enterprise’s success or failure.
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Figure 1.13 Digital
technology released
since 2010.

• Google launched
Android mobile
OS to compete
with iPhones
By 2014, became
the first billion-user
mobile OS
• App Store opened
on July 10, 2008
via an update to iTunes
By mid-2011, over 15 billion apps
downloaded from App Store
2008
• Apple launched
iPad
100 million
iPads sold
in 2 years
2010 2011–2012
• No tough interfaces
to communicate
by simply gesturing
or talking
Microsoft’s Kinect for
Windows Apple’s Siri
Google’s Glass
• iWatch released
integrates with
iOS devices
2014

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More objects are being embedded with sensors and gaining
the ability to communicate with the Internet. This communi-
cation improves business processes while reducing costs and
risks. For example, sensors and network connections can be
embedded in rental cars. Zipcar has pioneered the car rental
by the hour business model. See Figure 1.14. Cars are leased
for short time spans to registered members, making retail
rental centers unnecessary. Traditional car rental agencies
are starting to experiment with sensors so that each car’s use
can be optimized to increase revenue.
When devices or products are embedded with sensors,
companies can track their movements or monitor interac-
tions with them. Business models can be adjusted to take
advantage of what is learned from this behavioral data. For
example, an insurance company offers to install location
sensors in customers’ cars. By doing so, the company
develops the ability to price the drivers’ policies on how a
car is driven and where it travels. Pricing is customized to
match the actual risks of operating a vehicle rather than
based on general proxies—driver’s age, gender, or location
of residence.
Opportunities for Improvement
Other applications of embedded physical things are:
• In the oil and gas industry, exploration and development
rely on extensive sensor networks placed in the earth’s

crust. The sensors produce accurate readings of the
location, structure, and dimensions of potential fields.
The payoff is lower development costs and improved oil
flows.
• In the health-care industry, sensors and data links can
monitor patients’ behavior and symptoms in real time
and at low cost. This allows physicians to more precisely
diagnose disease and prescribe treatment regimens.
For example, sensors embedded in patients with heart
disease or chronic illnesses can be monitored continu-
ously as they go about their daily activities. Sensors
placed on congestive heart patients monitor many of
these signs remotely and continuously, giving doctors
early warning of risky conditions. Better management
of congestive heart failure alone could reduce hospi-
talization and treatment costs by $1 billion per year in
the U.S.
• In the retail industry, sensors can capture shoppers’ pro-
file data stored in their membership cards to help close
purchases by providing additional information or offering
discounts at the point of sale.
• Farm equipment with ground sensors can take into
account crop and field conditions, and adjust the
amount of fertilizer that is spread on areas that need more
nutrients.
• Billboards in Japan scan people passing by, assessing
how they fit consumer profiles, and instantly change the
displayed messages based on those assessments.
• The automobile industry is developing systems that
can detect imminent collisions and take evasive action.

Certain basic applications, such as automatic braking
systems, are available in high-end autos. The potential
accident reduction savings resulting from wider deploy-
ment of these sensor systems could exceed $100 billion
annually.
Questions
1. Research Zipcar. How does this company’s business
model differ from that of traditional car rental companies,
such as Hertz or Avis?
2. Think of two physical things in your home or office that,
if they were embedded with sensors and linked to a net-
work, would improve the quality of your work or personal
life. Describe these two scenarios.
3. What might the privacy concerns be?
IT at Work 1 .1
Zipcar and Other Connected Products
Figure 1.14 A Zipcar-reserved parking sign in
Washington, DC.
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By 2016 wearable electronics in shoes, tattoos, and accessories
will become a $10 billion industry, according to Gartner (2012).
Wearable technology builds computing, connectivity,
and sensor capabilities into materials. The latest wearables
are lightweight and may be found in athletic shoes, golf
accessories, and fitness trackers. The wearables can include
data analysis apps or services that send feedback or insights
to the wearer. For example, Zepp Labs manufactures sensor-
embedded gloves for golf, tennis, and baseball that analyze
1,000 data points per second to create 3D representations
of a player’s swing. The sensors track every inch of a golfer’s
swing, analyzes the movements, and then sends the wearers
advice on how to improve their game. Sensors that weigh
only half an ounce clip onto the glove. Another example is
Sony’s SmartBand, a wristband that synchs with your phone
to track how many steps you take, the number of calories you
burn each day, and how well you sleep. The Lifelog app is
the key to the Smartband. The app gives a visual display of a
timeline and your activity, with boxes monitoring your steps,
calories, kilometers walked, and more. Lifelog goes beyond
just fitness by also monitoring time spent on social networks
and photos taken.

The major sources of revenue from wearable smart
electronics are items worn by athletes and sports enthusiasts
and devices used to monitor health conditions, such as auto-
matic insulin delivery for diabetics.
Applications and services are creating new value for
consumers, especially when they are combined with personal
preferences, location, biosensing, and social data. Wearable
electronics can provide more detailed data to retailers for
targeting advertisements and promotions.
Questions
1. Discuss how wearable electronics and the instant feedback
they send to your mobile device could be valuable to you.
2. How can data from wearable technology be used to
improve worker productivity or safety?
3. What are two other potentially valuable uses of instant
feedback or data from wearable technology?
4. How can wearable devices impact personal privacy?
IT at Work 1 . 2
Wearable Technology
All functions and departments in the enterprise have tasks that
they need to com-
plete to produce outputs, or deliverables, in order to meet their
objectives. Business
processes are series of steps by which organizations coordinate
and organize tasks
to get work done. In the simplest terms, a process consists of
activities that convert
inputs into outputs by doing work.

The importance of efficient business processes and continuous
process improve-
ment cannot be overemphasized. Why? Because 100 per cent of
an enterprise’s perfor-
mance is the result of its processes. Maximizing the use of
inputs in order to carry out
similar activities better than one’s competitors is a critical
success factor. IT at Work 1.3
describes the performance gains at AutoTrader.com, the
automobile industry’s largest
online shopping marketplace, after it redesigned its order-to-
cash process.
1.2 Business Process Management and Improvement
Objectives define the desired
benefits or expected per-
formance improvements.
They do not and should not
describe what you plan to do,
how you plan to do it, or what
you plan to produce, which is
the function of processes.
Questions
1. What are the benefi ts of cloud computing?
2. What is machine-to-machine (M2M) technology? Give an
example of a
business process that could be automated with M2M.
3. Describe the relationships in the SoMoClo model.
4. Explain the cloud.
5. Why have mobile devices given consumers more power in
the marketplace?
6. What is a business model?
7. What is a digital business model?

8. Explain the Internet of Things.
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AutoTrader.com is the leading automotive marketplace, list-
ing several million new and pre-owned vehicles, as shown
in Figure 1.15. AutoTrader.com is one of the largest local
online advertising entities, with profits of $300 million on
$1.2 billion in revenues in 2013. The site attracts over 15 mil-
lion unique visitors each month.
Outdated Order-to-Cash Process
AutoTrader processes thousands of orders and contracts
each month. Its cross-functional order fulfillment process,
or order-to-cash process, was outdated and could not
handle the sales volume. The legacy process was run on My
AutoTrader (MAT), a system based on Lotus Notes/Domino.
MAT took an average of 6.3 to 8.3 days to fulfill orders and
process contracts, as Figure 1.16 shows. MAT created a bot-
tleneck that slowed the time from order to cash, or revenue
generation. With over 100 coordinated steps, the process
was bound to be flawed, resulting in long and error-prone
cycle times. Cycle time is the time required to complete a
given process. At AutoTrader, cycle time is the time between
the signing and delivery of a contract. Customers were
aggravated by the unnecessary delay in revenue.
Redesigning the Order Fulfillment
Process with BPM

Management had set three new objectives for the company:
to be agile, to generate revenue faster, and to increase
customer satisfaction. They invested in a BPM (business pro-
cess management) solution—selecting webMethods from
Software AG (softwareag.com, 2011). The BPM software
was used to document how tasks were performed using
the legacy system. After simplifying the process as much as
possible, remaining tasks were automated or optimized. The
new system cuts down the order fulfillment process to 1 day,
as shown in Figure 1.17. Changes and benefits resulting from
the redesigned process are:
• There are only six human tasks even though the pro-
cess interacts with over 20 different data sources and
systems, including the inventory, billing, and contract
fulfillment.
• Tasks are assigned immediately to the right people, who
are alerted when work is added to their queues.
• Fewer than five percent of orders need to go back to
sales for clarification—a 400 percent improvement.
• Managers can check order fulfillment status anytime
using webMethods Optimize for Process, which provides
real time visibility into performance. They can measure
key performance indicators (KPIs) in real time to see
where to make improvements.
• Dealers can make changes directly to their contracts,
which cut costs for personnel. Software and hardware
costs are decreasing as the company retires old systems.
Sources: Compiled from Walsh (2012), softwareag.com (2011),
Alesci &

Saitto (2012).
IT at Work 1 . 3
AutoTrader Redesigns Its Order-to-Cash Process
Figure 1.15 AutoTrader.com car search site.
Figure 1.16 AutoTrader’s
legacy order fulfi llment
process had an average cycle
time of up to 8.3 days.
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Fulfillment Total Avg
Quality
Assurance
Contract
Delivered

Data EntryFax
2.8 days
2.8 days
.5 day 4 days 8.3 days
6.3 days
1 day
1 day2 days.5 day
New
Up-sell
Contract
Signed
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Figure 1.17 AutoTrader’s
objective is to process and
fi ll orders within one day.
Questions
1. Discuss how the redesigned order process supports the
company’s three new business objectives.

2. How does the reduced cycle time of the order fulfillment
pro-
cess improve revenue generation and customer satisfaction?
3. Does reducing the cycle time of a business process also
reduce errors? Why or why not?
THREE COMPONENTS
OF BUSINESS
PROCESSES
Business processes have three basic components, as shown in
Figure 1.18. They
involve people, technology, and information.
Examples of common business processes are:
• Accounting: Invoicing; reconciling accounts; auditing
• Finance: Credit card or loan approval; estimating credit risk
and financing
terms
• Human resources (HR): Recruiting and hiring; assessing
compliance with
regulations; evaluating job performance
• IT or information systems: Generating and distributing reports
and data
visualizations; data analytics; data archiving
• Marketing: Sales; product promotion; design and
implementation of sales
campaigns; qualifying a lead

• Production and operations: Shipping; receiving; quality
control; inventory
management
• Cross-functional business processes: Involving two or more
functions, for
example, order fulfillment and product development
Designing an effective process can be complex because you
need a deep under-
standing of the inputs and outputs (deliverables), how things
can go wrong, and how
to prevent things from going wrong. For example, Dell had
implemented a new
process to reduce the time that tech support spent handling
customer service calls. In
an effort to minimize the length of the call, tech support’s
quality dropped so much
that customers had to call multiple times to solve their
problems. The new process
had backfired—increasing the time to resolve computer
problems and aggravating
Dell customers.
Figure 1.18 Three
components of a
business process.
Deliverables are the outputs
or tangible things that are
produced by a business pro-
cess. Common deliverables
are products, services, actions,
plans, or decisions, such as
to approve or deny a credit
application. Deliverables are

produced in order to achieve
specific objectives.
Submit sales
order
electronically
Day 1:
Live online
processing of orders
Day 2:
Order fulfillment
1 day elapsed
raw materials,
data,
knowledge,
expertise
work that
transforms
inputs & acts on
data and
knowledge
products,
services,
plans,
or actions
Inputs Activities

Business Process
Deliverables
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Characteristics of Business Processes
Processes can be formal or informal. Formal processes are
documented and have
well-established steps. Order taking and credit approval
processes are examples.
Routine formal processes are referred to as standard operating
procedures, or
SOPs. A SOP is a well-defined and documented way of doing
something. An effec-
tive SOP documents who will perform the tasks; what materials
to use; and where,
how, and when the tasks are to be performed. SOPs are needed
for the handling of
food, hazardous materials, or situations involving safety,
security, or compliance. In
contrast, informal processes are typically undocumented, have
inputs that may not
yet been identified, and are knowledge-intensive. Although
enterprises would pre-
fer to formalize their informal processes in order to better
understand, share, and
optimize them, in many situations process knowledge remains in
people’s heads.

Processes range from slow, rigid to fast-moving, adaptive. Rigid
processes
can be structured to be resistant to change, such as those that
enforce security or
compliance regulations. Adaptive processes are designed to
respond to change or
emerging conditions, particularly in marketing and IT.
Process Improvement
Given that a company’s success depends on the efficiency of its
business processes,
even small improvements in key processes have significant
payoff. Poorly designed,
flawed, or outdated business processes waste resources,
increasing costs, causing
delays, and aggravating customers. For example, when
customers’ orders are not
filled on time or correctly, customer loyalty suffers, returns
increase, and reship-
ping increases costs. The blame may be flawed order fulfilment
processes and not
employee incompetence, as described in IT at Work 1.2.
Simply applying IT to a manual or outdated process will not
optimize it.
Processes need to be examined to determine whether they are
still necessary.
After unnecessary processes are identified and eliminated, the
remaining ones are
redesigned (or reengineered) in order to automate or streamline
them. Methods
and efforts to eliminate wasted steps within a process are
referred to as business
process reengineering (BPR). The goal of BPR is to eliminate
the unnecessary,

non-value-added processes, then to simplify and automate the
remaining processes
to significantly reduce cycle time, labor, and costs. For
example, reengineering the
credit approval process cuts time from several days or hours to
minutes or less.
Simplifying processes naturally reduces the time needed to
complete the process,
which also cuts down on errors.
After eliminating waste, digital technology can enhance
processes by (1) auto-
mating existing manual processes; (2) expanding the data flows
to reach more func-
tions in order to make it possible for sequential activities to
occur in parallel; and
(3) creating innovative business processes that, in turn, create
new business models.
For instance, consumers can scan an image of a product and
land on an e-commerce
site, such as Amazon.com, selling that product. This process
flips the traditional
selling process by making it customer-centric.
Business Process Management
BPR is part of the larger discipline of business process
management (BPM), which
consists of methods, tools, and technology to support and
continuously improve
business processes. The purpose of BPM is to help enterprises
become more agile
and effective by enabling them to better understand, manage,
and adapt their busi-
ness processes. Vendors, consulting and tech firms offer BPM
expertise, services,

software suites, and tools.
BPM software is used to map processes performed either by
computers or
manually—and to design new ones. The software includes built-
in templates show-
ing workflows and rules for various functions, such as rules for
credit approval. These
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templates and rules provide consistency and high-quality
outcomes. For example, Oracle’s
WebLogic Server Process Edition includes server software and
process integration
tools for automating complex business processes, such as
handling an insurance claim.
But, BPM initiatives can be extremely challenging, and in order
to be suc-
cessful, BPM requires buy-in from a broad cross section of the
business, the right
technology selection, and highly effective change management
processes. You will
read more about optimizing business processes and BPM’s role
in the alignment of
IT and business strategy in Chapter 13.
Questions
1. What is a business process? Give three examples.
2. What is the difference between business deliverables and

objectives?
3. List and give examples of the three components of a business
process.
4. Explain the differences between formal and informal
processes.
5. What is a standard operating procedure (SOP)?
6. What is the purpose of business process management (BPM)?
In business, as in sports, companies want to win—customers,
market share, and so
on. Basically, that requires gaining an edge over competitors by
being first to take
advantage of market opportunities, providing great customer
experiences, doing
something well that others cannot easily imitate, or convincing
customers why it is
a more valuable alternative than the competition.
1.3 The Power of Competitive Advantage
Agility means being able
to respond quickly.
Responsiveness means that
IT capacity can be easily
scaled up or down as needed,
which essentially requires
cloud computing.
Flexibility means having the
ability to quickly integrate
new business functions or to
easily reconfigure software
or apps.
BUILDING BLOCKS

OF COMPETITIVE
ADVANTAGE
Having a competitive edge means possessing an advantage over
your competition.
Once an enterprise has developed a competitive edge,
maintaining it is an ongoing
challenge. It requires forecasting trends and industry changes
and what the company
needs to do to stay ahead of the game. It demands that you
continuously track your
competitors and their future plans and promptly take corrective
action. In summary,
competitiveness depends on IT agility and responsiveness. The
benefit of IT agility
is being able to take advantage of opportunities faster or better
than competitors.
Closely related to IT agility is flexibility. For example, mobile
networks are
flexible—able to be set up, moved, or removed easily, without
dealing with cables
and other physical requirements of wired networks. Mass
migration to mobile
devices from PCs has expanded the scope of IT beyond
traditional organizational
boundaries—making location practically irrelevant.
IT agility, flexibility, and mobility are tightly interrelated and
fully dependent
on an organization’s IT infrastructure and architecture, which
are covered in greater
detail in Chapter 2.
With mobile devices, apps, platforms, and social media
becoming inseparable parts

of work life and corporate collaboration and with more
employees working from home,
the result is the rapid consumerization of IT. IT
consumerization is the migration of
consumer technology into enterprise IT environments. This shift
has occurred because
personally owned IT is as capable and cost-effective as its
enterprise equivalents.
COMPETITIVE
ADVANTAGE
Two key components of corporate profitability are:
1. Industry structure: An industry’s structure determines the
range of profi tability
of the average competitor and can be very diffi cult to change.
2. Competitive advantage: This is an edge that enables a
company to outperform
its average competitor. Competitive advantage can be sustained
only by con-
tinually pursuing new ways to compete.
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IT plays a key role in competitive advantage, but that advantage
is short-lived
if competitors quickly duplicate it. Research firm Gartner
defines competitive
advantage as a difference between a company and its

competitors that matters to
customers.
It is important to recognize that some types of IT are
commodities, which do
not provide a special advantage. Commodities are basic things
that companies need
to function, such as electricity and buildings. Computers,
databases, and network
services are examples of commodities. In contrast, how a
business applies IT to sup-
port business processes transforms those IT commodities into
competitive assets.
Critical business processes are those that improve employee
performance and profit
margins.
STRATEGIC PLANNING
AND COMPETITIVE
MODELS
Strategy planning is critical for all organizations, including
government agencies,
health care providers, educational institutions, the military, and
other nonprofits.
We start by discussing strategic analysis and then explain the
activities or compo-
nent parts of strategic planning.
What Is Strategic (SWOT) Analysis?
There are many views on strategic analysis. In general, strategic
analysis is the scan-
ning and review of the political, social, economic, and technical
environments of an
organization. For example, any company looking to expand its

business operations
into a developing country has to investigate that country’s
political and economic
stability and critical infrastructure. That strategic analysis
would include reviewing
the U.S. Central Intelligence Agency’s (CIA) World Factbook.
The World Factbook
provides information on the history, people, government,
economy, geography,
communications, transportation, military, and transnational
issues for 266 world
entities. Then the company would need to investigate
competitors and their poten-
tial reactions to a new entrant into their market. Equally
important, the company
would need to assess its ability to compete profitably in the
market and impacts of
the expansion on other parts of the company. For example,
having excess production
capacity would require less capital than if a new factory needed
to be built.
The purpose of this analysis of the environment, competition,
and capacity is
to learn about the strengths, weaknesses, opportunities, and
threats (SWOT) of the
expansion plan being considered. SWOT analysis, as it is
called, involves the evalu-
ation of strengths and weaknesses, which are internal factors,
and opportunities and
threats, which are external factors. Examples are:
• Strengths: Reliable processes; agility; motivated workforce
• Weaknesses: Lack of expertise; competitors with better IT
infrastructure

• Opportunities: A developing market; ability to create a new
market or product
• Threats: Price wars or other fierce reaction by competitors;
obsolescence
SWOT is only a guide. The value of SWOT analysis depends on
how the analy-
sis is performed. Here are several rules to follow:
• Be realistic about the strengths and weaknesses of your
organization.
• Be realistic about the size of the opportunities and threats.
• Be specific and keep the analysis simple, or as simple as
possible.
• Evaluate your company’s strengths and weaknesses in relation
to those of
competitors (better than or worse than competitors).
• Expect conflicting views because SWOT is subjective,
forward-looking, and
based on assumptions.
SWOT analysis is often done at the outset of the strategic
planning process.
Now you will read answers to the question, “What is strategic
planning?”
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What Is Strategic Planning?
Strategic planning is a series of processes in which an
organization selects and
arranges its businesses or services to keep the organization
healthy or able to func-
tion even when unexpected events disrupt one or more of its
businesses, markets,
products, or services. Strategic planning involves environmental
scanning and pre-
diction, or SWOT analysis, for each business relative to
competitors in that business’s
market or product line. The next step in the strategic planning
process is strategy.
What Is Strategy?
Strategy defines the plan for how a business will achieve its
mission, goals, and
objectives. The plan specifies the necessary financial
requirements, budgets, and
resources. Strategy addresses fundamental issues such as the
company’s position
in its industry, its available resources and options, and future
directions. A strategy
addresses questions such as:
• What is the long-term direction of our business?
• What is the overall plan for deploying our resources?
• What trade-offs are necessary? What resources will need to be
shared?

• What is our position compared to that of our competitors?
• How do we achieve competitive advantage over rivals in order
to achieve or
maximize profitability?
Two of the most well-known methodologies were developed by
Michael Porter.
Porter’s Competitive Forces Model and Strategies
Michael Porter’s competitive forces model, also called the five-
forces model, has
been used to identify competitive strategies. The model
demonstrates how IT
can enhance competitiveness. Professor Porter discusses this
model in detail in a
13-minute YouTube video from Harvard Business School.
The model recognizes five major forces (think of them as
pressures or drivers) that
influence a company’s position within a given industry and the
strategy that manage-
ment chooses to pursue. Other forces, including new
regulations, affect all companies
in the industry, and have a rather uniform impact on each
company in an industry.
According to Porter, an industry’s profit potential is largely
determined by the
intensity of competitive forces within the industry, shown in
Figure 1.19. A good
understanding of the industry’s competitive forces and their
underlying causes is a
crucial component of strategy formulation.

Basis of the competitive forces model Before examining the
model, it is
helpful to understand that it is based on the fundamental
concept of profitability
and profit margin:
PROFIT TOTAL REVENUES minus TOTAL COSTS
Profit is increased by increasing total revenues and/or
decreasing total costs. Profit
is decreased when total revenues decrease and/or total costs
increase:
PROFIT MARGIN SELLING PRICE minus COST OF THE
ITEM
Profit margin measures the amount of profit per unit of sales,
and does not take into
account all costs of doing business.
Five industry forces According to Porter’s competitive forces
model, the five
major forces in an industry affect the degree of competition,
which impact profit
margins and ultimately profitability. These forces interact, so
while you read about
them individually, their interaction determines the industry’s
profit potential. For
example, while profit margins for pizzerias may be small, the
ease of entering that
Video 1-1
Five Competitive Forces
that Shape Strategy, by
Michael Porter: youtube.com/

watch?v mYF2_FBCvXw
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Threat of
New Entrants
(Bargaining Power of
Suppliers and Brands)
(Bargaining Power of
Buyers and Distribution
Channels)
Rivalry
Competing
Companies
Our
Company
Threat of Substitute
Products or Services
Supplier Power Buyer Power
Figure 1.19 Porter’s
competitive forces model.
industry draws new entrants. Conversely, profit margins for

delivery services may
be large, but the cost of the IT needed to support the service is a
huge barrier to
entry into the market.
The five industry (or market) forces are:
1. Threat of entry of new competitors. Industries that have
large profi t margins
attract entrants into the market to a greater degree than
industries with small
margins. The same principle applies to jobs—people are
attracted to higher-paying
jobs, provided that they can meet the criteria or acquire the
skills for that job.
In order to gain market share, entrants usually need to sell at
lower prices as an
incentive. Their tactics can force companies already in the
industry to defend
their market share by lowering prices—reducing profi t margin.
Thus, this threat
puts downward pressure on profi t margins by driving down
prices.
This force also refers to the strength of the barriers to entry
into an industry,
which is how easy it is to enter an industry. The threat of entry
is lower (less pow-
erful) when existing companies have ITs that are diffi cult to
duplicate or very
expensive. Those ITs create barriers to entry that reduce the
threat of entry.
2. Bargaining power of suppliers. Bargaining power is high
where the supplier or
brand is powerful, such as Apple, Microsoft, and auto
manufacturers. Power is

determined by how much a company purchases from a supplier.
The more pow-
erful company has the leverage to demand better prices or
terms, which increase
its profi t margin. Conversely, suppliers with very little
bargaining power tend to
have small profi t margins.
3. Bargaining power of customers or buyers. This force is the
reverse of the bar-
gaining power of suppliers. Examples are Walmart and
government agencies.
This force is high when there are few large customers or buyers
in a market.
4. Threat of substituting products or services. Where there is
product-for-product
substitution, such as Kindle for Nook, there is downward
pressure on prices. As
the threat of substitutes increases, the profi t margin decreases
because sellers
need to keep prices competitively low.
5. Competitive rivalry among existing fi rms in the industry.
Fierce competition in-
volves expensive advertising and promotions, intense
investments in research
and development (R&D), or other efforts that cut into profi t
margins. This force
is most likely to be high when entry barriers are low, the threat
of substitute
products is high, and suppliers and buyers in the market attempt
to control it.
That is why this force is placed in the center of the model.

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The strength of each force is determined by the industry’s
structure. Existing
companies in an industry need to protect themselves against
these forces.
Alternatively, they can take advantage of the forces to improve
their position or to
challenge industry leaders. The relationships are shown in
Figure 1.19.
Companies can identify the forces that influence competitive
advantage in their
marketplace and then develop their strategy. Porter (1985)
proposed three types of
strategies—cost leadership, differentiation, and niche strategies.
In Table 1.2, Porter’s
three classical strategies are listed first, followed by a list of
nine other general
strategies for dealing with competitive advantage. Each of these
strategies can be
enhanced by IT.
TABLE 1.2 Strategies for Competitive Advantage
Strategy Description
Cost leadership Produce product/service at the lowest cost in
the
industry.
Differentiation Offer different products, services, or product

features.
Niche Select a narrow-scope segment (market niche) and
be the best in quality, speed, or cost in that segment.
Growth Increase market share, acquire more customers, or
sell more types of products.
Alliance Work with business partners in partnerships, alli-
ances, joint ventures, or virtual companies.
Innovation Introduce new products/services; put new features
in existing products/services; develop new ways to
produce products/services.
Operational effectiveness Improve the manner in which internal
business
processes are executed so that the fi rm performs
similar activities better than its rivals.
Customer orientation Concentrate on customer satisfaction.
Time Treat time as a resource, then manage it and use it
to the fi rm’s advantage.
Entry barriers Create barriers to entry. By introducing
innovative
products or using IT to provide exceptional service,
companies can create entry barriers to discourage
new entrants.
Customer or supplier Encourage customers or suppliers to stay
with
lock-in you rather than going to competitors. Reduce
customers’ bargaining power by locking them in.

Increase switching costs Discourage customers or suppliers
from going to
competitors for economic reasons.
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Primary activities are those business activities directly involved
in the production
of goods. Primary activities involve the purchase of materials,
the processing of materi-
als into products, and delivery of products to customers. The
five primary activities are:
1. Inbound logistics, or acquiring and receiving of raw materials
and other inputs
2. Operations, including manufacturing and testing
3. Outbound logistics, which includes packaging, storage,
delivery, and distribution
4. Marketing and sales to customers
5. Services, including customer service
The primary activities usually take place in a sequence from 1
to 5. As work
progresses, value is added to the product in each activity. To be
more specific, the
incoming materials (1) are processed (in receiving, storage,
etc.) in activities called

inbound logistics. Next, the materials are used in operations (2),
where significant
value is added by the process of turning raw materials into
products. Products need
to be prepared for delivery (packaging, storing, and shipping) in
the outbound logis-
tics activities (3). Then marketing and sales (4) attempt to sell
the products to cus-
tomers, increasing product value by creating demand for the
company’s products.
The value of a sold item is much larger than that of an unsold
one. Finally, after-
sales service (5), such as warranty service or upgrade
notification, is performed for
the customer, further adding value.
Primary activities rely on the following support activities:
1. The fi rm’s infrastructure, accounting, fi nance, and
management
2. Human resources (HR) management (For an IT-related HR
trend, see IT at
Work 1.4.)
3. Technology development, and research and development
(R&D)
4. Procurement, or purchasing
Each support activity can be applied to any or all of the primary
activities.
Support activities may also support each other, as shown in
Figure 1.20.
Innovation and adaptability are critical success factors, or

CSFs, related to
Porter’s models. CSFs are those things that must go right for a
company to achieve
its mission.
Accounting, legal &
finance
Human resources
management
INBOUND
LOGISTICS
Quality control,
receiving,
raw materials
control
OPERATION
Manufacturing,
packaging,
production
control, quality
control
OUTBOUND
LOGISTICS
Order handling,
delivery,
invoicing
SALES &
MARKETING
Sales
campaigns,

order taking,
social
networking,
sales analysis,
market
research
SERVICING
Warranty,
maintenance
Procurement
Product and
technology
development
Legal, accounting, financial management
Personnel, recruitment, training, staff planning, etc.
Supplier management, funding, subcontracting
Product and process design, production
engineering, market testing, R&D
S
u
p
p
o
rt

A
ct
iv
it
ie
s
P
ri
m
ar
y
A
ct
iv
it
ie
s
Figure 1.20 A fi rm’s value
chain. The arrows represent
the fl ow of goods, services,
and data.
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1.4 Enterprise Technology Trends 25
Questions
1. What are the characteristics of an agile organization?
2. Explain IT consumerization.
3. What are two key components of corporate profi tability?
4. Defi ne competitive advantage.
5. Describe strategic planning.
6. Describe SWOT analysis.
7. Explain Porter’s fi ve-forces model, and give an example of
each force.
Managers at a global energy services company could not
find or access their best talent to solve clients’ technical
problems because of geographic boundaries and business
unit barriers. The company’s help desks supported engineers
well enough for common problems, but not for difficult
issues that needed creative solutions. Using Web technolo-
gies to expand access to experts worldwide, the company
set up new innovation communities across its business units,
which have improved the quality of its services.
Dow Chemical set up its own social network to help
managers identify the talent they need to carry out projects
across its diverse business units and functions. To expand
its talent pool, Dow extended the network to include former
employees and retirees.
Other companies are using networks to tap external tal-
ent pools. These networks include online labor markets such
as Amazon Mechanical Turk and contest services such as
InnoCentive that help solve business problems.
• Amazon Mechanical Turk is a marketplace for work that
requires human intelligence. Its web service enables

companies to access a diverse, on-demand workforce.
• InnoCentive is an “open innovation” company that
takes R&D problems in a broad range of areas such as
engineering, computer science, and business and frames
them as “challenge problems” for anyone to solve. It
gives cash awards for the best solutions to solvers who
meet the challenge criteria.
Sources: Compiled from McKinsey Global Institute
(mckinsey.com/
insights/mgi.aspx), Amazon Mechanical Turk (aws.amazon.com/
mturk), and InnoCentive (Innocentive.com).
Questions
1. Visit and review the Amazon Mechanical Turk website.
Explain HITs. How do they provide an on-demand work-
force?
2. Visit and review the InnoCentive website. Describe what
the company does and how.
IT at Work 1 . 4
Finding Qualified Talent
At the end of his iPhone presentation at MacWorld 2007,
Apple’s visionary leader
Steve Jobs displayed advice once expressed by legendary
hockey player Wayne
Gretzky (Figure 1.21): “I skate to where the puck is going to be,
not where it has
been.” Steve Jobs added: “And we’ve always tried to do that at
Apple. Since the

very very beginning. And we always will.” He was telling us
that Apple always
moves toward where it expects the future will be.
Looking at Apple’s history, you see innovative products and
services that shaped
the future. For example, launching the iTunes store in April
2003 jumpstarted the
1.4 Enterprise Technology Trends
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digital music industry. iTunes was a significant breakthrough
that forever changed
the music industry and the first representation of Apple’s future
outside its traditional
computing product line. You are familiar with the success of
that future-driven busi-
ness model.
Three IT directions for the late 2010s are outlined next.
Throughout all the
chapters in this book, you will learn how these and other digital
technology are
transforming business and society.
Figure 1.21 Wayne Gretzky’s strategy for success in hockey was
to skate to
where the puck was going to be. Steve Jobs followed a similar
forward-looking

strategy. In October, 2003, Jobs announced a Windows version
of the iTunes
store, saying “Hell froze over,” which brought a big laugh from
the audience in
San Francisco.
MORE MOBILE
BUSINESS APPS, FEWER
DOCS ON DESKTOPS
The direction is away from the traditional desktop and
documents era and toward
business apps in the cloud. Why? Google Apps offers apps that
provide work-
ers with information and answers with low effort—instead of
having to complete
tedious actions, such as logging in or doing extensive searches.
This ongoing move
to mobile raises data security issues. Data stored on mobiles are
at higher risk, in
part because the devices can be stolen or lost.
MORE SOCIALLY
ENGAGED—BUT
SUBJECT TO
REGULATION
Engaging customers via mobiles and social media sites—and
those customers who
do not tolerate delays—is the norm. However, customers
probably do not know of
restrictions on financial institutions and health–care providers
that make it illegal
to respond to individuals publicly via social media. That is, for
regulatory purposes,
financial institutions cannot post or respond to comments or e-

mails through social
media sites because of privacy and security.
MORE NEAR-FIELD
COMMUNICATION
(NFC) TECHNOLOGY
Near-field communication (NFC) technology is an umbrella
description covering
several technologies that communicate within a limited
distance. Using radio fre-
quency identification (RFID) chip-based tags, as shown in
Figure 1.22, devices relay
identifying data, such as product ID, price, and location, to a
nearby reader that
captures the data. It is projected that the global market for NFC
handsets will reach
1.6 billion units by 2018, according to a recent Global Industry
Analysts research
report. According to the report, strong demand is “driven by
growing penetration
of mobile phones, continued rise in demand and production of
smartphones, rising
penetration of NFC in consumer devices, and chip level
technology developments”
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and Career 27
(NFC World, 2014). Innovative ways in which businesses are
applying NFC include
the following:
• Amsterdam’s Schiphol Airport has installed an NFC boarding
gate allowing pas-
sengers to validate their boarding pass with a touch of their
NFC smartphone.
• French leather goods brand Delage has partnered with NFC
object identi-
fication specialist Selinko to integrate NFC tags into its range
of premium
leather bags. Each bag will have a unique chip and a unique
digital serial
number. Consumers with an NFC smartphone equipped with
Selinko’s free
mobile app will be able to use the tag to access information
about their
product and confirm its authenticity as well as access marketing
offers.
• iPhone owners in the United States can make Isis payments
following
AT&T’s introduction of a range of phone cases that add NFC
functionality
to the devices. To use the Isis Mobile Wallet on an iPhone, the
owner selects
the Isis-ready NFC case, slides the iPhone in, downloads the
Isis Mobile
Wallet app from the App Store, and taps the iPhone at hundreds
of thou-
sands of merchants nationwide for a quick way to pay.

These trends are forces that are changing competition, business
models, how
workers and operations are managed, and the skills valuable to a
career in business.
Figure 1.22 NFC technology relies on sensors or RFID chips.
NFC is used
for tracking wine and liquor to manage the supply chain effi
ciently. NFC
smartphones are being integrated into payment systems in
supermarkets so
customers can pay for purchases without cash or credit cards.
Questions
1. What was the signifi cance of Apple’s introduction of the
iPhones music
store?
2. What are three IT trends?
3. What are three business applications of NFC?
Every tech innovation triggers opportunities and threats to
business models and
strategies. With rare exceptions, every business initiative
depends on the mix of IT,
knowledge of its potential, the requirements for success, and,
equally important, its
limitations. Staying current in emerging technologies affecting
markets is essential to
the careers of knowledge workers, entrepreneurs, managers, and
business leaders—
not just IT and chief information officers (CIOs).
and Career

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WHAT COMPANIES
CAN DO DEPENDS
ON THEIR IT
What companies can do depends on what their information
technology and data
management systems can do. For over a decade, powerful new
digital approaches
to doing business—and getting through your day—have
emerged. And there is
sufficient proof to expect even more rapid and dramatic changes
due to IT break-
throughs and advances. Understanding trends that affect the
ways business is done
and getting in front of those trends give you a career edge.
Key strategic and tactical questions that determine an
organization’s profitabil-
ity and management performance are shown in Figure 1.23.
Answers to each ques-
tion will entail understanding the capabilities of mundane to
complex ITs, which
ones to implement, and how to manage them.
IT CAREERS OUTLOOK Having a feel for the job market helps
you improve your career options. According
to the U.S. Department of Labor, and the University of
California Los Angeles
(UCLA), the best national jobs in terms of growth,

advancement, and salary
increases in 2013 are in the fields of IT, engineering, health
care, finance, construc-
tion, and management. It is projected that these job categories
will see above-
average national growth over the next several years. The U.S.
Department of Labor
projections are generally 6–10 years in reference.
With big data, data science, and M2M, companies are increasing
their IT staff.
In addition, many new businesses are seeking more
programmers and designers.
Data security threats continue to get worse. The field of IT
covers a wide range that
includes processing of streaming data, data management, big
data analytics, app
development, system analysis, information security, and more.
Job growth is estimated at 53 percent by 2018, according to the
U.S. Department
of Labor; and salaries in many IT jobs will increase by 4 to 6
percent. The lack of
skilled IT workers in the U.S. is a primary reason for the
outsourcing of IT jobs.
Digital Technology Defines and Creates
Businesses and Markets
Digital technology creates markets, businesses, products, and
careers. As you con-
tinue to read this book, you will see that exciting IT
developments are changing how
organizations and individuals do things. New technologies and
IT-supported func-
tions, such as 4G or 5G networks, embedded sensors, on-

demand workforces, and
e-readers, point to ground-breaking changes. CNN.com, one of
the most respected
Figure 1.23 Key strategic
and tactical questions.
Business
processes,
producers,
and technology
Strategic direction;
industry, markets,
and customers
Business model
• What do we do?
• What is our direction?
• What markets & customers should
we be targeting and how do we
prepare for them?
• How do we do it?
• How do we generate revenues &
profits to sustain ourselves and
build our brand?
• How well do we do it?
• How can we be more
efficient?

AM f-w-204a /208/WB01490/9781118897782/ch01/text_s
Key Terms 29
news media, has created a new market whose impacts are yet to
be realized. Visit
iReport.com where a pop-up reads, “iReport is the way people
like you report the
news. The stories in this section are not edited, fact-checked or
screened before
they post.”
IT as a Career: The Nature of IS and IT Work
IT managers play a vital role in the implementation and
administration of digital
technology. They plan, coordinate, and direct research on the
computer-related
activities of firms. In consultation with other managers, they
help determine the
goals of an organization and then implement technology to meet
those goals.
Chief technology officers (CTOs) evaluate the newest and most
innovative
technologies and determine how they can be applied for
competitive advantage.
CTOs develop technical standards, deploy technology, and
supervise workers
who deal with the daily IT issues of the firm. When innovative
and useful new
ITs are launched, the CTO determines implementation
strategies, performs
cost-benefit or SWOT analysis, and reports those strategies to

top management,
including the CIO.
IT project managers develop requirements, budgets, and
schedules for their
firm’s information technology projects. They coordinate such
projects from devel-
opment through implementation, working with their
organization’s IT workers, as
well as clients, vendors, and consultants. These managers are
increasingly involved
in projects that upgrade the information security of an
organization.
IT Job Prospects
Workers with specialized technical knowledge and strong
communications and
business skills, as well as those with an MBA with a
concentration in an IT area, will
have the best prospects. Job openings will be the result of
employment growth and
the need to replace workers who transfer to other occupations or
leave the labor
force (Bureau of Labor Statistics, 2012–2013).
Questions
1. Why is IT a major enabler of business performance and
success?
2. Explain why it is benefi cial to study IT today.
3. Why are IT job prospects strong?
Key Terms
agility
barriers to entry

big data
business model
business process
business process
management (BPM)
business process
reengineering (BPR)
business-to-business
(B2B)
chief technology offi cer
(CTO)
cloud computing
commodity
competitive advantage
competitive forces model
(fi ve-forces model)
critical success factor (CSF)
cross-functional business
process
customer experience (CX)
cycle time
dashboards
data analytics
data science
dashboard
deliverables
digital business model
formal process

inbound logistics
industry structure
informal process
Internet of Things (IoT)
IT consumerization
IT project manager
key performance
indicators (KPIs)
machine-to-machine
(M2M) technology
near-fi eld communication
(NFC) technology
objectives
operations
process
productivity
radio frequency
identifi cation (RFID)
real time system
responsiveness
services
social, mobile, and cloud
(SoMoClo)
standard operating
procedures (SOPs)
supply chain
support activities
SWOT analysis
unstructured data

wearable technology
AM f-w-204a /208/WB01490/9781118897782/ch01/text_s
1. Why are businesses experiencing a digital transfor-
mation?
2. More data are collected in a day now than existed in
the world 10 years ago. What factors have contrib-
uted to this volume of data?
3. Assume you had no smartphone, other mobile de-
vice, or mobile apps to use for 24 hours. How would
that mobile blackout disrupt your ability to function?
4. What were three highly disruptive digital technolo-
gies? Give an example of one disruption for each
technology.
5. Why are enterprises adopting cloud computing?
6. What is the value of M2M technology? Give two
examples.
7. Starbucks monitors tweets and other sources of big
data. How might the company increase revenue
from big data analytics?
8. Select three companies in different industries, such

as banking, retail store, supermarket, airlines, or
package delivery, that you do business with. What
digital technologies does each company use to
engage you, keep you informed, or create a unique
customer experience? How effective is each use of
digital technology to keeping you a loyal customer?
9. Describe two examples of the infl uence of SoMoClo
on the fi nancial industry.
10. What is a potential impact of the Internet of things
on the health-care industry?
11. How could wearable technology be used to create
a competitive edge in the athletic and sportswear
industry?
12. Why does reducing the cycle time of a business
process also help to reduce errors?
13. Research fi rm Gartner defi nes competitive advantage
as a difference between a company and its competi-
tors that matters to customers. Describe one use of
M2M technology that could provide a manufacturer
with a competitive advantage.
14. What IT careers are forecasted to be in high de-
mand? Explain why.
15. Why or how would understanding the latest IT
trends infl uence your career?
DISCUSS: Critical Thinking Questions
16. Research the growing importance of big data ana-

lytics. Find two forecasts of big data growth. What
do they forecast?
17. Go to the U.S. Department of Commerce website
and search for U.S. Economy at a Glance: Perspec-
tive from the BEA Accounts.
a. Review the BEA homepage to learn the types of
information, news, reports, and interactive data
available. Search for the page that identifi es who
uses BEA measures. Identify two users of indus-
try data and two users of international trade and
investment data.
b. Click on the Glossary. Use the Glossary to
explain GDP in your own words.
c. Under the NEWS menu, select U.S. Economy at
a Glance. Review the GDP current numbers for
the last two reported quarters. How did GDP
change in each of these two quarters?
EXPLORE: Online and Interactive Exercises
18. A transportation company is considering investing
in a truck tire with embedded sensors—the Internet
of Things. Outline the benefi ts of this investment.
Would this investment create a long-term competi-
tive advantage for the transportation company?
19. Visit the website of UPS (ups.com), Federal Express
(fedex.com), and one other logistics and delivery
company.
a. At each site, what information is available to

customers before and after they send a package?
b. Compare the three customer experiences.
20. Visit YouTube.com and search for two videos on
Michael Porter’s strategic or competitive forces
models. For each video, report what you learned.
Specify the complete URL, video title, who uploaded
the video and the date, video length, and number of
views.
21. Visit Dell.com and Apple.com to simulate buying a
laptop computer. Compare and contrast the selection
process, degree of customization, and other buying
features. What are the barriers to entry into this mar-
ket, based on what you learned from this exercise?
ANALYZE & DECIDE: Apply IT Concepts to Business
Decisions
AM f-w-204a /208/WB01490/9781118897782/ch01/text_s
CASE 1.2 Business Case 31
CASE 1.2
Business Case: Restaurant Creates Opportunities to Engage
Customers
Back when phones were used only to make calls, few
retailers and restaurants could have predicted that mo-
bile technology was going to transform their industries.
Smartphones and other portable devices are access points
to customers. Companies can push real time, personally

targeted ads to customers’ phones using text messages, or
interact with them using location-aware mobile apps. And
potential customers can access product or brand informa-
tion using 2D codes, and comparison-shop right in the
store.
Brands are always looking for more effective ways
to integrate social media with traditional media, such as
print and TV, when implementing marketing campaigns.
Managing these campaigns and interactions requires
specialized software, and possibly support from the
vendor or consulting firm if the company lacks in-house
expertise.
Pei Wei Asian Diner’s Mobile
and Cloud Campaign
Pei Wei Asian Diner (www.peiwei.com), a fast-food casual
restaurant chain owned by P.F. Chang’s China Bistro, is an
example of a company that invested in technology to
manage multichannel (also called cross-channel) marketing
campaigns. In mid-2011 Pei Wei introduced a new entrée,
Caramel Chicken. The company integrated traditional
in-store promotions with mobile and Web-based
marketing efforts to motivate people to subscribe to
its e-mail marketing campaign. It also reached out to
fans via Facebook and Twitter. The success of the new
campaign depended on investing in appropriate software
and expertise. With thousands of tweets, Facebook posts,
and Google searches per second, companies need IT
support to understand what people are saying about their
brands.
Campaign Management
Software Vendor
Software vendor ExactTarget was selected to run and
manage Pei Wei’s marketing campaigns. Famous brands—
like Expedia, Best Buy, Nike, and Papa John’s—also used

ExactTarget to power their mission-critical messages.
With ExactTarget’s software, Pei Wei invited guests to join
(register) its e-mail list via text, the Web, Twitter, or Face-
book in order to receive a buy-one, get-one free (BOGO)
coupon.
Using ExactTarget’s software and infrastructure, clients
such as Pei Wei can send more than thousands of e-mails per
second and millions of messages in 15 minutes. A massive
infrastructure and architecture are needed to meet the de-
mands of high-volume senders.
Another feature of ExactTarget is the ability to respond in
a real time environment. Companies need to be able to react
to the real time actions that their customers are taking across
all channels. That is why it is necessary to be able to quickly
and easily confi gure messages that are triggered by external
events like purchases or website interactions. Finally, software
helps companies immediately respond to customers with
burst sending capabilities—sending millions of e-mails in a
few minutes.
Why the Campaign Was a Success
Within two weeks, about 20,000 people had responded to
the offer by registering. The BOGO coupon redemption rate
at Pei Wei’s 173 locations was 20 percent. It was the restau-
rant chain’s most successful new e-mail list growth effort to
date.
Effective marketing requires companies or brands to cre-
ate opportunities with which to engage customers. Pei Wei
was successful because it used multiple interactive channels
to engage—connect with—current and potential custom-
ers. Brands have a tremendous opportunity to connect with
consumers on their mobiles in stores and on Twitter and
Facebook.
A 2010 ExactTarget study of more than 1,500 U.S.
consumers entitled The Collaborative Future found that:

• 27 percent of consumers said they are more likely to
purchase from a brand after subscribing to e-mail.
• 17 percent of consumers are more likely to purchase after
liking a brand on Facebook.
A study by Forrester Consulting found that 48 percent
of interactive marketing executives ranked understanding
customers’ cross-channel interactions as one of the top
challenges facing marketing today.
Questions
1. What software capabilities did Pei Wei need to launch its
marketing campaign?
2. What factors contributed to the success of Pei Wei’s
campaign?
3. Why is a high-capacity (massive) infrastructure needed to
launch e-mail or text campaigns?
4. Visit ExactTarget.com. Identify and describe how the
vendor makes it easy for companies to connect via e-mail
and Twitter.
5. What solutions for small businesses does ExactTarget
offer?
AM f-w-204a /208/WB01490/9781118897782/ch01/text_s

CASE 1.3
Video Case: What Is the Value of Knowing More and Doing
More?
Teradata (Teradata.com) is a leading provider of big data
and data analytics solutions. In a video, Teradata explains
that when you know the right thing to do, you can do
more of what truly matters for your business and your
customers. View the video entitled “What Would You Do
If You Knew?”™ at http://www.teradata.com/Resources/
Videos/What-would-you-do-if-you-knew/
Questions
1. What did you learn from the video?
2. What is the value of knowing and doing more?
Accenture Technology Vision 2013.
Alesci, C. & S. Saitto. “AutoTrader.Com Said to Be in Talks
About Possible IPO of Buyer-Seller Site.” Bloomberg,
February 4, 2012.
Bureau of Labor Statistics. Occupational Outlook Handbook.
U.S. Department of Labor, 2012–2013.
Central Intelligence Agency (CIA). World Factbook.
Cooper, B. B. “10 Surprising Social Media Statistics That Will
Make You Rethink Your Social Strategy.” Fast Company,
November 18, 2013.
Davenport, T.H. & D.J. Patil. “Data Scientist: The Sexiest Job
of the 21st Century.” Harvard Business Review Magazine.

October 2012.
“Gartner Reveals Top Predictions for IT Organizations and
Users for 2013 and Beyond.” Gartner Newsroom. October 24,
2012.
glassdoor.com. “Data Analyst Salaries.” May 8, 2014.
Gnau, S. “Putting Big Data in Context.” Wired, September 10,
2013.
Joy, O. “What Does It Mean to Be a Digital Native?” CNN,
December 8, 2012.
Kelly, M. “Data Scientists Needed: Why This Career Is
Exploding Right Now.” VentureBeat.com, November 11, 2013.
Lockard, C.B. & M. Wolf. “Occupational Employment Projec-
tions to 2020.” Monthly Labor Review, January 2012.
McCain Foods. “McCain Foods: Integrating Data from the
Plant to the Boardroom to Increase the Bottom Line.”
Teradata.com, 2013.
NFC World. “News in Brief.” February 2014.
Pogue, D. “Embracing the Mothers of Invention.” The New
York Times, January 25, 2012.
Porter, M. E. The Competitive Advantage: Creating and
Sustaining
Superior Performance. NY: Free Press. 1985.
Porter, M. E. “Strategy and the Internet.” Harvard Business
Review, March 2001.

Schmidt-Subramanian, M., H. Manning, J. Knott, & M. Murphy.
“The Business Impact of Customer Experience, 2013.” For-
rester Research, June 10, 2013.
Smith, Gavin. “Frozen Food Production in the US Industry
Market Research Report from IBISWorld Has Been Updated.”
PRWeb, March 27, 2013.
softwareag.com. “Orders Are in the Fast Lane at AutoTrader.
com—Thanks to BPM.” 2011.
Transparency Market Research. “Frozen Food Market—Global
Industry Analysis, Size, Share, Growth, Trends and Forecast,
2013–2019.” September 2013.
U.S. Department of Labor, Bureau of Labor Statistics. 2014.
Walsh, M. “Autotrader.com Tops In Local Online Ad Dollars.”
MediaPost.com, April 3, 2012.
References
PM f-392 /208/WB01490/9781118897782/ch01/text_s
Chapter Snapshot
High performance is about outperforming rivals again
and again, even as the basis of competition in an indus-
try changes. Markets do not stand still and the basis of
competition is changing at a faster pace. By the time a
company’s financial performance starts tapering off, it
might be too late to start building new market-relevant
capabilities. To stay ahead, today’s leaders seek out new

ways to grow their businesses during rapid technology
changes, more empowered consumers and employees,
and more government intervention.
Effective ways to thrive over the long term are to
launch new business models and strategies or devise new
ways to outperform competitors. In turn, these perfor-
mance capabilities depend on a company’s enterprise IT
Data Governance and
IT Architecture Support
Long-Term Performance2
Chapter
1. Explain the business benefits of information management
and how data quality determines system success or failure.
2. Describe how enterprise architecture (EA) and data
governance play leading roles in guiding IT growth and
sustaining long-term performance.
3. Map the functions of various types of information
systems to the type of support needed by business
operations and decision makers.
4. Describe the functions of data centers, cloud computing,
and virtualization and their strengths, weaknesses, and
cost considerations.
5. Explain the range of cloud services, their benefits, and
business and legal risks that they create.
Learning Outcomes

33
Chapter Snapshot
Case 2.1 Opening Case: Detoxing Dirty Data
with Data Governance at Intel Security
2.1 Information Management
2.2 Enterprise Architecture and Data
Governance
2.3 Information Systems: The Basics
2.4 Data Centers, Cloud Computing, and
Virtualization
2.5 Cloud Services Add Agility
Key Terms
• Discuss: Critical Thinking Questions
• Explore: Online and Interactive Exercises
• Analyze & Decide: Apply IT Concepts
to Business Decisions
Case 2.2 Business Case: Data Chaos Creates Risk
Case 2.3 Video Case: Cloud Computing:
Three Case Studies
References
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architecture and data governance. The enterprise IT archi-
tecture, or simply the enterprise architecture (EA), guides
the evolution and expansion of information systems,
digital technology, and business processes. This guide is
needed in order to leverage IT capability for competitive
advantage and growth. Data governance, or information
governance, is the control of enterprise data through for-
mal policies and procedures. A goal of data governance
is to provide employees and business partners with high-
quality data they trust and can access on demand.
CASE 2.1 OPENING CASE
Detoxing Dirty Data with Data Governance at Intel Security
COMPANY OVERVIEW
CUSTOMER-CENTRIC
BUSINESS MODEL
Intel Security protects data and IT resources from attack and
unauthorized access.
The company provides cybersecurity services to large
enterprises, governments,
small- and medium-sized businesses, and consumers. A
significant portion of its
revenues comes from postsales service, support, and
subscriptions to its software
and managed services. The company sells directly and also
through resellers to
corporations and consumers in the United States, Europe, Asia,
and Latin America.
Intel Security management recognized that it needed to

implement a best-practices
customer-centric business model. In the fiercely competitive
industry, the ability
to connect with customers, anticipate their needs, and provide
flawless customer
service is essential to loyalty and long-term growth. Why?
Mostly because social
and mobile technology is forcing businesses to offer excellent
customer experiences
(CX) across every available touchpoint, including chat, video,
mobile apps, and
alerts (Figure 2.2). A touchpoint is “any influencing action
initiated through com-
munication, human contact or physical or sensory interaction”
(De Clerck, 2013).
Most customers search for and exchange detailed information
about the good
and bad of their encounters with companies. (You will read
about Yelp and the
34
Customer-centric business
models strive to create the
best solution or experience
for the customer. In contrast,
product-centric models are
internally focused on creating
the best product.
TABLE 2.1 Opening Case Overview
Company McAfee was renamed Intel Security in 2014. It is a
sub-
sidiary of Intel Corp. headquartered in Santa Clara, CA.

Has more than $2 billion in revenues annually, over 7,600
employees, and over 1 million customers.
Industry Cybersecurity software, hardware, and services.
Product lines The company develops, markets, distributes, and
supports
cybersecurity products that protect computers, networks,
and mobile devices. They offer managed security services
to protect endpoints, servers, networks, and mobile devices.
Consulting, training and support services are also provided.
Digital technology Data governance and master data
management (MDM) in
order to build a best-in-class customer data management
capability to facilitate the company’s vision.
Business vision To become the fastest-growing dedicated
security
company in the world.
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BUSINESS CHALLENGES
FROM POOR-QUALITY
CUSTOMER DATA
Intel Security is following a growth-driven business strategy.
Its vision is to become
the fastest-growing dedicated security company in the world.

Management rec-
ognized that accurate customer data are the foundation of top-
notch customer
service. But, they faced a common business problem—poor-
quality customer data.
Characteristics of poor-quality data, also known as dirty data,
are listed in Table 2.2.
Duplicate customer records and incomplete customer data were
harming
sales. The company could not effectively cross-sell (sell
complementary products
or services) or up-sell (sell more expensive models or features).
Opportunities to
get customers to renew their software licenses—and keep them
loyal—were being
lost. Data errors degraded sales forecasts and caused order-
processing mistakes.
Time was wasted trying to find, validate, and correct customer
records and manu-
ally reconcile month-end sales and calculate sales commissions.
Until the causes of
dirty data were identified and corrected, the growth strategy
could not be achieved.
Dirty data are data of such
poor quality that they cannot
be trusted or relied upon for
decisions.
Figure 2.2 Providing
excellent service to
customers via their preferred
touchpoints, such as online
chat, has never been more
important as consumers use

social media to rate brands,
expose bad service, and vent
their frustrations.
Intel Security
(formerly McAfee, Inc.)
Data governance
Master data management (MDM)
Digital Technology
Delivers proactive cybersecurity
solutions and services for
information systems, networks,
and mobile devices around the
world.
Brand Aligned Data
Management with
Business Strategy
Implemented data governance to
build a best-in-class customer data
management capability in order to
achieve the company’s strategic
vision.
Figure 2.1 Intel Security overview.
United Breaks Guitar video in Chapter 7.) This transparency
gives companies a
strong incentive to work harder to make customers happy
before, during, and after
their purchases.

By creating a customer-centric business model, Intel Security
can track what is
working for its customers and what is not. Using digital
technology and data analytics
to understand customer touchpoints would enable the company
to connect with
customers in meaningful ways. Committing to a better
experience for customers can
increase revenue and promote loyalty—and achieve the
company’s growth objective.
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TermPerformance.indd Page 35 07/11/14 4:15 PM f-392
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36 Chapter 2 Data Governance and IT Architecture Support
TABLE 2.2 Characteristics of Poor-Quality or Dirty Data
Characteristic of Dirty Data Description
Incomplete Missing data.
Outdated or invalid Too old to be valid or useful.
Incorrect Too many errors.
Duplicated or in confl ict Too many copies or versions of the

same
data—and the versions are inconsistent or in
confl ict with each other.
Nonstandardized Data are stored in incompatible formats—and
cannot be compared or summarized.
Unusable Data are not in context to be understood or
interpreted correctly at the time of access.
DATA QUALITY
SOLUTION: DATA
GOVERNANCE
Working with consulting company First San Francisco Partners,
Intel Security
planned and implemented data governance and master data
management (MDM).
Master data are the business-critical information on customers,
products, accounts,
and other things that is needed for operations and business
transactions. Master
data were stored in disparate systems spread across the
enterprise. MDM would
link and synchronize all critical data from those disparate
systems into one file,
called a master file, that provided a common point of reference.
Data governance
and MDM manage the availability, usability, integrity, and
security of the data used
throughout the enterprise. Intel Security’s data governance
strategy and MDM
were designed after a thorough review of its 1.3 million
customer records, sales
processes, and estimated future business requirements.

BENEFITS OF DATA
GOVERNANCE AND
MDM
Data governance and MDM have improved the quality of Intel
Security’s customer
data, which were essential for its customer-centric business
model. With high-quality
data, the company is able to identify up-sell and cross-sell sales
opportunities. Best
practices for customer data management improved customer
experiences that
translated into better customer retention and acquisition. The
key benefits achieved
after implementing data governance and the MDM architecture
to improve data
quality are:
• Better customer experience
• Greater customer loyalty and retention
• Increased sales growth
• Accurate sales forecasts and order processing
Intel Security has successfully aligned its IT capabilities to
meet business needs. All
these efforts benefit the business by improving productivity as a
result of reduced
data-cleansing efforts, and by increasing sales as a result of
better customer experi-
ences.
Sources: Compiled from mcafee.com (2013), De Clerck, (2013),
First San Francisco Partners (2009), and

Rich (2013).
Data governance is the
control of enterprise data
through formal policies and
procedures to help ensure
that data can be trusted and
are accessible.
Master data management
(MDM) methods synchronize
all business-critical data from
disparate systems into a
master file, which provides
a trusted data source.
/208/WB01490/9781118897782/ch02/text_s
Questions
1. What is the difference between customer-centric and
product-centric
business models?
2. Explain the business challenges caused by Intel Security’s
dirty data.
3. What is the function of data governance?
4. Describe the function of master data.
5. Why is it important to keep data synchronized across
disparate systems?
6. Why did Intel Security need master data management

(MDM)?
7. How did MDM and data governance enable the company to
achieve its
vision?
8. What benefi ts did the company achieve as a result of
implementing
data governance and MDM?
Most business initiatives succeed or fail based on the quality of
their data. Effective
planning and decisions depend on systems being able to make
data available to
decision makers in usable formats on a timely basis. Most
everyone manages infor-
mation. You manage your social and cloud accounts across
multiple mobile devices
and computers. You update or synchronize (“synch”) your
calendars, appoint-
ments, contact lists, media files, documents, and reports. Your
productivity depends
on the compatibility of devices and apps and their ability to
share data. Not being
able to transfer and synch whenever you add a device or app is
bothersome and
wastes your time. For example, when you switch to the latest
mobile device, you
might need to reorganize content to make dealing with data and
devices easier. To
simplify add-ons, upgrades, sharing, and access, you might
leverage cloud services
such as iTunes, Instagram, Diigo, and Box.
This is just a glimpse of the information management situations
that organiza-

tions face today—and why a continuous plan is needed to guide,
control, and govern
IT growth. As with building construction (Figure 2.3),
blueprints and models help
guide and govern future IT and digital technology investments.
2.1 Information Management
Information management is
the use of IT tools and
methods to collect, process,
consolidate, store, and
secure data from sources that
are often fragmented and
inconsistent.
INFORMATION
MANAGEMENT
HARNESSES SCATTERED
DATA
Business information is generally scattered throughout an
enterprise, stored in
separate systems dedicated to specific purposes, such as
operations, supply chain
management, or customer relationship management. Major
organizations have over
100 data repositories (storage areas). In many companies, the
integration of these
disparate systems is limited—as is users’ ability to access all
the information they
Figure 2.3 Blueprints and
models, like those used for
building construction, are
needed to guide and govern

an enterprise’s IT assets. ©
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/208/WB01490/9781118897782/ch02/text_s
need. Therefore, despite all the information flowing through
companies, executives,
managers, and workers often struggle to find the information
they need to make
sound decisions or do their jobs. The overall goal of
information management is to
eliminate that struggle through the design and implementation
of data governance

and a well-planned enterprise architecture.
Providing easy access to large volumes of information is just
one of the chal-
lenges facing organizations. The days of simply managing
structured data are over.
Now, organizations must manage semistructured and
unstructured content from
social and mobile sources even though that data may be of
questionable quality.
Information management is critical to data security and
compliance with con-
tinually evolving regulatory requirements, such as the Sarbanes-
Oxley Act, Basel III,
the Computer Fraud and Abuse Act (CFAA), the USA PATRIOT
Act, and the
Health Insurance Portability and Accountability Act (HIPAA).
Issues of information access, management, and security must
also deal with
information degradation and disorder—where people do not
understand what data
mean or how they can be useful.
REASONS FOR
INFORMATION
DEFICIENCIES
Companies’ information and decision support technologies have
developed over
many decades. During that time span, there have been different
management teams
with their own priorities and understanding of the role of IT;
technology advanced
in unforeseeable ways, and IT investments were cut or increased

based on compet-
ing demands on the budget. These are some of the contributing
factors. Other com-
mon reasons why information deficiencies are still a problem
include:
1. Data silos. Information can be trapped in departments’ data
silos (also called
information silos), such as marketing or production databases.
Data silos are
illustrated in Figure 2.4. Since silos are unable to share or
exchange data, they
cannot consistently be updated. When data are inconsistent
across multiple
enterprise applications, data quality cannot (and should not) be
trusted without
extensive verifi cation. Data silos exist when there is no overall
IT architecture
to guide IS investments, data coordination, and communication.
Data silos sup-
port a single function and, as a result, do not support an
organization’s cross-
functional needs.
For example, most health-care organizations are drowning in
data, yet they
cannot get reliable, actionable insights from these data.
Physician notes, regis-
tration forms, discharge summaries, documents, and more are
doubling every
five years. Unlike structured machine-ready data, these are
messy data that take
Data silos are stand-alone
data stores. Their data are
not accessible by other ISs

that need it or outside that
department.
Information Requirements:
Understandable
Relevant
Timely
Accurate
Secure
Parts Replenish
Procuring
Design
Build
Ship
Sales
Fulfillment
Billing
Support
Customer data
Product data
Procurement data
Contract data
Data order
Parts inventory data
Engineering data
Logistics data

Data Types
Operations
silos
Sourcing
silos
Customer-facing
silos
Figure 2.4 Data (or
information) silos are ISs that
do not have the capability to
exchange data with other ISs,
making timely coordination
and communication across
functions or departments
diffi cult.
/208/WB01490/9781118897782/ch02/text_s
too much time and effort for health-care providers to include in
their business
analysis. So, valuable messy data are routinely left out. Millions
of patient notes
and records sit inaccessible or unavailable in separate clinical
data silos because
historically there has been no easy way to analyze the

information.
2. Lost or bypassed data. Data can get lost in transit from one
IS to another. Or,
data might never get captured because of inadequately tuned
data collection
systems, such as those that rely on sensors or scanners. Or, the
data may not get
captured in suffi cient enough detail, as described in Tech Note
2.1.
3. Poorly designed interfaces. Despite all the talk about user-
friendly interfaces,
some ISs are horrible to deal with. Poorly designed interfaces or
formats that
require extra time and effort to fi gure out increase the risk of
errors from misun-
derstanding the data or ignoring them.
4. Nonstandardized data formats. When users are presented
with data in inconsis-
tent or nonstandardized formats, errors increase. Attempts to
compare or ana-
lyze data are more diffi cult and take more time. For example, if
the Northeast
division reports weekly gross sales revenues per product line
and the South-
west division reports monthly net sales per product, you cannot
compare their
performance without converting the data to a common format.
Consider the
extra effort needed to compare temperature-related sales, such
as air condition-
ers, when some temperatures are expressed in degrees
Fahrenheit and others in
Centigrade.

5. Cannot hit moving targets. The information that decision
makers want keeps
changing—and changes faster than ISs can respond to because
of the fi rst four
reasons in this list. Tracking tweets, YouTube hits, and other
unstructured con-
tent requires expensive investments—which managers fi nd
risky in an economic
downturn.
Without information management, these are the data challenges
managers
have to face. Companies undergoing fast growth or merger
activity or those with
decentralized systems (each division or business unit manages
its own IT) will end
up with a patchwork of reporting processes. As you would
expect, patchwork sys-
tems are more complicated to modify, too rigid to support an
agile business, and yet
more expensive to maintain.
TECH NOTE 2.1 Need to Measure in Order to Manage
A residential home construction company had two divisions:
standard homes and
luxury homes. The company was not capturing material, labor,
and other costs
associated with each type of construction. Instead, these costs
were pooled, making
it impossible to allocate costs to each type of construction and
then to calculate the
profi t margins of each division. They had no way of calculating
profi t margins on
each type of home within the divisions. Without the ability to

measure costs, they did
not have any cost control.
After upgrading their ISs, they began to capture detailed data at
the house level.
They discovered a wide profi t margin on standard homes,
which was hiding the nega-
tive margins (losses) of the luxury home division. Without cost
control data, the prof-
itable standard homes division had been subsidizing the luxury
home division for
many years.
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Executives at a large chemical corporation were supported
by an information system specifically designed for their
needs—called an executive information system (EIS). The
EIS was designed to provide senior managers with internal
and external data and key performance indicators (KPIs)
that were relevant to their specific needs. Tech Note 2.2
describes KPIs. As with any system, the value of the EIS
depends on the data quality.
Too Much Irrelevant Data
The EIS was a failure. Executives found that only half of
the data available through the EIS related to their level of
analysis and decision making—the corporate level. A worse
problem was that the data they needed were not available

when and how they wanted them. For example, executives
needed current detailed sales revenue and cost data for
every strategic business unit (SBU), product line, and operat-
ing business. Sales and cost data were needed for analysis
and to compare performance. But, data were not in stan-
dardized format as is needed for accurate comparisons and
analysis. A large part of the problem was that SBUs reported
sales revenues in different time frames (e.g., daily, weekly,
monthly, or quarterly), and many of those reports were not
available because of delays in preparing them. As a result,
senior management could not get a trusted view of the com-
pany’s current overall performance and did not know which
products were profitable.
There were two reasons for the failure of the EIS:
1. IT architecture was not designed for customized
reporting. The design of the IT architecture had been
based on financial accounting rules. That is, the data
were organized to make it easy to collect and consolidate
the data needed to prepare financial statements and
reports that had to be submitted to the SEC (Securities
and Exchange Commission) and other regulatory agen-
cies. These statements and reports have well-defined or
standardized formats and only need to be prepared at
specific times during the year, typically annually or quar-
terly. The organization of the data (for financial reporting)
did not have the flexibility needed for the customized ad
hoc (unplanned) data needs of the executives. For exam-
ple, it was nearly impossible to generate customized
sales performance (nonfinancial) reports or do ad hoc
analyses, such as comparing inventory turnover rates by
product for each region for each sales quarter. Because
of lags in reports from various SBUs, executives did not
trust the underlying data.

2. Complicated user interface. Executives could not easily
review the KPIs. Instead, they had to sort through screens
packed with too much data—some of interest and some
irrelevant. To compensate for poor interface design, sev-
eral IT analysts themselves had to do the data and KPI
analyses for the executives—delaying response time and
driving up the cost of reporting.
Solution
: New Enterprise IT Architecture
with Standardized Data Formats
The CIO worked with a task force to design and implement
an entirely new EA. Data governance policies and proce-
dures were implemented to standardize data formats com-
panywide. Data governance eliminated data inconsistencies
to provide reliable KPI reports on inventory turns, cycle
times, and profit margins of all SBUs.
The new architecture was business-driven instead of
financial reporting-driven. It was easy to modify reports—
eliminating the costly and time-consuming ad hoc analyses.
Fewer IT resources are needed to maintain the system.
Because the underlying data are now relatively reliable, EIS

use by executives increased significantly.
Questions
1. Why was an EIS designed and implemented?
2. What problems did executives have with the EIS?
3. What were the two reasons for those EIS problems?
4. How did the CIO improve the EIS?
5. What are the benefits of the new IT architecture?
6. What are the benefits of data governance?
IT at Work 2 .1
Data Quality Determines Systems Success and Failure
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TECH NOTE 2.2 KPIs
KPIs are performance measurements. These measures

demonstrate the effective-
ness of a business process at achieving organizational goals.
KPIs present data in
easy-to-comprehend and comparison-ready formats. Examples
of key comparisons
are actual vs. budget, actual vs. forecasted, and this year vs.
prior years. KPIs help
reduce the complex nature of organizational performance to a
small number of
understandable measures, including:
• Financial KPIs: current ratio; accounts payable turnover;
inventory turn-
over; net profit margin
• Social media KPIs: social traffic and conversions (number of
visitors who
are converted to customers); likes; new followers per week;
social visits and
leads
• Sales and marketing KPIs: cost per lead; how much revenue a
marketing
campaign generates

• Operational and supply chain KPIs: units per transaction;
carrying cost of
inventory; order status; back order rate
• Environmental and carbon-footprint KPIs: energy, water, or
other resource
use; spend by utility; weight of landfill waste
FACTORS DRIVING
THE SHIFT FROM SILOS
TO SHARING AND
COLLABORATION
BUSINESS BENEFITS
OF INFORMATION
MANAGEMENT
Senior executives and managers know about their data silos and
information
management problems, but they also know about the huge cost
and disruption
associated with converting to newer IT architectures. A Tech
CEO Council Report
estimated that Fortune 500 companies waste $480 billion every
year on inefficient

business processes (techceocouncil.org, 2010). However,
business process improve-
ments are being made. An IBM study of more than 3,000 CIOs
showed that more
than 80 percent plan to simplify internal processes, which
includes integrated siloed
global applications (IBM Institute, 2011). Companies are
struggling to integrate
thousands of siloed global applications, while aligning them to
business operations.
To remain competitive, they must be able to analyze and adapt
their business pro-
cesses quickly, efficiently and without disruption.
Greater investments in collaboration technologies have been
reported by the
research firm Forrester (Keitt, 2011). The three factors that
Forrester identified as
driving the trend toward collaboration and data sharing
technology are shown in
Figure 2.5.
Based on the examples you have read, the obvious benefits of
information manage-
ment are the following:

1. Improves decision quality. Decision quality depends on
accurate and complete
data.
2. Improves the accuracy and reliability of management
predictions. It is essential
for managers to be able to predict sales, product demand,
opportunities, and
competitive threats. Management predictions focus on “what is
going to happen”
as opposed to fi nancial reporting on “what has happened.”
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3. Reduces the risk of noncompliance. Government regulations
and compliance
requirements have increased signifi cantly in the past decade.

Companies that
fail to comply with laws on privacy, fraud, anti-money
laundering, cybersecurity,
occupational safety, and so on face harsh penalties.
4. Reduces the time and cost of locating and integrating relevant
information.
Figure 2.5 Factors that
are increasing demand for
collaboration technology.
Questions
1. Explain information management.
2. Why do organizations still have information defi ciency
problems?
3. What is a data silo?
4. Explain KPIs and give an example.
5. What three factors are driving collaboration and information
sharing?
6. What are the business benefi ts of information management?
Every enterprise has a core set of information systems and
business processes
that execute the transactions that keep it in business.

Transactions include
processing orders, order fulfillment and delivery, purchasing
inventory and sup-
plies, hiring and paying employees, and paying bills. The
enterprise architecture
(EA) helps or impedes day-to-day operations and efforts to
execute business
strategy.
Success of EA and data governance is measured in financial
terms of prof-
itability and return on investment (ROI), and in the nonfinancial
terms of
improved customer satisfaction, faster speed to market, and
lower employee
turnover.
2.2 Enterprise Architecture and Data Governance
MAINTAINING IT–
BUSINESS ALIGNMENT
As you read in Chapter 1, the volume, variety, and velocity of
data being collected
or generated have grown exponentially. As enterprise

information systems become
more complex, the importance of long-range IT planning
increases dramatically.
Companies cannot simply add storage, new apps, or data
analytics on an as-needed
basis and expect those additions to work with the existing
systems.
62% of the workforce works
outside an office at some
point. This number is
increasing.
Global, mobile
workforce
Growing number of cloud
collaboration services
Mobility-driven
consumerization
Growing need to connect
anybody, anytime, anywhere
on any device

Principle of “any”
Enterprise architecture (EA)
is the way IT systems and
processes are structured. EA
is an ongoing process of cre-
ating, maintaining, and lever-
aging IT. It helps to solve two
critical challenges: where an
organization is going and
how it will get there.
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The relationship between complexity and planning is easier to
see in physical
things such as skyscrapers and transportation systems. If you
are constructing a

simple cabin in a remote area, you do not need a detailed plan
for expansion or
to make sure that the cabin fits into its environment. If you are
building a simple,
single-user, nondistributed system, you would not need a well-
thought-out growth
plan either. Therefore, it is no longer feasible to manage big
data, content from
mobiles and social networks, and data in the cloud without the
well-designed set of
plans, or blueprint, provided by EA. The EA guides and controls
software add-ons
and upgrades, hardware, systems, networks, cloud services, and
other digital tech-
nology investments.
ONGOING PROCESS
OF LEVERAGING IT
According to consulting firm Gartner, enterprise architecture is
the ongoing process
of creating, maintaining, and leveraging IT. It helps to solve
two critical challenges:
where an organization is going and how it will get there.

Shared Vision of the Future
EA has to start with the organization’s target–where it is
going—not with where it is.
Gartner recommends that an organization begin by identifying
the strategic direc-
tion in which it is heading and the business drivers to which it
is responding. The
goal is to make sure that everyone understands and shares a
single vision. As soon
as managers have defined this single shared vision of the future,
they then consider
the implications of this vision on the business, technical,
information, and solutions
architectures of the enterprise. The shared vision of the future
will dictate changes
in all these architectures, assign priorities to those changes, and
keep those changes
grounded in business value.
Strategic Focus
There are two problems that the EA is designed to address:
1. IT systems’ complexity. IT systems have become

unmanageably complex and
expensive to maintain.
2. Poor business alignment. Organizations fi nd it diffi cult to
keep their increasingly
expensive IT systems aligned with business needs.
Business and IT Benefits of EA
Having the right architecture in place is important for the
following reasons:
• EA cuts IT costs and increases productivity by giving decision
makers access
to information, insights, and ideas where and when they need
them.
• EA determines an organization’s competitiveness, flexibility,
and IT eco-
nomics for the next decade and beyond. That is, it provides a
long-term view
of a company’s processes, systems, and technologies so that IT
investments
do not simply fulfill immediate needs.

• EA helps align IT capabilities with business strategy—to
grow, innovate,
and respond to market demands, supported by an IT practice
that is 100
percent in accord with business objectives.
• EA can reduce the risk of buying or building systems and
enterprise apps
that are incompatible or unnecessarily expensive to maintain
and integrate.
Basic EA components are listed and described in Table 2.3. IT
at Work 2.2 describes
Gartner’s view of EA.
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TABLE 2.3 Components of Enterprise Architecture

Business architecture The processes the business uses to meet
its goals.
Application architecture How specifi c applications are
designed and how they
interact with each other.
Data architecture How an enterprise’s data stores are organized
and
accessed.
Technical architecture The hardware and software
infrastructure that
supports applications and their interactions.
In order to keep IT and business in alignment, the EA must
be a dynamic plan. As shown in the model in Figure 2.6, the
EA evolves toward the target architecture, which represents
the company’s future IT needs. According to this model, EA
defines the following:
1. The organization’s mission, business functions, and future
direction

2. Information and information flows needed to perform the
mission
3. The current baseline architecture
4. The desired target architecture
5. The sequencing plan or strategy to progress from the
baseline to the target architecture.
IT at Work 2 .2
EA Is Dynamic
Figure 2.6 The importance of viewing EA as a
dynamic and evolving plan. The purpose of the EA is
to maintain IT–business alignment. Changes in priorities
and business are refl ected in the target architecture to
help keep IT aligned with them (GAO, 2010).
Baseline Transition Target
Im
p
le
m

en
ta
ti
o
n
S
ta
tu
s
Baseline architecture
Sequencing plan
Target architecture
Essential Skills of an Enterprise Architect
Enterprise architects need much more than technol-
ogy skills. The job performance and success of such

an architect—or anyone responsible for large-scale IT
projects—depend on a broad range of skills.
• Interpersonal or people skills. The job requires inter-
acting with people and getting their cooperation.
• Ability to influence and motivate. A large part of
the job is motivating users to comply with new pro-
cesses and practices.
• Negotiating skills. The project needs resources—
time, money, and personnel—that must be negoti-
ated to get things accomplished.
CAREER INSIGHT 2 . 1
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• Critical-thinking and problem-solving skills. Architects

face complex and unique problems. Being able to
expedite solutions prevents bottlenecks.
• Business and industry expertise. Knowing the busi-
ness and industry improves the outcomes and the
architect’s credibility.
Managing EA implementations requires someone who
is able to handle multiple aspects of a project at one
time. Project management is covered in Chapter 13.
DATA GOVERNANCE:
MAINTAINING DATA
QUALITY AND COST
CONTROL
Data governance is the process of creating and agreeing to
standards and require-
ments for the collection, identification, storage, and use of data.
The success of
every data-driven strategy or marketing effort depends on data
governance. Data
governance policies must address structured, semistructured,
and unstructured data
(discussed in Section 2.3) to ensure that insights can be trusted.

Enterprisewide Data Governance
With an effective data governance program, managers can
determine where their
data are coming from, who owns them, and who is responsible
for what—in order
to know they can trust the available data when needed. Data
governance is an
enterprise-wide project because data cross boundaries and are
used by people
throughout the enterprise. New regulations and pressure to
reduce costs have increased
the importance of effective data governance. Governance
eliminates the cost of
maintaining and archiving bad, unneeded, or wrong data. These
costs grow as the
volume of data grows. Governance also reduces the legal risks
associated with
unmanaged or inconsistently managed information.
Three industries that depend on data governance to comply with
regulations or
reporting requirements are the following:

• Food industry. In the food industry, data governance is
required to comply
with food safety regulations. Food manufacturers and retailers
have sophis-
ticated control systems in place so that if a contaminated food
product, such
as spinach or peanut butter, is detected, they are able to trace
the problem
back to a particular processing plant or even the farm at the
start of the food
chain.
• Financial services industry. In the financial services sector,
strict report-
ing requirements of the Dodd–Frank Wall Street Reform and
Consumer
Protection Act of 2010 are leading to greater use of data
governance. The
Dodd–Frank Act regulates Wall Street practices by enforcing
transparency
and accountability in an effort to prevent another significant
financial crisis
like the one that occurred in 2008.
• Health-care industry. Data are health care’s most valuable

asset. Hospitals
have mountains of electronic patient information. New health-
care account-
ability and reporting obligations require data governance
models for trans-
parency to defend against fraud and to protect patients’
information.
As you read in the Intel Security opening case, data governance
and MDM are
a powerful combination. As data sources and volumes continue
to increase, so does
the need to manage data as a strategic asset in order to extract
its full value. Making
business data consistent, trusted, and accessible across the
enterprise is a critical
first step in customer-centric business models. With data
governance, companies
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are able to extract maximum value from their data, specifically
by making better
use of opportunities that are buried within behavioral data.
According to Adele
Pugliese, data governance director of Toronto-based Scotiabank,
“If we are able
to leverage and understand the data, and achieve integrity and a
level of accuracy
with that data, in terms of our touchpoints with the customers,
we should be able to
change that customer experience and take it to the next level
where we know a lot
more about our customers” (Hamilton, 2013).
Master Data and MDM
Master data describe key entities such as customers, products
and services, vendors,
locations, and employees around which business is conducted.
Master data are typi-
cally quite stable—and fundamentally different from the high
volume, velocity, and

variety of big data and traditional data. For example, when a
customer applies for
automobile insurance, data provided on the application become
the master data
for that customer. In contrast, if the customer’s vehicle has a
device that sends data
about his or her driving behavior to the insurer, those machine-
generated data are
transactional or operational, but not master data.
Data are used in two ways—both depend on high-quality
trustworthy data:
1. For running the business: Transactional or operational use
2. For improving the business: Analytic use
Strong data governance is needed to manage the availability,
usability, integrity,
and security of the data used throughout the enterprise so that
data are of sufficient
quality to meet business needs. The characteristics and
consequences of weak or
nonexistent data governance are listed in Table 2.4.

MDM solutions can be complex and expensive. Given their
complexity and
cost, most MDM solutions are out of reach for small and
medium companies.
Vendors have addressed this challenge by offering cloud-
managed MDM ser-
vices. For example, in 2013 Dell Software launched its next-
generation Dell Boomi
MDM. Dell Boomi provides MDM, data management, and data
quality services
(DQS)—and they are 100 percent cloud-based with near real
time synchronization.
Politics: The People Conflict
In an organization, there may be a culture of distrust between
the technology and
business employees. No enterprise architecture methodology or
data governance
can bridge this divide unless there is a genuine commitment to
change. That com-
mitment must come from the highest level of the organization—
senior management.
Methodologies cannot solve people problems; they can only
provide a framework in

which those problems can be solved.
TABLE 2.4 Characteristics and Consequences of Weak or
Nonexistent
Data Governance
• Data duplication causes isolated data silos.
• Inconsistency exists in the meaning and level of detail of data
elements.
• Users do not trust the data and waste time verifying the data
rather than
analyzing them for appropriate decision making.
• Leads to inaccurate data analysis.
• Bad decisions are made on perception rather than reality,
which can negatively
affect the company and its customers.
• Results in increased workloads and processing time.
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Questions
1. Explain the relationship between complexity and planning.
Give an
example.
2. Explain enterprise architecture.
3. What are the four components of EA?
4. What are the business benefi ts of EA?
5. How can EA maintain alignment between IT and business
strategy?
6. What are the two ways that data are used in an organization?
7. What is the function of data governance?
8. Why has interest in data governance and MDM increased?
9. What role does personal confl ict or politics play in the
success of data
governance?
Information systems (ISs) are built to achieve specific goals,
such as processing cus-
tomer orders and payroll. In general, ISs process data into
meaningful information

and knowledge.
2.3 Information Systems: The Basics
DATA, INFORMATION,
AND KNOWLEDGE
Data, or raw data, describe products, customers, events,
activities, and transactions
that are recorded, classified, and stored. Data are the raw
material from which
information is produced; the quality, reliability, and integrity of
the data must be
maintained for the information to be useful. Examples are the
number of hours an
employee worked in a certain week or the number of new
Toyota vehicles sold in
the first quarter of 2015.
A database is a repository or data store that is organized for
efficient access,
search, retrieval, and update.
Information is data that have been processed, organized, or put
into context

so that they have meaning and value to the person receiving
them. For example,
the quarterly sales of new Toyota vehicles from 2010 through
2014 is information
because it would give some insight into how the vehicle recalls
during 2009 and 2010
impacted sales. Information is an organization’s most important
asset, second only
to people.
Knowledge consists of data and/or information that have been
processed,
organized, and put into context to be meaningful, and to convey
understanding,
experience, accumulated learning, and expertise as they apply to
a current problem
or activity. Knowing how to manage a vehicle recall to
minimize negative impacts
on new vehicle sales is an example of knowledge. Figure 2.7
shows the differences
in data, information, and knowledge.
ISs collect or input and process data, distribute reports or other
outputs that
support decision making and business processes. Figure 2.8

shows the input-
processing-output (IPO) model.
Figure 2.9 shows how major types of ISs relate to one another
and how data
flow among them. In this example,
1. Data from online purchases are captured and processed by the
TPS, or transac-
tion processing system and then stored in the transactional
database.
2. Data needed for reporting purposes are extracted from the
database and used
by the MIS (management information system) to create
periodic, ad hoc, or
other types of reports.
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Figure 2.7 Examples of data,
information, and knowledge.
Figure 2.8 Input-processing-
output model.
Figure 2.9 Flow of data
from the point of sale (POS)
through processing, storage,
reporting, decision support,
and analysis. Also shows
the relationships among
information systems.
Q1-
2008 2008
Q2-
2008
Q3-
2008
Q4-

2009
Q1-
2009
Q2-
2009
Q3-
2009
Q4-
2010
Q1-
2010
Q2-
2010
Q3-
2010
Q4-

Number of new vehicles sold in the
1st quarter of 2010 (Q1-2010)
Information
Data
Managing a vehicle recall in a way that minimizes
negative impacts on new vehicle sales and net income
Knowledge
Storage
Temporary memory (RAM), hard disks, flash memory, cloud
People
Users, clients, customers, operators, technicians, governments,
companies
Sending
results,
collecting
data,

feedback
Communication
Working with
information,
changing,
calculating,
manipulating
Processing
Data collected,
captured,
scanned,
snapped from
transactions
Input
Showing
results on
screen,
hardcopy, digital

copy, archive
Output
Data
Data Data
Data are extracted,
transformed, &
loaded (ETL)
Data from online
purchases
of transactional
data
Database
Reporting
MIS
Models applied to

data for analysis
DSS
Processes raw
data
TPS
Analytical processing
of data to discover
trends and learn
insights
Data Warehouse
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TRANSACTION
PROCESSING SYSTEMS
Transaction processing systems (TPSs) are designed to process
specific types of
data input from ongoing transactions. TPSs can be manual, as
when data are typed
into a form on a screen, or automated by using scanners or
sensors to capture bar-
codes or other data (Figure 2.10).
Organizational data are processed by a TPS—sales orders,
payroll, accounting,
financial, marketing, purchasing, inventory control, and so
forth. Transactions are
either:
• Internal transactions that originate within the organization or
that occur
within the organization. Examples are payroll, purchases,
budget trans-
fers, and payments (in accounting terms, they are referred to as
accounts
payable).

• External transactions that originate from outside the
organization, for
example, from customers, suppliers, regulators, distributors, and
financing
institutions.
TPSs are essential systems. Transactions that are not captured
can result in lost
sales, dissatisfied customers, and many other types of data
errors with finan-
cial impacts. For example, if the accounting department issued a
check to pay
an invoice (bill) and it was cashed by the recipient, but
information about that
transaction was not captured, then two things happen. First, the
amount of cash
listed on the company’s financial statements is wrong because
no deduction was
made for the amount of the check. Second, the accounts payable
(A/P) system
3. Data are output to a decision-support system (DSS) where
they are analyzed
using formulas, fi nancial ratios, or models.

Data collected by the TPS are converted into reports by the MIS
and analyzed by
the DSS to support decision making. Corporations, government
agencies, the mili-
tary, health care, medical research, major league sports, and
nonprofits depend on
their DSSs at all levels of the organization. Innovative DSSs
create and help sustain
competitive advantages. DSSs reduce waste in production
operations, improve
inventory management, support investment decisions, and
predict demand. The
model of a DSS consists of a set of formulas and functions, such
as statistical, finan-
cial, optimization, and/or simulation models.
Customer data, sales, and other critical data are selected for
additional analy-
sis, such as trend analysis or forecasting demand. These data are
extracted from
the database, transformed into a standard format, and then
loaded into a data
warehouse.
Figure 2.10 Scanners

automate the input of data
into a transaction processing
system (TPS). ©
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will continue to show the invoice as unpaid, so the accounting
department might
pay it a second time. Likewise, if services are provided, but the
transactions are
not recorded, the company will not bill for them and thus not
collect that service
revenue.
Batch vs. Online Real Time Processing
Data captured by a TPS are processed and stored in a database;
they then become
available for use by other systems. Processing of transactions is
done in one of two
modes:
1. Batch processing: A TPS in batch processing mode collects
all transaction for
a day, shift, or other time period, and then processes the data

and updates the
data stores. Payroll processing done weekly or bi-weekly is an
example of batch
mode.
2. Online transaction processing (OLTP) or real time
processing: The TPS pro-
cesses each transaction as it occurs, which is what is meant by
the term real time
processing. In order for OLTP to occur, the input device or
website must be
directly linked via a network to the TPS. Airlines need to
process fl ight reserva-
tions in real time to verify that seats are available.
Batch processing costs less than real time processing. A
disadvantage is that data
are inaccurate because they are not updated immediately, in real
time.
Processing Impacts Data Quality
As data are collected or captured, they are validated to detect
and correct obvi-
ous errors and omissions. For example, when a customer sets up

an account with a
financial services firm or retailer, the TPS validates that the
address, city, and postal
code provided are consistent with one another and also that they
match the credit
card holder’s address, city, and postal code. If the form is not
complete or errors
are detected, the customer is required to make the corrections
before the data are
processed any further.
Data errors detected later may be time-consuming to correct or
cause other
problems. You can better understand the difficulty of detecting
and correcting
errors by considering identity theft. Victims of identity theft
face enormous chal-
lenges and frustration trying to correct data about them.
MANAGEMENT
INFORMATION
SYSTEMS
Functional areas or departments—accounting, finance,
production/operations,

marketing and sales, human resources, and engineering and
design—are supported
by ISs designed for their particular reporting needs. General-
purpose reporting
systems are referred to as management information systems
(MISs). Their objective
is to provide reports to managers for tracking operations,
monitoring, and control.
Typically, a functional system provides reports about such
topics as operational
efficiency, effectiveness, and productivity by extracting
information from databases
and processing it according to the needs of the user. Types of
reports include the
following:
• Periodic: These reports are created or run according to a pre-
set schedule.
Examples are daily, weekly, and quarterly. Reports are easily
distributed via
e-mail, blogs, internal websites (called intranets), or other
electronic media.
Periodic reports are also easily ignored if workers do nott find
them worth

the time to review.
• Exception: Exception reports are generated only when
something is outside
the norm, either higher or lower than expected. Sales in
hardware stores
prior to a hurricane may be much higher than the norm. Or sales
of fresh
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produce may drop during a food contamination crisis. Exception
reports are
more likely to be read because workers know that some unusual
event or
deviation has occurred.
• Ad hoc, or on demand: Ad hoc reports are unplanned reports.
They are gen-

erated to a mobile device or computer on demand as needed.
They are gener-
ated on request to learn more about a situation, problem, or
opportunity.
Reports typically include interactive data visualizations, such as
column and pie
charts, as shown in Figure 2.11.
Functional information systems that support business analysts
and other
departmental employees can be fairly complex, depending on
the type of employ-
ees supported. The following examples show the support that IT
provides to major
functional areas.
1. Bolsa de Comercio de Santiago, a large stock exchange in
Chile, processes
high-volume trading in microseconds using IBM software. The
stock exchange
increased its transaction capacity by 900 percent by 2011. The
Chilean stock
exchange system can do the detective work of analyzing current
and past

transactions and market information, learning and adapting to
market trends
and connecting its traders to business information in real time.
Immediate
throughput in combination with analytics allows traders to make
more accu-
rate decisions.
2. According to the New England Journal of Medicine, 1 in 5
patients suffers from
preventable readmissions, which cost taxpayers over $17 billion
a year. Begin-
ning in 2012, hospitals have been penalized for high
readmission rates with cuts
to the payments they receive from the government (Miliard,
2011). Using a DSS
and predictive analytics, the health-care industry can leverage
unstructured in-
formation in ways not possible before, according to Charles J.
Barnett, president/
CEO of Seton Health Care. “With this solution, we can access
an integrated view
of relevant clinical and operational information to drive more
informed decision
making. For example, by predicting which patients might be

readmitted, we can
reduce costly and preventable readmissions, decrease mortality
rates, and ulti-
mately improve the quality of life for our patients” (Miliard,
2011).
DECISION SUPPORT
SYSTEMS
Decision support systems (DSSs) are interactive applications
that support decision
making. Configurations of a DSS range from relatively simple
applications that
support a single user to complex enterprisewide systems. A DSS
can support the
analysis and solution of a specific problem, evaluate a strategic
opportunity, or sup-
port ongoing operations. These systems support unstructured
and semistructured
decisions, such as make-or-buy-or-outsource decisions, or what
products to develop
and introduce into existing markets.
Figure 2.11 Sample report
produced by an MIS. ©

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Degree of Structure of Decisions
Decisions range from structured to unstructured. Structured
decisions are those
that have a well-defined method for solving and the data
necessary to reach a sound
decision. An example of a structured decision is determining
whether an applicant
qualifies for an auto loan, or whether to extend credit to a new
customer—and the
terms of those financing options. Structured decisions are
relatively straightforward
and made on a regular basis, and an IS can ensure that they are
done consistently.
At the other end of the continuum are unstructured decisions
that depend on
human intelligence, knowledge, and/or experience—as well as
data and models to
solve. Examples include deciding which new products to
develop or which new mar-
kets to enter. Semistructured decisions fall in the middle of the

continuum. DSSs
are best suited to support these types of decisions, but they are
also used to support
unstructured ones. To provide such support, DSSs have certain
characteristics to
support the decision maker and the overall decision-making
process.
Three Defining DSS Characteristics
These characteristics of DSSs include:
1. An easy-to-use interactive interface
2. Models or formulas that enable sensitivity analysis, what-if
analysis, goal seek-
ing, and risk analysis
3. Data from multiple sources—internal and external sources
plus data added by
the decision maker who may have insights relevant to the
decision situation
Having models is what distinguishes DSS from MIS. Some
models are devel-

oped by end users through an interactive and iterative process.
Decision makers can
manipulate models to conduct experiments and sensitivity
analyses, for example,
what-if and goal seeking. What-if analysis refers to changing
assumptions or data in
the model to observe the impacts of those changes on the
outcome. For example, if
sale forecasts are based on a 5 percent increase in customer
demand, a what-if anal-
ysis would replace the 5 percent with higher and/or lower
estimates to determine
what would happen to sales if demand changed. With goal
seeking, the decision
maker has a specific outcome in mind and needs to figure out
how that outcome
could be achieved and whether it is feasible to achieve that
desired outcome. A DSS
can also estimate the risk of alternative strategies or actions.
California Pizza Kitchen (CPK) uses a DSS to support inventory
decisions.
CPK has 77 restaurants located in various states in the United
States. Maintaining
optimal inventory levels at all restaurants was challenging and

time-consuming. A
DSS was built to make it easy for the chain’s managers to
maintain updated records
and make decisions. Many CPK restaurants increased sales by 5
percent after
implementing a DSS.
Building DSS Applications
Planners Lab is an example of software for building DSSs. The
software is free to
academic institutions and can be downloaded from
plannerslab.com. Planners Lab
includes:
• An easy-to-use model-building language
• An easy-to-use option for visualizing model output, such as
answers to what-if
and goal-seeking questions, to analyze the impacts of different
assumptions
These tools enable managers and analysts to build, review, and
challenge the
assumptions upon which their decision scenarios are based.

With Planners Lab,
decision makers can experiment and play with assumptions to
assess multiple views
of the future.
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DATABASE VOLATILITY
AND DATA
WAREHOUSING
Given the huge number of transactions, the data in databases are
constantly in use
or being updated. This characteristic of databases—referred to
as volatility—makes
it impossible to use them for complex decision-making and
problem-solving tasks.
For this reason, data are extracted from the database
transformed (processed to

standardize the data), and then loaded into a data warehouse. As
a result of the
extract, transformation, and load (ETL), operations data in the
data warehouse are
better formatted for analyses.
ISS EXIST WITHIN
A CULTURE
ISs do not exist in isolation. They have a purpose and a social
(organizational)
context. A common purpose is to provide a solution to a
business problem. The
social context of the system consists of the values and beliefs
that determine what
is admissible and possible within the culture of the organization
and among the
people involved. For example, a company may believe that
superb customer service
and on-time delivery are critical success factors. This belief
system influences IT
investments, among other factors.
The business value of IT is determined by the people who use
them, the busi-

ness processes they support, and the culture of the organization.
That is, IS value
is determined by the relationships among ISs, people, and
business processes—all
of which are influenced strongly by organizational culture, as
shown in Figure 2.12.
Figure 2.12 Organizational
culture plays a signifi cant
role in the use and benefi ts
of Information systems.
Questions
1. Contrast data, information, and knowledge.
2. Defi ne TPS and give an example.
3. When is batch processing used?
4. When are real time processing capabilities needed?
5. Explain why TPSs need to process incoming data before they
are
stored.
6. Defi ne MIS and DSS and give an example of each.
7. Why are databases inappropriate for doing data analysis?
On-premises data centers, virtualization, and cloud computing

are types of IT
infrastructures or computing systems. Long ago, there were few
IT infrastructure
options. Mostly, companies owned their servers, storage, and
network com-
ponents to support their business applications and these
computing resources
were on their premises. Now, there are several choices for an IT
infrastructure
2.4 Data Centers, Cloud Computing, and Virtualization
Organizational Culture
Information
Systems:
hardware, software,
networks, and data
Business
Processes
People

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strategy—including virtualization and cloud computing. As is
common to IT
investments, each infrastructure configuration has strengths,
weaknesses, and cost
considerations.
DATA CENTERS A data center consists of a large number of
network servers (Figure 2.13) used for the
storage, processing, management, distribution, and archiving of
data, systems, Web
traffic, services, and enterprise applications. Data center also
refers to the building or
facility that houses the servers and equipment. Here are some
examples of data centers:
• National Climatic Data Center. The National Climatic Data

Center is an
example of a public data center that stores and manages the
world’s largest
archive of weather data.
• U.S. National Security Agency. The National Security
Agency’s (NSA) data
center in Bluffdale, UT, shown in Figure 2.14, opened in the
fall of 2013. It
is the largest spy data center for the NSA. People who think
their corre-
spondence and postings through sites like Google, Facebook,
and Apple are
safe from prying eyes should rethink that belief. You will read
more about
reports exposing government data collection programs in
Chapter 5.
• Apple. Apple has a 500,000-square-foot data center in Maiden,
NC, that
houses servers for various iCloud and iTunes services. The
center plays
a vital role in the company’s back-end IT infrastructure. In 2014
Apple
expanded this center with a new, smaller 14,250 square-foot

tactical data
center that also includes office space, meeting areas, and
breakrooms.
Companies may own and manage their own on-premises data
centers or pay
for the use of their vendors’ data centers, such as in cloud
computing, virtualization,
and software, as service arrangements (Figure 2.15).
Figure 2.13 A row of
network servers in data
center.
Figure 2.14 The NSA
data center (shown under
construction) opened in the
fall of 2013 in Bluffdale, UT. It
is the largest spy data center
for the NSA. People who
believe their correspondence
and postings through sites
like Google, Facebook, and
Apple are safe from prying
eyes should think again.

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Since only the company owns the infrastructure, a data center is
more suitable
for organizations that run many different types of applications
and have complex
workloads. A data center, like a factory, has limited capacity.
Once it is built, the

amount of storage and the workload the center can handle does
not change without
purchasing and installing more equipment.
When a Data Center Goes Down, so Does Business
Data center failures disrupt all operations regardless of who
owns the data center.
Here are two examples.
• Uber. The startup company Uber experienced an hour-long
outage in
February 2014 that brought its car-hailing service to a halt
across the coun-
try. The problem was caused by an outage at its vendor’s West
Coast data
center. Uber users flooded social media sites with complaints
about prob-
lems kicking off Uber’s app to summon a driver-for-hire.
• WhatsApp. WhatsApp also experienced a server outage in
early 2014 that took
the service offline for 2.5 hours. WhatsApp is a smartphone
text-messaging
service that had been bought by Facebook for $19 billion.

“Sorry we currently
experiencing server issues. We hope to be back up and
recovered shortly,”
WhatsApp said in a message on Twitter that was retweeted more
than 25,000
times in just a few hours. The company has grown rapidly to
450 million active
users within five years, nearly twice as many as Twitter. More
than two-thirds of
these global users use the app daily. WhatsApp’s’ server failure
drove millions
of users to a competitor. Line, a messaging app developed in
Japan, added 2
million new registered users within 24 hours of WhatsApp’s
outage—the big-
gest increase in Line’s user base within a 24-hour period.
These outages point to the risks of maintaining the complex and
sophisticated
technology needed to power digital services used by millions or
hundreds of mil-
lions of people.
Figure 2.15 Data centers
are the infrastructure

underlying cloud computing,
virtualization, networking,
security, delivery systems,
and software as a service.
Many of these issues are
discussed in this chapter. ©
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INTEGRATING DATA TO
COMBAT DATA CHAOS
An enterprise’s data are stored in many different or remote
locations—creating
data chaos at times. And some data may be duplicated so that
they are available
in multiple locations that need a quick response. Therefore, the
data needed for
planning, decision making, operations, queries, and reporting
are scattered or dupli-
cated across numerous servers, data centers, devices, and cloud
services. Disparate
data must be unified or integrated in order for the organization
to function.
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Unified Data Center
One solution is Cisco’s Unified Data Center (UDC). UDC can
significantly speed
up the integration and consolidation of data and cut data center
costs. UDC inte-
grates compute, storage, networking, virtualization, and
management into a single
or unified platform. That platform provides an infrastructure
that simplifies data
management and improves business agility or responsiveness.
UDC can run appli-
cations more quickly in virtual and cloud computing
environments.
Data Virtualization
Cisco provides data virtualization, which gives greater IT
flexibility. Using virtual-
ization methods, enterprises can respond to change more

quickly and make better
decisions in real time without physically moving their data,
which significantly cuts
costs. Cisco Data Virtualization makes it possible to:
• Have instant access to data at any time and in any format.
• Respond faster to changing data analytics needs.
• Cut complexity and costs.
Compared to traditional (nonvirtual) data integration and
replication methods,
Cisco Data Virtualization accelerates time to value with:
• Greater agility: speeds 5 to 10 times faster than traditional
data integration
methods
• Streamlined approach: 50 to 75 percent time savings over data
replication
and consolidation methods
• Better insight: instant access to data

Cisco offers videos on cloud computing, virtualization, and
other IT infrastruc-
tures at its video portal at video.cisco.com.
CLOUD COMPUTING
INCREASES AGILITY
In a business world where first movers gain the advantage, IT
responsiveness and
agility provide a competitive edge. Yet, many IT infrastructures
are extremely
expensive to manage and too complex to easily adapt. A
common solution is cloud
computing. Cloud computing is the general term for
infrastructures that use the
Internet and private networks to access, share, and deliver
computing resources.
The National Institute of Standards and Technology (NIST)
more precisely defines
cloud computing as “a model for enabling convenient, on-
demand network access to
a shared pool of configuration computing resources that can be
rapidly provisioned
and released with minimal management effort or service
provider interaction”

(NIST, 2012).
SELECTING A CLOUD
VENDOR
Because cloud is still a relatively new and evolving business
model, the decision to
select a cloud service provider should be approached with even
greater diligence
than other IT decisions. As cloud computing becomes an
increasingly important
part of the IT delivery model, assessing and selecting the right
cloud provider also
become the most strategic decisions that business leaders
undertake. Providers are
not created equally, so it is important to investigate each
provider’s offerings prior to
subscribing. When selecting and investing in cloud services,
there are several service
factors a vendor needs to address. These evaluation factors are
listed in Table 2.5.
Vendor Management and Service-Level Agreements
The move to the cloud is also a move to vendor-managed

services and cloud service-
level agreements (SLAs). An SLA is a negotiated agreement
between a company
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and service provider that can be a legally binding contract or an
informal contract.
You can review an example of the Google Apps SLA by visiting
its website at
Google.com and searching for “SLA.” Staff experienced in
managing outsourcing
projects may have the necessary expertise for managing work in
the cloud and polic-
ing SLAs with vendors. The goal is not building the best SLA
terms, but getting the
terms that are most meaningful to the business.
The Cloud Standards Customer Council published the Practical

Guide to
Cloud Service Level Agreements (2012), which brings together
numerous customer
experiences into a single guide for IT and business leaders who
are considering
cloud adoption. According to this guide, an SLA serves:
as a means of formally documenting the service(s), performance
expectations,
responsibilities and limits between cloud service providers and
their users. A
typical SLA describes levels of service using various attributes
such as: availability,
TABLE 2.5 Service Factors to Consider when Evaluating Cloud
Vendors
or Service Providers
Factors Examples of Questions to Be Addressed
Delays What are the estimated server delays and network
delays?
Workloads What is the volume of data and processing that can
be

handled during a specifi c amount of time?
Costs What are the costs associated with workloads across
multiple cloud computing platforms?
Security How are data and networks secured against attacks?
Are data encrypted and how strong is the encryption?
What are network security practices?
Disaster recovery How is service outage defi ned? What level
of
and business redundancy is in place to minimize outages,
including
continuity backup services in different geographical regions? If
a
natural disaster or outage occurs, how will cloud
services be continued?
Technical expertise Does the vendor have expertise in your
industry or
and understanding business processes? Does the vendor
understand what
you need to do and have the technical expertise to
fulfi ll those obligations?

Insurance in case Does the vendor provide cloud insurance to
mitigate
of failure user losses in case of service failure or damage? This
is
a new and important concept.
Third-party audit, or Can the vendor show objective proof with
an audit
an unbiased assessment that it can live up to the promises it is
making?
of the ability to rely on
the service provided by
the vendor
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serviceability, performance, operations, billing, and penalties
associated with
violations of such attributes. (Cloud Standards Customer
Council, 2012, pp. 5–6.)
Implementing an effective management process is an important
step in ensur-
ing internal and external user satisfaction with cloud services.
CLOUD VS. DATA
CENTER: WHAT IS THE
DIFFERENCE?
A main difference between a cloud and data center is that a
cloud is an off-premise
form of computing that stores data on the Internet. In contrast, a
data center refers
to on-premises hardware and equipment that store data within
an organization’s
local network. Cloud services are outsourced to a third-party
cloud provider who
manages the updates, security, and ongoing maintenance. Data
centers are typically
run by an in-house IT department.

Cloud computing is the delivery of computing and storage
resources as a ser-
vice to end-users over a network. Cloud systems are scalable.
That is, they can be
adjusted to meet changes in business needs. At the extreme, the
cloud’s capacity is
unlimited depending on the vendor’s offerings and service
plans. A drawback of the
cloud is control because a third party manages it. Companies do
not have as much
control as they do with a data center. And unless the company
uses a private cloud
within its network, it shares computing and storage resources
with other cloud users
in the vendor’s public cloud. Public clouds allow multiple
clients to access the same
virtualized services and utilize the same pool of servers across a
public network. In
contrast, private clouds are single-tenant environments with
stronger security and
control for regulated industries and critical data. In effect,
private clouds retain all
the IT security and control provided by traditional data center
infrastructures with
the advantage of cloud computing.

Companies often use an arrangement of both on-premises data
centers and
cloud computing (Figure 2.16).
A data center is physically connected to a local network, which
makes it easier
to restrict access to apps and information to only authorized,
company-approved
people and equipment. However, the cloud is accessible by
anyone with the proper
credentials and Internet connection. This accessibility
arrangement increases expo-
sure to company data at many more entry and exit points.
CLOUD
INFRASTRUCTURE
The cloud has greatly expanded the options for enterprise IT
infrastructures
because any device that accesses the Internet can access, share,
and deliver data.
Cloud computing is a valuable infrastructure because it:
1. Provides a dynamic infrastructure that makes apps and

computing power avail-
able on demand. Apps and power are available on demand
because they are
provided as a service. For example, any software that is
provided on demand is
referred to as software as a service, or SaaS. Typical SaaS
products are Google
Apps and Salesforce.com. Section 2.5 discussed SaaS and other
cloud services.
2. Helps companies become more agile and responsive while
signifi cantly reducing
IT costs and complexity through improved workload
optimization and service
delivery.
Move to Enterprise Clouds
A majority of large organizations have hundreds or thousands of
software licenses
that support business processes, such as licenses for Microsoft
Office, Oracle database
management, IBM CRM (customer relationship management),
and various network
security software. Managing software and their licenses

involves deploying, provi-
sioning, and updating them—all of which are time-consuming
and expensive. Cloud
computing overcomes these problems.
/208/WB01490/9781118897782/ch02/text_s
Figure 2.16 Corporate IT
infrastructures can consist of
an on-premises data center
and off-premises cloud
computing.
ISSUES IN MOVING
WORKLOADS FROM
THE ENTERPRISE TO
THE CLOUD
Building a cloud strategy is a challenge, and moving existing

apps to the cloud is
stressful. Despite the business and technical benefits, the risk
exists of disrupting
operations or customers in the process. With the cloud, the
network and WAN
(wide area network) become an even more critical part of the IT
infrastructure.
Greater network bandwidth is needed to support the increase in
network traffic.
And, putting part of the IT architecture or workload into the
cloud requires dif-
ferent management approaches, different IT skills, and knowing
how to manage
vendor relationships and contracts.
Infrastructure Issues
There is a big difference because cloud computing runs on a
shared infrastructure,
so the arrangement is less customized to a specific company’s
requirements. A
comparison to help understand the challenges is that
outsourcing is like renting an
apartment, while the cloud is like getting a room at a hotel.

With cloud computing, it may be more difficult to get to the
root of perfor-
mance problems, like the unplanned outages that occurred with
Google’s Gmail
and Workday’s human resources apps. The trade-off is cost vs.
control.
Increasing demand for faster and more powerful computers, and
increases in
the number and variety of applications are driving the need for
more capable IT
architectures.
VIRTUALIZATION AND
VIRTUAL MACHINES
Computer hardware had been designed to run a single operating
system (OS) and
a single app, which leaves most computers vastly underutilized.
Virtualization is a
technique that creates a virtual (i.e., nonphysical) layer and
multiple virtual machines
(VMs) to run on a single physical machine. The virtual (or
virtualization) layer makes
it possible for each VM to share the resources of the hardware.

Figure 2.17 shows the
relationship among the VMs and physical hardware.
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What Is a Virtual Machine?
Just as virtual reality is not real, but a software-created world, a
virtual machine is
a software-created computer. Technically, a virtual machine
(VM) is created by a
software layer, called the virtualization layer, as shown in
Figure 2.17. That layer
has its own Windows or other OS and apps, such as Microsoft
Office, as if it were
an actual physical computer. A VM behaves exactly like a
physical computer and
contains its own virtual—that is, software-based—CPU, RAM
(random access
memory), hard drive, and network interface card (NIC). An OS
cannot tell the dif-
ference between a VM and a physical machine, nor can apps or
other computers
on a network tell the difference. Even the VM thinks it is a

“real” computer. Users
can set up multiple real computers to function as a single PC
through virtualization
to pool resources to create a more powerful VM.
Virtualization is a concept that has several meanings in IT and
therefore sev-
eral definitions. The major type of virtualization is hardware
virtualization, which
remains popular and widely used. Virtualization is often a key
part of an enter-
prise’s disaster recovery plan. In general, virtualization
separates business applica-
tions and data from hardware resources. This separation allows
companies to pool
hardware resources—rather than dedicate servers to
applications—and assign those
resources to applications as needed.
The major types of virtualization are the following:
• Storage virtualization is the pooling of physical storage from
multiple net-
work storage devices into what appears to be a single storage
device man-

aged from a central console.
• Network virtualization combines the available resources in a
network by
splitting the network load into manageable parts, each of which
can be
assigned (or reassigned) to a particular server on the network.
• Hardware virtualization is the use of software to emulate
hardware or a total
computer environment other than the one the software is
actually running
in. It allows a piece of hardware to run multiple operating
system images at
once. This kind of software is sometimes known as a virtual
machine.
Virtualization Characteristics and Benefits
Virtualization increases the flexibility of IT assets, allowing
companies to consoli-
date IT infrastructure, reduce maintenance and administration
costs, and prepare
for strategic IT initiatives. Virtualization is not primarily about
cost-cutting, which

Figure 2.17 Virtual machines
running on a simple
computer hardware layer.
Application
Virtualization Layer
Hardware Layer
Operating
System
Application
Operating
System
Application
Operating
System
Virtual Machines

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is a tactical reason. More importantly, for strategic reasons,
virtualization is used
because it enables flexible sourcing and cloud computing.
The characteristics and benefits of virtualization are as follows:
1. Memory-intensive. VMs need a huge amount of RAM
(random access memory,
or primary memory) because of their massive processing
requirements.
2. Energy-effi cient. Minimizes energy consumed running and
cooling servers in
the data center—representing up to a 95 percent reduction in
energy use per
server.

3. Scalability and load balancing. When a big event happens,
such as the Super
Bowl, millions of people go to a website at the same time.
Virtualization pro-
vides load balancing to handle the demand for requests to the
site. The VMware
infrastructure automatically distributes the load across a cluster
of physical serv-
ers to ensure the maximum performance of all running VMs.
Load balancing is
key to solving many of today’s IT challenges.
Virtualization consolidates servers, which reduces the cost of
servers, makes
more efficient use of data center space, and reduces energy
consumption. All of
these factors reduce the total cost of ownership (TCO). Over a
three-year life cycle,
a VM costs approximately 75 percent less to operate than a
physical server.
Liberty Wines supplies to restaurants, supermarkets, and
independent retailers from its headquarters in central
London. Recipient of multiple international wine awards—

including the International Wine Challenge on Trade Supplier
of the Year for two years running—Liberty Wines is one of the
United Kingdom’s foremost wine importers and distributors.
IT Problems and Business Needs
As the business expanded, the existing servers did not have
the capacity to handle increased data volumes, and main-
tenance of the system put a strain on the IT team of two
employees. Existing systems were slow and could not pro-
vide the responsiveness that employees expected.
Liberty Wines had to speed up business processes to
meet the needs of customers in the fast-paced world of
fine dining. To provide the service their customers expect,
employees at Liberty Wines needed quick and easy access
to customer, order, and stock information. In the past, the
company relied on 10 physical servers for apps and services,
such as order processing, reporting, and e-mail.
Virtualized

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