Cover Page

Wiley & SAS Business Series

The Wiley & SAS Business Series presents books that help senior-level managers with their critical management decisions.

Titles in the Wiley & SAS Business Series include:

  1. Activity-Based Management for Financial Institutions: Driving Bottom-Line Results by Brent Bahnub
  2. Bank Fraud: Using Technology to Combat Losses by Revathi Subramanian
  3. Big Data Analytics: Turning Big Data into Big Money by Frank Ohlhorst
  4. Branded! How Retailers Engage Consumers with Social Media and Mobility by Bernie Brennan and Lori Schafer
  5. Business Analytics for Customer Intelligence by Gert Laursen
  6. Business Analytics for Managers: Taking Business Intelligence beyond Reporting by Gert Laursen and Jesper Thorlund
  7. The Business Forecasting Deal: Exposing Bad Practices and Providing Practical Solutions by Michael Gilliland
  8. Business Intelligence Applied: Implementing an Effective Information and Communications Technology Infrastructure by Michael Gendron
  9. Business Intelligence in the Cloud: Strategic Implementation Guide by Michael S. Gendron
  10. Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy by Olivia Parr Rud
  11. CIO Best Practices: Enabling Strategic Value with Information Technology, Second Edition by Joe Stenzel
  12. Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media by Frank Leistner
  13. Credit Risk Assessment: The New Lending System for Borrowers, Lenders, and Investors by Clark Abrahams and Mingyuan Zhang
  14. Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring by Naeem Siddiqi
  15. The Data Asset: How Smart Companies Govern Their Data for Business Success by Tony Fisher
  16. Delivering Business Analytics: Practical Guidelines for Best Practice by Evan Stubbs
  17. Demand-Driven Forecasting: A Structured Approach to Forecasting, Second Edition by Charles Chase
  18. Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain by Robert A. Davis
  19. The Executive’s Guide to Enterprise Social Media Strategy: How Social Networks Are Radically Transforming Your Business by David Thomas and Mike Barlow
  20. Economic and Business Forecasting: Analyzing and Interpreting Econometric Results by John Silvia, Azhar Iqbal, Kaylyn Swankoski, Sarah Watt, and Sam Bullard
  21. Executive’s Guide to Solvency II by David Buckham, Jason Wahl, and Stuart Rose
  22. Fair Lending Compliance: Intelligence and Implications for Credit Risk Management by Clark R. Abrahams and Mingyuan Zhang
  23. Foreign Currency Financial Reporting from Euros to Yen to Yuan: A Guide to Fundamental Concepts and Practical Applications by Robert Rowan
  24. Health Analytics: Gaining the Insights to Transform Health Care by Jason Burke
  25. Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World by Carlos Andre Reis Pinheiro and Fiona McNeill
  26. Human Capital Analytics: How to Harness the Potential of Your Organization’s Greatest Asset by Gene Pease, Boyce Byerly, and Jac Fitz-enz
  27. Implement, Improve and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education by Jamie McQuiggan and Armistead Sapp
  28. Information Revolution: Using the Information Evolution Model to Grow Your Business by Jim Davis, Gloria J. Miller, and Allan Russell
  29. Killer Analytics: Top 20 Metrics Missing from Your Balance Sheet by Mark Brown
  30. Manufacturing Best Practices: Optimizing Productivity and Product Quality by Bobby Hull
  31. Marketing Automation: Practical Steps to More Effective Direct Marketing by Jeff LeSueur
  32. Mastering Organizational Knowledge Flow: How to Make Knowledge Sharing Work by Frank Leistner
  33. The New Know: Innovation Powered by Analytics by Thornton May
  34. Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics by Gary Cokins
  35. Predictive Business Analytics: Forward-Looking Capabilities to Improve Business Performance by Lawrence Maisel and Gary Cokins
  36. Retail Analytics: The Secret Weapon by Emmett Cox
  37. Social Network Analysis in Telecommunications by Carlos Andre Reis Pinheiro
  38. Statistical Thinking: Improving Business Performance, Second Edition by Roger W. Hoerl and Ronald D. Snee
  39. Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics by Bill Franks
  40. Too Big to Ignore: The Business Case for Big Data by Phil Simon
  41. The Value of Business Analytics: Identifying the Path to Profitability by Evan Stubbs
  42. Visual Six Sigma: Making Data Analysis Lean by Ian Cox, Marie A. Gaudard, Philip J. Ramsey, Mia L. Stephens, and Leo Wright
  43. Win with Advanced Business Analytics: Creating Business Value from Your Data by Jean Paul Isson and Jesse Harriott

For more information on any of the above titles, please visit

Business Transformation

A Roadmap for Maximizing Organizational Insights


Aiman Zeid




Wiley Logo


When Information Revolution1 was published in 2006, no Chinese-based companies were among the top 10 largest companies by market capitalization. Apple didn’t sell phones. Facebook was something college kids used to connect with their friends. Back then, we talked a lot about the amount of data coming in and faster processing speed.

What we believed then remains true today: Data, and the decision-making process, can be moved throughout the organization to equip every decision maker (automated, line worker, analyst, executive) to make the best choices. By operationalizing analytics, organizations can identify and quantify both opportunity and risk. Information Revolution highlighted SAS’ Information Evolution Model, which helps organizations understand how they interact with their information and how to extract more value from it through analytics.


Business intelligence still matters. But today’s global economy requires predictive analytics and forecasting to play a more active role. Insights from unstructured data now hold great promise. New ways to store, move, and process data have made big data more accessible and affordable than ever before. Delivery has moved to mobile. Many leaders run their businesses from tablets and smartphones.

A persistent myth is that technology alone enables all this. Sure, you need technology, but it’s just one component: People, information processes, and culture are equally critical. That’s really what this book is about—transforming your organization to harness all four components.


After Information Revolution was published, accelerated processing speeds gave rise to near-real-time results. More granular exploration of data became possible in ways that weren’t quick or easy before. Organizations that treat their data as an asset continue to:

  1. Invest in people with the skills to extract the insights that were hidden in the data and surface them to decision makers throughout the organizations.
  2. Foster a culture that encourages using data to uncover new business opportunities and gain a better understanding of their customers.
  3. Have an executive sponsor who leads the effort to find, hire, cultivate, and support individuals who embrace fact-based decision making. This executive sponsor pays particular attention to the communication challenge that data-driven decision making presents. It’s important to have an executive who can articulate what the analytical insight returns can mean to the business units—and win over skeptics.

If top executives still make decisions based on gut feeling and data-driven individuals are still a separate part of the business, no amount of technology and data governance processes will make a difference. But if an organization is committed to using data successfully, one strategic hire can have a huge impact. A new type of professional, the data scientist, can bridge the communication gap that prevents an analytical culture from taking hold. Tom Davenport, in his Harvard Business Review article “Data Scientist: The Sexiest Job of the 21st Century,”2 describes a data scientist this way: “It’s a high-ranking professional with the training and curiosity to make discoveries in the world of big data. . . . Their sudden appearance on the business scene reflects the fact that organizations are now wrestling with information that comes in varieties and volumes never encountered before.” Data scientists help organizations get the most out of their data, in part, by using business requirements to drive the information exploration and the application of analytics. Data scientists often have a background in math, statistics, and computer science, but aren’t necessarily experts in any one of those fields. They have to be very good at translating the value of data to the business and helping analysts understand what they need to do.

Internal communication and business and IT alignment continue to present challenges for organizations. Many rely on enterprise Centers of Excellence to boost business-transformation efforts.

My point is: You can’t just bring in technology tools to solve your business problems and expect them to do all the work. You must have the infrastructure capabilities, the skilled people, the information processes, and the cultural commitment to derive the most value from your data.


Some things haven’t changed, and one of them is taking a structured approach to building toward the enterprise level of information maturity—and beyond. The five levels outlined in 2006 remain relevant today (though we’ve grouped the levels into three key categories). Unfortunately, many organizations are in a quandary about how to reach information maturity. Now here’s the clincher: “By 2015, 15 percent of organizations will modernize their strategy for information management capability and exhibit a 20 percent higher financial performance than their peers,” according to Gartner.3 These are clear signs of strategic initiatives by many organizations to reach higher maturity level.

To get started, you need to understand where your organization is today before you can build toward the future. This is particularly important as it relates to purchasing technology. Organizations that say they have not received a strong return on their investment in analytic technology frequently suffer from information maturity issues and may benefit from a business-transformation effort. Assessing maturity is a process, but well worth the effort in the knowledge you will gain. It can be painful to find out your organization is not at the maturity level you assumed. But, you will have a clear picture of how to begin developing your road map to get to the next level.

A fact-based decision-making culture is no longer an option; it’s a requirement spreading across industries. To stay competitive, be proactive. Use the Information Evolution Model. Let your data give you a fresh perspective on your business—see what’s working, fix what isn’t, and set your sights on new opportunities.

—Jim Davis

Senior Vice President and Chief Marketing Officer SAS



Over the past 28 years of my professional career, I had the opportunity and privilege to work with many clients in almost all industries and sectors in the United States, Europe, the Middle East, Asia, and Latin America. I have helped these clients improve their efficiency, change their operating models, and transform their organizations. Although each region has business and cultural differences, all organizations face the same types of core challenges when they look closely at their operating models and evaluate their efficiency and alignment. When organizations realize they have a weakness in their decision-making process, strategy, or business functions, the first impulse is go with the easy answer first. Often in my travels I’ve seen a new technology being touted as a cure-all. And while new technology might be needed, the business results could vary considerably. Visionary leaders and executives realize that the key to unlocking their organization’s full potential requires honest and objective observation and evaluation of how the organization conducts its daily routine tasks.

Two key obvious ingredients are required to develop strategy and make sound decisions—information and skills. Accurate and consistent information provides a detailed understanding of business performance. People with the right skills can explore this information and analyze it to help their organization make sound decisions. This may be all organizations need if they limit their view to specific tasks or functions. But the focus should always be on enterprise performance. The formula for an efficient operating model will now need two more ingredients. Decision makers from various business units need to interact and collaborate to make the right decisions for the enterprise. Then the human nature characteristics and challenges quickly bring our attention to the internal organization culture that we all recognize in our individual environments. Each environment has its own unique formal and informal business practices, norms, and expectations that influence how decisions are made.

Aligning all business units around enterprise performance can be difficult. Effective organizational transformations can achieve alignment when organizations focus on their four key pillars—people, processes, technical infrastructure, and culture. The winning organizational transformation formula is now complete. When I visit clients I emphasize that it doesn’t matter that you’ve mastered one, or even two, of these factors—you need to work on all of them to bring your organization into alignment and truly transform it. Think of it like a recipe. Cut out a key ingredient, or substitute a poor alternative, and the recipe won’t taste the same—it might not even work. It’s the same with organizational transformation. If you ignore the culture part, the best technical infrastructure in the world won’t help you improve the organization’s business performance.

Many visionary leaders and executives realize the need to take a comprehensive look at their organizations. Addressing weaknesses and leveraging strengths in the current capabilities in each environment requires business transformation efforts in many cases. Leaders who realize that and, more important, act quickly can produce significant results for their organizations. I wrote this book because many executives still struggle with how and where to start. Approaching these complex organizational challenges needs a structured approach and a sound strategy that is tailored for each environment. This has been a significant focus of my professional career, and I wanted to share my experience and provide a roadmap for organizations to follow.


Writing this book would not have been possible without the encouragement and support I received from my family and colleagues. Their support gave me the energy and inspiration I needed to make the time to write this book after long days in the office and many business trips. I dedicate this book to my wife Marianne for her patience, support, and tolerance of my work and travel schedule, and to my children Suzanne and Adam, of whom I am very proud. The support I received from my colleagues at SAS has been invaluable. I would like to especially thank Michi Johnson, Christina Harvey, Cathy Traugot, and Stacey Hamilton for the contributions and support they provided.