Business Intelligence Strategy and Big Data Analytics: A General Management Perspective

Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability.  It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion.  Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others.  It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges.

In recent years, terms like “big data” and “big data analytics” have been introduced into the business and technical lexicon.  Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness.  Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate.  More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both.

• Provides ideas for improving the business performance of one’s company or business functions
• Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies
• Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans

As a BI strategy consultant, Steve has had the privilege of working with successful companies in retail, distribution, manufacturing, consumer packaged goods, government, and electric power. His clients have included:

• ArcBest

• Heinens Fine Foods

• Louisville Gas and Electric

• Navy Federal Credit Union

• Northwestern Mutual Life

• Partners Federal Credit Union

• Pinnacle Foods Group

• Principal Financial Group

• Toronto Hydro Electric System

• United Natural Foods

• U.S. Social Security Administration

• Watsco

While the industries and companies are different, there are many common challenges when it comes to leveraging BI, analytics, and big data to enhance profitability. Steve understands these challenges, and he provides proven methods for meeting them.

In addition to his consulting work, Steve is also an active contributor to the field of business intelligence, analytics, and big data. He and Nancy Williams wrote The Profit Impact of Business Intelligence in 2006, and Steve has continued to write for magazines such as Strategic Finance, Business Intelligence Journal, and MWorld (The Journal of the American Management Association). In addition to widely-sharing his thinking about BI, analytics, and big data, Steve has also served as a judge since 2001 for the annual TDWI Best Practices in Business Intelligence and Data Warehousing Competition.

Prior to founding DecisionPath, Steve worked for twenty years in several specialized consulting companies where he developed expertise in program management, systems integration, software engineering, and management accounting. He holds an MBA in General Management from the Darden School at the University of Virginia and a B.S. in Business Management from the University of Maryland.