Business Intelligence Strategy and Big Data Analytics (eBook)

Business Intelligence Strategy in the Big Data Analytics: A General Management Perspective explains how to deliver competitive advantages and substantial economic benefits by overcoming commonly-encountered barriers to success. It includes lessons learned from leading companies that provide practical ideas for how to use the many different forms of BI to meet key business objectives. Further, it clarifies how BI initiatives are really business initiatives that require business units to change how they use information and analysis to drive and improve business results, particularly profits.

Business intelligence (BI) and business analytics are like a Swiss army knife-they can be used in many different ways to achieve many different business purposes. In working with leading companies in a wide range of industries to help them formulate and execute BI strategies and program plans, the author has seen firsthand that these successful companies struggle in two key areas: BI Strategy, which is understanding how they can leverage BI in core business functions such as marketing, sales, customer service, operations, distribution, supplier management, cost improvement, and financial management; and BI Program Execution, which is effectively aligning and executing the diverse workstreams that are critical for achieving a return on investment (ROI), including change management, business process and BI integration, and BI and data warehousing development.

• 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

Steve Williams is the founder and CEO of DecisionPath Consulting. He specializes in helping clients formulate business-driven, technically-savvy strategies for leveraging business intelligence, analytics, and big data to improve profits. Steve blends general management experience and a general management MBA with nearly 30 years' experience in the information systems field - the last fifteen of which have been spent in the business intelligence (BI) and analytics specialty.
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.

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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 "e;big data? and "e;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