Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics: The New Science of Winning. Harvard Business School Press, 2007.
Edward Demmings is reputed to have said “in God we trust, all others bring data.”
Yet, many businesses continue to be run on gut instinct. As Harrah’s Entertainment CEO Gary Loveman notes in the preface to the book, visionary leadership and intuition are still often prized over evidence-based decision-making.
OBJ360 (Sponsored)
The Ottawa Hospital’s Campaign to Create Tomorrow enters important next phase
For Ginger Bertrand, some of her earliest childhood memories in Ottawa are centred around healthcare. “I grew up across the street from what was originally the General Hospital,” she explains,
The Ottawa Hospital’s Campaign to Create Tomorrow enters important next phase
For Ginger Bertrand, some of her earliest childhood memories in Ottawa are centred around healthcare. “I grew up across the street from what was originally the General Hospital,” she explains,
Building on their 2006 article in the Harvard Business Review, Thomas H. Davenport, the president’s distinguished professor of information technology and management at Babson College, and Jeanne G. Harris, director of research at the Accenture Institute for High Performance Business, make a case for the use of analytics as a competitive differentiator.
This book is a useful primer for CEOs, managers and students who may not be conversant with the uses of business intelligence and analytics. However, it will probably disappoint those looking for a more in-depth and technical treatment of the subject.
Competing on Analytics is divided into two parts. The first provides an overview of nature of analytical competition and examples of how companies in different industries have used analytics to support their strategic positioning. The second part provides a high-level roadmap for becoming an analytical competitor, including an interesting discussion of the human and organizational dimensions and a slightly dated overview of business intelligence architecture and tools.
The authors use a five-stage model to outline the path that organizations follow to becoming an analytical computer. At the top, “stage-five” competitors are those organizations that manage analytics enterprise-wide, have an executive team committed to them and have made significant strategic bets on their use.
Most important, these organizations use analytics to support a distinctive competency such as optimizing their supply chains or accelerating product innovation. Based on their research, only about five per cent of large firms would today fit into this category.
The book offers a number of interesting examples of organizations that have differentiated themselves through the use of analytics. Examples include professional sports franchises such as the New England Patriots, Oakland Athletics and Boston Red Sox – all of whom use data and analytic models extensively for both player selection and on-field decisions.
Other examples range from financial institutions such as Capital One and RBC – who use analytics to improve their ability to target customers and to test products before engaging in full-scale marketing – to airline companies and hotel chains who use them for revenue management by optimizing room or seat pricing.
Government organizations are also increasingly using sophisticated analytics in decision-making. Case examples and anecdotes, however, are not a substitute for data and rigorous analysis.
One of the weaknesses in the book and this area in general is the lack of a body of research demonstrating the link between the comprehensive use of analytics and business performance. The authors acknowledge this, suggesting this should be an important topic of business school research. For those companies interested in becoming an analytical competitor, the journey described is neither quick nor easy.
The authors make it very clear that it involves far more than simply buying the right tools or software. Rather, it entails bringing together a lot of different pieces, including software applications, technology, data, processes, metrics, incentives, skills, culture and sponsorship. Above all, it requires building a strong analytical culture across the organization, starting with an executive team that is committed to evidence-based decision-making. While the authors do provide some useful checklists and lists of questions to ask in implementing a more analytic approach, the advice offered in this area does tend to be pretty high-level.
Overall, however, this volume should give executives new to this area a lot to think about. Many organizations today are sitting on considerable amounts of data generated by enterprise systems, point-of-sale systems and web transactions, as well as from customers and suppliers. The tools for analyzing this data are also becoming increasingly available.
C.K. Prahalad and M.S. Krishnan in their book The New Age of Innovation, reviewed earlier in this column, also made a strong case for using analytics to identify future consumer trends, opportunities for innovation and for product co-creation with customers.
More companies will likely be looking at how they can use the data they have for competitive advantage. This book is a good place to start.
Micheal Kelly is dean of the Telfer School of Management at the University of Ottawa.
