10 Principles of the New Business Intelligence by Tom Davenport

James Taylor brought an interesting article to my attention this month, called 10 Principles of the New Business Intelligence, written by Tom Davenport, and published in the Harvard Business Publishing. Davenport commented about a study entitled Linking Decisions and Information for Organizational Performance, with the sponsorship of IBM's Information Management business unit. In the study, he looked at 26 efforts to improve decision-making in organizations, and concluded that ten things about how business intelligence (BI) needs to evolve:

1. Decisions are the unit of work to which BI initiatives should be applied.

2. Providing access to data and tools isn't enough if you want to ensure that decisions are actually improved.

3. If you're going to supply data to a decision-maker, it should be only what is needed to make the decision.

4. The relationship between information and decisions is a choice organizations can make--from "loosely coupled," which is what happens in traditional BI, to "automated," in which the decision is made through automation.

5. "Loosely coupled" decision and information relationships are efficient to provision with information (hence many decisions can be supported), but don't often lead to better decisions.

6. The most interesting relationship involves "structured human" decisions, in which human beings still make the final decision, but the specific information used to make the decision is made available to the decision-maker in some enhanced fashion.

7. You can't really determine the value of BI or data warehousing unless they're linked to a particular initiative to improve decision-making. Otherwise, you'll have no idea how the information and tools are being used.

8. The more closely you want to link information and decisions, the more specific you have to get in focusing on a particular decision.

9. Efforts to create "one version of the truth" are useful in creating better decisions, but you can spend a lot of time and money on that goal for uncertain return unless you are very focused on the decisions to be made as a result.

10. Business intelligence results will increasingly be achieved by IT solutions that are specific to particular industries and decisions within them.

He mentioned a good article entitled Performance Management Links Strategy And Operations, written by Doug Henschen in Information Week, where he quoted:

BI historically has been about dashboards and scorecards developed for specific uses, says AMR Research analyst John Hagerty. But that's changing. "All of a sudden it's about integrated analytics within applications," he says. "The conversation is starting to shift to looking at information in the context of specific decisions and roles."

Tom Davenport also wrote an excellent book, with Jeanne Harris: Competing on Analytics: The New Science of Winning (I commented about this book in a post).

Competing on Analytics: The New Science of Winning

Competing on Analytics: The New Science of Winning - Thomas Davenport and Jeanne Harris

This book originated from an excellent article that the authors wrote to the Harvard Business Review. In this book, the authors define the analytical competition, and why and how the companies are using sophisticated quantitative and statistical analysis and predictive modeling to competing in a world where the companies are offering similar products. The globalization finished with several previous bases for competition and the companies need increasingly build their competitive strategies using the concepts of analytics.

They divide the book in two parts. In the part one, called The Nature of Analytical Competition, they wrote about the fundamentals that define the analytical competition.

In the first chapter, they define analytics as: "By Analytics we mean the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions. The analytics may be input for human decisions or may drive fully automated decisions. Analytics are a subset of what has come to be called Business Intelligence: a set of technologies and processes that use data to understand and analyze business performance."

They explain the use of analytics to improve the business performance and the business process to gain competitive advantage, divided into two categories: internal and external. In the internal process, they explain the use in financial analytics, cost management, mergers and acquisition, manufacturing, operations, research and development, and human resources. In competing on analytics with external processes, they define how the analytical competitors are using the data from customer-based process and supplier-facing processes to improve their external processes (sales, marketing, procurement, logistics).

In the part two, called Building an analytical capability, they define a road map, through five stages to the companies develop the analytical capability, and also how the companies should managing efficiently the analytical professionals.

It is an excellent book that to point the direction that the companies need to drive to become an analytical competitor.