An organization experiences data-driven performance when it converts its data into knowledge which drives measurable achievements supporting organizational objectives.

The concept of data-driven performance has evolved for quite some time. During the 1990s, when Dr. N. Duru Ahanotu, founder of Ahan Analytics, LLC, wrote his dissertation on knowledge management, optimism abounded that the lessons and techniques covering a broad range of fields (from artificial intelligence to organizational behavior) could be applied to enable companies to leverage the data and knowledge they generate every day. There was a growing vision that workers in any industry would become empowered to help their companies in this process. Today, our mathematical tools are more robust than ever and our computing resources are faster and more powerful than ever. Accordingly, no organization should struggle to make measurable improvements in their performance with their data.

The corpus of knowledge on data-drive performance has grown rapidly over the past many years. Practitioners like Ahan Analytics, LLC are working hard to bridge the gap between the concept and practice of improving organizational performance with data and its analysis. For example, books such as “Hard Facts, Dangerous Half-Truths And Total Nonsense: Profiting From Evidence-Based Management” by Stanford Graduate School of Business Professor Jeffrey Pfeffer and “Competing on Analytics: The New Science of Winning” by Babson College Professor Thomas Davenport and Jeanne G. Harris are pioneering works that highlight issues relevant to data-driven business performance. Even in the fertile field of web analytics, work continues to formalize approaches for translating accumulations of data into productive value – see for example, “Actionable Web Analytics: Using Data to Make Smart Business Decisions” by Jason Burby.