Michael Koukounas

About the Book

One of the secrets to using data, analytics, and systems to drive business impacts is: "No matter how good analytics are, analytical solutions only add value if they can be consumed." While I have observed average analytics that had hundred of millions of dollars of impacts on their originations' P&L, I have also observed brilliant, world- class analytics that have sat on a shelf never been used. In today’s Big Data Crazed-world, I too many companies are repeating the same mistakes I have seen made throughout my career: Before launching an analytic, they don't consider all the barriers that need to be dismantled in order to make their analytics usable.

For example, I was once asked to manage an analytical team for a large global bank. When I took over the team, I reviewed its recent work. I was surprised to find that, had over the past couple of years, the team developed over a dozen analytical solutions that no one was using. I initially assumed quality issues must have been involved— and was take aback when I learned they were excellent analytics, many exceptionally ingenious.

I soon realized, though, that the team had not considered how these analytical solutions were going to be consumed. Those very smart Ph.D.’s were focused on developing elegant, powerful analytics; they failed to consider how to develop the analytical solutions in order to ensure that they could be implemented and used to drive business impacts.

Many barriers exist to making analytical solutions consumable. Failing to even identify those barriers can be very, very expensive. This book provides a concise guide to recognizing them and describes effective ways to surmount them.
Chapter 1: Analytics In The Real World

Chapter 2: What’s "Analytics"?

Chapter 3: The Atom Method Of Developing Analytics Capabilities

Chapter 4: Access To Data

Chapter 5: Talent

Chapter 6: Operational Knowledge

Chapter 7: Maintenance

Chapter 8: Analytical Organizations Come In All Shapes And Sizes

Chapter 9: Trade-Offs Between Efficiency And Creativity

Chapter 10: Organize To Ensure Continuity

Chapter 11: The Great Debate—"Which Expertise?"

Chapter 12: Size Of The Analytical Team

Chapter 13: Analytics Resource Functions

Chapter 14: Deep Analytical Talent

Chapter 15: Analytical Maintenance Teams

Chapter 16: Research And Development Teams

Chapter 17: Step One—Defining The Problem

Chapter 18: Step Two—Identifying Touch Points

Chapter 19: Step Three—Understanding Your Touch Points

Chapter 20: Step Four—Selecting Data

Chapter 21: Step Five—Analyzing The Data

Chapter 22: The Future
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