Monetizing Your Data

CHAPTER 3Decision Architecture Methodology: Closing the Gap

One approach that gets inconsistent results, for instance, is simple data mining. Corralling huge data sets allows companies to run dozens of statistical tests to identify submerged patterns, but that provides little benefit if managers can't effectively use the correlations to enhance business performance. A pure data-mining approach often leads to an endless search for what the data really say.

This quote from the Harvard Business Review article, “Making Advanced Analytics Work for You,” by Dominic Barton and David Court, sums up one of the biggest challenges that exist in analytics today: organizations are throwing data at the problem hoping to find a solution versus understanding the business problem and aligning the right data and methods to it. The premise of this book addresses this shortcoming and we focus on the importance of connecting data to decisions in order to truly monetize the wealth of business data accessible.

The Decision Architecture methodology laid out in this chapter helps you make practical use of the waves of information flooding your desktop. The methodology provides a framework to translate the business problem into hypotheses, questions, decisions, action levers, metrics, and data needed to build an analytical solution tied to a monetization strategy. The monetization strategy is a major component to the overall methodology and has its own dedicated section.

The frameworks, techniques, ...