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Book Review: Monetizing Your Data by Andrew Roman Wells and Kathy Williams Chiang

For those of us firmly entrenched in the big data industry, we’re well familiar with the “collect data at all costs” mantra. So it’s no great surprise to see this new title that takes the story to its completion, specifically how to monetize all the data being stored away. My own personal recurring slogan is for enterprises to “maximize the value of their data assets” so “Monetizing Your Data: A Guide to Turning Data into Profit-Driving Strategies and Solutions,” by Andrew Roman Wells and Kathy Williams Chiang is a welcome resource.

Organizations are swamped with data—collected from web traffic, point of sale systems (POS), enterprise resource planning (ERP) systems, sensors of every type imaginable, and more. But once collected, what’s the end game? How do you make money? Monetizing your Data provides a useful framework and path to follow for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics.

There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns.

The book is a great practitioner’s guide, providing a practical, step-by-step framework that will allow you to immediately put the data monetization strategies into practice in your organization. Wells and Chiang deliver valuable insights that transform my need to make sense of your company’s data from an abstract desire toward a concrete next step. Not all of the methods outlined in the book are new, but the way that the authors bring together several methods (e.g., decision analysis, agile analytics, dashboard development) make the approach unique.

This book shows you how to use your data for the purpose of:

  • Monetizing your data to drive revenue and cut costs
  • Connecting your data to decisions that drive action and deliver value
  • Developing analytic tools to guide managers up and down the ladder to better decisions

Turning data into action is key – data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies. As the last section, the book includes a descriptive case study to prove the methodologies work well in the field.

You likely knew there is a reason why you should capture as much data as possible about your customers, but you may not have understood how to best leverage it. The book provides a step by step approach for turning your data into strategies that can drive revenue for your company. This is a good read for all classes of business owner.

Monetizing your Data is organized in the following sections:

  • Introduction
  • Decision Analysis
  • Monetization Strategy
  • Agile Analytics
  • Enablement
  • Case Study

The book may not be for everyone. It is tailored to business professionals, and MBAs likely will love its tone and temperament. If you’re a data scientist or data engineer on the other hand, it may be a more challenging read but still worth the effort.

The book comes with a companion website, providing templates, checklists, and examples to help you apply the methodology in your own environment. The expert author team provides authoritative guidance every step of the way.

Contributed by Daniel D. Gutierrez, Managing Editor of insideBIGDATA. In addition to being a tech journalist, Daniel also is a practicing data scientist, author, educator and sits on a number of advisory boards for various start-up companies. 

 

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