Book Image

The Economics of Data, Analytics, and Digital Transformation

By : Bill Schmarzo
5 (2)
Book Image

The Economics of Data, Analytics, and Digital Transformation

5 (2)
By: Bill Schmarzo

Overview of this book

In today’s digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization’s data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company’s operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization’s digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon."
Table of Contents (14 chapters)
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Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics

DX Law #3: It's About Speaking the Language of Your Customers

Digital Transformation is about empathizing, ideating, validating, and quantifying the creators and inhibitors of customer value; it's about reinventing your business model to expand upon, exploit, and monetize those sources of customer value creation while eliminating the inhibitors of value creation.

Let's say that you are in the retail industry and looking to identify opportunities to combine digital technologies with customer usage insights (propensities) to eliminate barriers to customer value creation. That retailer would want to invest the time to empathize, ideate, validate, and quantify the sources and impediments of value creation for their customers. Figure 8.4 provides an example of how a retailer could reinvent the customer value creation process by emphasizing the sources and eliminating the inhibitors of value creation.

Figure 8.4: Traditional versus Digitally Transformed Customer...