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)
10
Other Books You May Enjoy
11
Index
Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics

Creating the Collaborative Value Creation Framework

Data and analytics are powerful assets in which to invest, but organizations struggle to assign these intangible assets their appropriate economic value. Assigning the appropriate value to these digital assets is important if organizations want to maximize their economic impact and optimize organizational investments in data and analytics.

Organizations need a framework—what we will call the collaborative value creation platform—that maximizes the economic value of data and analytic assets across the organization.

Step 1: Prioritizing Business Use Cases

To quantify the value of these intangible data and analytic assets, we need to find a basis point around which the organization can establish the prudent value of the data and analytics. We will use the organization's key business use cases (for example, acquiring more customers, reducing customer churn, improving the quality of care, improving customer...