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The Economics of Data, Analytics, and Digital Transformation

You're reading from   The Economics of Data, Analytics, and Digital Transformation The theorems, laws, and empowerments to guide your organization's digital transformation

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800561410
Length 260 pages
Edition 1st Edition
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Author (1):
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Bill Schmarzo Bill Schmarzo
Author Profile Icon Bill Schmarzo
Bill Schmarzo
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Table of Contents (14) Chapters Close

Preface 1. The CEO Mandate: Become Value‑driven, Not Data-driven 2. Value Engineering: The Secret Sauce for Data Science Success FREE CHAPTER 3. A Review of Basic Economic Concepts 4. University of San Francisco Economic Value of Data Research Paper 5. The Economic Value of Data Theorems 6. The Economics of Artificial Intelligence 7. The Schmarzo Economic Digital Asset Valuation Theorem 8. The 8 Laws of Digital Transformation 9. Creating a Culture of Innovation Through Empowerment 10. Other Books You May Enjoy
11. Index
Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics
1. Appendix B: The Economics of Data, Analytics, and Digital Transformation Cheat Sheet

Postponement Theory

Postponement is a decision to postpone a decision. Postponement occurs when one party seeks to either gain additional information and/or to delay the decision in search of better terms.

Postponement Theory is an economic strategy that maximizes possible benefits and minimizes risks by delaying a decision in order to gain additional data or analytic insights. That is, the decision maker believes that the benefits of delaying the decision while more data is acquired outweigh the cost of potentially making a suboptimal decision.

Data Ramifications: Postponement theory plays out when organizations decide to postpone a decision in order to gather more data and build more accurate analytics to improve the probability of making a "better" decision.

DEAN OF BIG DATA TIP:

Postponement theory is heavily influenced by the costs associated with Type I Errors (False Positive) and Type II Errors (False Negative) associated with that decision...

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