How to Measure Anything Workbook: Finding the Value of Intangibles in Business

CHAPTER 7 Quantifying the Value of Information

LEARNING OBJECTIVES

• Explain Expected Opportunity Loss, and learn how it is calculated.
• Learn how to compute EVPI for ranges.
• Explain the difference between EVI and ECI curves and a practical implication.
• Define and give examples of a common “Measurement Myth.”
• Define and give an example of “Measurement Inversion.”
• Review definitions for “uncertainty,” “risk,” and “information value.”

CHAPTER OVERVIEW

Chapter NaN focuses on how to compute the value of information for decisions and how this affects measurements. Expected Opportunity Loss (EOL) is a simple calculation of risk, which is equivalent to Expected Value of Perfect Information (EVPI). Discrete, binary outcomes have an easily computed EVPI. Uncertainties are frequently expressed as ranges and EVPI calculations for those situations are discussed. The book and website provide tools for calculating EVPI for ranges. While EVPI represents uncertainty elimination, uncertainty reduction is a more practical goal, so general considerations are provided for calculating values and costs of uncertainty reduction.

It is often thought that the more uncertainty you have, the more data you will need to reduce it, and this chapter describes why the exact opposite is in fact the case. In addition, more attention is incorrectly paid to measuring variables of lower economic value, a phenomenon the author refers to as “measurement inversion.” These tendencies are seen across business sectors. ...