How to Measure Anything is a fantastic book. Here are the most significant insights you learn in the book
- how to measure anything; Hubbard actually comes through on the promise of the title - after finishing the book you will truly feel that the scope of what you can measure is massive. He does this by a change in the definition of what it means to measure something, but you realize his definition is more correct than the everyday intuitive one.
- value of information; Hubbard gives a good introduction to the VOI concept in economics, which basically lets you put a price on any measurement or information and prioritize what to measure
- motivation for 'back of the napkin' calcs; through his broad experience he has seen how a lot of the most important things that affect a business go unmeasured, and how his approach to 'measuring anything' can empower people to really measure what matters.
Reading this book provided one half of what I have been searching for for a long time - a framework for thinking about data science activities which is not based on hype, fundamentally correct and still intuitive and practical.
- how to measure anything; Hubbard actually comes through on the promise of the title - after finishing the book you will truly feel that the scope of what you can measure is massive. He does this by a change in the definition of what it means to measure something, but you realize his definition is more correct than the everyday intuitive one.
- value of information; Hubbard gives a good introduction to the VOI concept in economics, which basically lets you put a price on any measurement or information and prioritize what to measure
- motivation for 'back of the napkin' calcs; through his broad experience he has seen how a lot of the most important things that affect a business go unmeasured, and how his approach to 'measuring anything' can empower people to really measure what matters.
Reading this book provided one half of what I have been searching for for a long time - a framework for thinking about data science activities which is not based on hype, fundamentally correct and still intuitive and practical.