Just saying, a lot of people want to appear like they are productively exploring measures that yield changes and progress while tacitly sabotaging that very activity to retain political control over status quos. Most of these are also covered in other book from author "How To Measure Anything", but this book connect directly with cybersecurity examples.

How to Measure Anything Quotes by Douglas W. Hubbard - Goodreads How to Measure Anything Quotes by Douglas W. Hubbard - Goodreads

Bertrand Russell once said, “Mathematics, rightly viewed, possesses not only truth, but supreme beauty. Hubbard illustrates this step by telling the story of how he helped the Department of Veterans Affairs (VA) with a measurement problem. In the TQM world this comes under the heading "any metric used to reward people will become corrupt".That might work in an academic setting, but doesn't work in a real-life business setting where you're not going to tie up two programmers (or two teams, more likely) reimplementing the same stuff just to satisfy your curiosity. If no remaining variables have enough information value to justify the cost of measuring them, skip to step 5. And those very things most likely to be seen as immeasurable are, virtually always, solved by relatively simple measurement methods. Usually, though, only one or two iterations are needed before the VoI analysis shows that no further measurements are justified.

How to Measure Anything: Finding the - Yumpu Read Book [PDF] How to Measure Anything: Finding the - Yumpu

The ratio of time spent on work that counted towards your features over the work that didn't is your productivity metric. If a measurement is not informing your decisions, it could still be informing the decisions of others who are willing to pay for the information. A comprehensive guide to measuring anything and everything, from the concrete to the intangible, revealing the power of measurement in our understanding of business and the world at large.The book mostly repeats the message of How to Measure Anything: Finding the Value of Intangibles in Business - now with cybersecurity focus.

How to Measure Anything: Finding the Value of Intangibles in

Now that we know how to objectively confirm it, it (or rather, something similar but more accurate) is a scientific theory. Furthermore, I feel like the book was written to do a find and replace with any subject they feel like later. No matter what field you specialize in and no matter what the measurement problem may be, we start with the idea that if you care about this alleged intangible at all, it must be because it has observable consequences, and usually you care about it because you think knowing more about it would inform some decision.

Yet, just as the same procedure in arithmetic applies to multiplying any two numbers, the methods we will discuss are fundamental to any measurement problem regardless of whether it is mentioned by name. They also make a case against the much used risk-matrix and provide scenarios where a risk-matrix isn't just inaccurate but that it's lying to us. Seems to me that before a philosophical problem is solved, it becomes a problem in some other field of study. Those disciplines have measurement methods for a variety of interesting problems, and the professionals in those disciplines are already much less inclined to apply the label “intangible” to something they are curious about. After reading this book, my goal is that you will be able to identify methods for measuring each and every one of them.

How to Measure Anything: Finding the Value of Explaining ‘How to Measure Anything: Finding the Value of

In other words, the quantitative method you use to make measurements and decisions only has to beat the alternative. Much of the value we’ve generated for our clients has come through measuring variables that the client thought were either irrelevant or too difficult to measure.In addition, many major investments were approved with no plans for measuring their effectiveness after they were implemented. In a business case, the economic value of measuring a variable is usually inversely proportional to how much measurement attention it usually gets. Even with sampling information, the calibrated estimator – who has a Bayesian instinct – can consider qualitative information on samples that most textbooks don’t cover. Is “strategic alignment” higher if the profit went up by 10% but the “total quality index” went down by 5%?