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

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We want to know the probability of a huge loss, the probability of a small loss, the probability of a huge savings, and so on. Would it be OK for you as the author of the post if I will create a mindmap of the book with reference to your article and publish it?

How to Measure Anything Book | Douglas Hubbard

The fact that one variable is correlated to another does not necessarily mean that one variable causes the other.If it’s something important and something uncertain, you have a cost of being wrong and a chance of being wrong. Hubbard’s book includes two case studies in which Hubbard describes how he led two fairly different clients (the EPA and U. But a very interesting pattern arose when I compared the function point estimates to the initial estimates provided by project managers… The costly, time-intensive function point counting did change the initial estimate but, on average, it was no closer to the actual project effort than the initial effort… Not only was this the single largest measurement effort in the IT organization, it literally added no value since it didn’t reduce uncertainty at all. I certainly wouldn't spend a lot of time optimizing to hire only carpenters and tell them to build the entire house. We will be talking about measuring such seemingly immeasurable things as the number of fish in the ocean, the value of a happy marriage, and even the value of a human life.

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

What we’ve found is a bit unsettling to data scientists: some of the things organizations currently measure are largely irrelevant or outright useless – and can even be misleading. Preliminary measurement method designs: Focusing on the few variables with highest information value, the AIE analyst chooses measurement methods that should reduce uncertainty. Though one must be ready to start learning about statistics, BI and analytics to use this knowledge in real world.As our work with leading public and private entities across the globe has proven, these obstacles can be overcome. In a business case, the economic value of measuring a variable is usually inversely proportional to how much measurement attention it usually gets. By the way, there's a mistake in the spreadsheet: when it assumes a uniform distribution it uses different bounds for two different parts of the calculation. In other words, if you don’t know how valuable a variable is, you may be making a measurement you shouldn’t – or may be missing out on making a measurement you should. The simplest tool for measuring such risks accurately is the Monte Carlo (MC) simulation, which can be run by Excel and many other programs.

How to Measure Anything in Cybersecurity Risk How to Measure Anything in Cybersecurity Risk

explaining why p-value hypothesis testing doesn't measure what the reader might think it measures (and thus Hubbard doesn't use p-value hypothesis testing). Given this information, what is the chance that the median time spent in such activities is actually below 7%, in which case the investment would not be justified?g., by demonstrating that people aren't doing their jobs, or that existing strategies aren't working or are counterproductive), and are therefore dangerous.

How to Measure Anything in Cybersecurity Risk - Goodreads How to Measure Anything in Cybersecurity Risk - Goodreads

Hubbard’s book explains the basics of linear regressions, and of course gives the caveat that correlation does not imply causation. The computer then calculates the outcome (in this case, the annual savings) for each generated combination of values, and we’re able to see how often different kinds of outcomes occur. For many decisions, one decision is required if a value is above some threshold, and another decision is required if that value is below the threshold. But it’s too costly to acquire perfect information, so instead we’d like to know which decision-relevant variables are the most valuable to measure more precisely, so we can decide which measurements to make.Some of the field's premier risk management approaches actually create more risk than they mitigate, and questionable methods have been duplicated across industries and embedded in the products accepted as gospel.