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

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When measuring risk, we don’t just want to know the “average” risk or benefit. 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. That’s what Monte Carlo can tell us. And of course programming is diverse enough to encompass a wide variety of needs and skillsets. Say, programmer A is great at writing small self-contained useful libraries, programmer B has the ability to refactor a mess of spaghetti code into something that's clear and coherent, programmer C writes weird chunks of code that look strange but consume noticeably less resources, programmer D is a wizard at databases, programmer E is clueless about databases but really groks Windows GUI APIs, etc. etc. How are you going to compare their productivity?

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

Wow, this is really exciting. I thought at first, "Man, quantifying my progress on math research sounds really difficult. I don't know how to make it more than a measure of how happy I feel about what I've done." When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of science. —Lord Kelvin (1824–1907),” The variables that had high information values were routinely those that the client had never measured… * The variables that clients [spent] the most time measuring were usually those with a very low (even zero) information value…Douglas Hubbard’s How to Measure Anything is one of my favorite how-to books. I hope this summary inspires you to buy the book; it’s worth it.

7 Simple Principles for Measuring Anything - Hubbard Decision

It's not that they're measuring the wrong variables, it's most likely that those organizations have already made the decisions based on variables they already measure. In the "Function Points" example, I would bet there were a few obvious learnings early on that spread throughout the organizations, and once the culture had changed any further effort didn't help at all. Nothing is impossible to measure. We’ve measured concepts that people thought were immeasurable, like customer/employee satisfaction, brand value and customer experience, reputation risk from a data breach, the chances and impact of a famine, and even how a director or actor impacts the box office performance of a movie. If you think something is immeasurable, it’s because you’re thinking about it the wrong way. It concerns me. Because business is already full of dubious metrics that actually do harm. For instance, in programming, source lines of code (SLOC) per month is one metric that is used to gauge 'programmer productivity', but has come under extreme and rightful skepticism.Can the thing be forced to occur under new conditions which allow you to observe it more easily? E.g. you could implement a proposed returned-items policy in some stores but not others and compare the outcomes. you should start thinking about measurements as a multistep chain of thought. Inferences can be made from highly indirect observations.” Another example: I took statistics on how my friends played games that involved bidding, such as Liar's Poker. I found that they typically would bid too much. Therefore a measurement of how many times someone had the winning bid was a high predictor of how they would perform in the game-people who bid high would typically lose. The bottom line is simple: Measurement is a process, not an outcome. It doesn’t have to be perfect, just better than what you use now. Perfection, after all, is the perfect enemy of progress.