Part 1 - Douglas W. Hubbard Demystifying the 'Intangible' - Why Everything is Measurable
Welcome to the first in a series of posts exploring the revolutionary ideas presented in How to Measure Anything and its related works on risk management and cybersecurity. Have you ever heard someone say, "That's too intangible to measure"? Perhaps it was about brand image, employee morale, risk, or even the effectiveness of a cybersecurity control. The central premise of these books, particularly How to Measure Anything: Finding the Value of Intangibles in Business by Douglas W. Hubbard, is that everything is measurable. This might sound audacious, especially when dealing with concepts often deemed purely qualitative, but the sources provide a clear framework and practical methods to achieve just that.
The core topic we'll delve into is the quantification of things previously considered intangible or immeasurable, especially within the domains of business, risk management, and cybersecurity. Douglas W. Hubbard is the president and founder of Hubbard Decision Research and the inventor of the powerful Applied Information Economics (AIE) method. He is the author of How to Measure Anything, The Failure of Risk Management, and co-author of Pulse and How to Measure Anything in Cybersecurity Risk. His work challenges the common notion that certain concepts lie beyond the reach of quantitative analysis.
Why is this important? Because decisions are made under uncertainty, and poor assessment of this uncertainty can lead to costly mistakes. Many popular methods used in risk assessments and management, even in areas like cybersecurity, don't withstand scientific scrutiny and can be no better than pseudoscience. This book aims to expose the flaws in ineffective methods and introduce readers to better, quantitative solutions.
The book How to Measure Anything is structured into four parts, with the first part making the fundamental case that everything is measurable and providing basic philosophy and examples. It's argued that a specific definition of measurement is critical to correctly understand the rest of the book. Measurement, in this context, isn't necessarily about perfect precision or using complex equipment; it's about reducing uncertainty. Even a small reduction in uncertainty counts as a measurement, especially if it's less than the uncertainty before the observation.
Hubbard's approach is not just academic; it's born from applying these methods to real-world complex problems like allocating venture capital, reducing poverty, prioritising technology projects, measuring training effectiveness, and improving homeland security. He found that while humans have a basic instinct to measure, it's often suppressed in environments favouring committees and consensus over simple, clever observations.
The journey towards measuring anything starts with accepting the premise that it can be measured. The sources suggest a universal approach to measurement, a five-step decision-oriented framework applicable to any measurement problem. This framework forms the basis of the Applied Information Economics (AIE) method. We'll explore these steps and key ideas in subsequent posts.
For those ready to challenge the illusion of intangibles, the invitation is clear: Write down one or more measurement challenges you face and read with the objective of finding a way to measure them. If these measurements influence a significant decision, the effort will be immensely rewarded.
Implementation Recommendation Step 1:
Identify a specific "intangible" concept or risk in your work or personal life that you believe is difficult or impossible to measure. This could be employee satisfaction, project risk, the value of a process improvement, or a cybersecurity threat likelihood.
Articulate why you think it's hard to measure. Is it the concept itself, the object, or the perceived lack of methods/data?. Keep this challenge in mind as we proceed, looking for potential measurement solutions.
Stay tuned for the next post, where we'll tackle the common misconceptions that make things seem immeasurable.