The Failure of Risk Management. Douglas W. Hubbard

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CHAPTER 2 A Summary of the Current State of Risk Management

      People who don't take risks generally make about two big mistakes a year. People who do take risks generally make about two big mistakes a year.

      —PETER DRUCKER

      Before we start changing any system, it's a good idea to get a reading on its current state and to figure out how it got that way. Risk management is a very old idea that has changed dramatically just in the past few decades.

      The history of any idea brings its own baggage that often limits our current thinking on the concept and risk management is no exception. Institutions evolve, standards are codified, and professions mature in such a way that it causes all of us to think in more limited ways than we need to. So before we consider the current state, let's see how we got here.

A SHORT AND ENTIRELY-TOO-SUPERFICIAL HISTORY OF RISK

Organizational risk management could be said to have existed at least as early as the first time a king or chieftain decided to fortify walls, make security alliances, or store extra provisions in case of famine. Even more formalized risk management by agreement among parties seems to be a feature of the earliest civilizations. Since ancient Babylon, traders managed the risks of transporting goods great distances by having the buyers provide loans to the sellers that would be repaid with interest only when the goods arrived safely. The Code of Hammurabi by the Babylonian king of that name provided certain compensations or indemnifications for those harmed by bandits or floods. Babylon was also the birthplace of banking, where lenders managed risks starting with the careful selection of debtors.

      But throughout most of human history, risk management was an unguided mitigation of risks. Choosing what risks to prepare for was always a matter of gut feel. What differentiates risk management since the start of the Age of Enlightenment is a more systematic approach to assessing the risk. The development of probability theory and statistics in the seventeenth century enabled risk to be quantified in a meaningful way. However, the typical context of these mathematical investigations were well-defined games of chance. These powerful new tools would be adopted only in select industries for select applications and, even then, only slowly.

      From the eighteenth century to the beginning of the twentieth century, the quantitative assessment of risk was exemplified in—and largely limited to—insurance and banking. Although the term actuary predates even probability theory, it was not until the mid-nineteenth century that actuaries became an established profession with accreditation requirements and their methods had risen to earn the title of actuarial science.

Later in that period, we see quantitative risk analysis applied to financial markets and perhaps certain government agencies dealing with public health. Still, until the mid-twentieth century, the idea of a retailer or manufacturer using similar methods to assess risk in operations, new products, marketing campaigns, or major acquisitions was not seriously considered. For this reason, the executives in many firms may have treated risk management as synonymous with insurance or making sure the simplest and most obvious precautions are taken (and many still do today). At most, it was effectively a checklist approach in, for example, areas where safety was a key driver (aviation, mining, etc.).

      By the 1960s, new methods and tools were being adopted by professionals outside of traditional insurance: engineers and economists. The emergence of computers and the ability to generate thousands of random scenarios with quantitative models made it possible to do the math with uncertain inputs. Engineers in nuclear power and oil and gas were among the first to adopt methods like this outside of insurance. Economists were influenced more by mathematical fields of game theory and decision theory, which provided for the mathematical description of common decision problems, especially decisions under uncertainty. The methods of engineers and economists were both connected to the fundamental ideas of probability theory, and they were largely developed in isolation from actuarial science.

      By the end of the twentieth century, a fourth independent set of methods were being used as part of risk management, and these methods had almost no connection to the previous ideas developed by actuaries, economists, or engineers. Struggling to keep track of emerging risks, executives were hungry for a simple way to summarize the risk landscape, without necessarily adopting the more quantitative (and, at the time, more obscure) methods that came before them.

      By the 1990s the major consulting firms promoted an early version of a common risk communication tool known as the risk matrix as well as various qualitative risk ranking or risk scoring methods. These were simple to use and simple to communicate. In some cases, pressure to adopt some sort of risk analysis method quickly encouraged the adoption of the simplest method without regard to its effectiveness. Once one approach gains momentum, prudent executives had a growing interest in using a method that everyone else was using. Every shock to the system, such as natural disasters, recessions, terrorism, emerging cybersecurity threats, and more, encouraged wider adoption of whatever simple method was gaining a foothold.

Firms were caught up in a growing “risk culture.” In response to demand for more clarity, several attempts to make so-called formal methodologies for risk assessment and risk management have evolved. Some of these methods are codified in influential standards such as the International Standards Organization (ISO) and the National Institute of Standards & Technology (NIST) in the US. More variations on these have been developed by numerous consulting firms, and many companies created customized approaches based on the same ideas.

      If executives needed any more incentive to adopt risk management, СКАЧАТЬ