BY RYNE A. SHERMAN
Organizations have a limited amount of financial and human resources. A fundamental problem for organizations concerns effectively and efficiently allocating these limited resources. The primary task of an organization’s leadership (i.e., the mangers and executives) is to make decisions about how to allocate resources. In modern businesses, such decisions are made all the time, and ultimately the success or failure of the organization is the cumulative sum of these business decisions. In an ideal world, leaders would direct money and energy toward activities that increase long-term profitability.
In practice however, leaders often designate time and money toward irrelevant projects. Indeed, Peter Drucker, the fabled philosopher of management, argued that the main reason businesses struggle is because the leaders make poor decisions. As a reflection of their poor decision-making, the base rate of managerial failure is startlingly high. A recent survey of the UK public indicated that 22% of people hate their boss, 52% of people name their boss as their main source of dissatisfaction, 20% would forgo a pay raise if someone would fire their boss, and an astonishing 12% of respondents admit to having imagined killing their boss. A similar survey of US adults indicated that 65% of Americans say they would prefer getting rid of their boss to receiving a pay raise. From the preceding it is reasonable to conclude that somewhere between 65-75% of business leaders are incompetent, and often this incompetence is the result of their poor decision-making skills.
Making good decisions about where and how to allocate resources in a business reflects one’s critical reasoning skills. Although most people understand the importance of critical reasoning, new managers and executives are rarely (if ever) selected based on their ability to make good decisions. Despite this, it is wholly possible to fairly and accurately evaluate business leaders in terms of their critical reasoning skills. Doing so simply requires understanding the underlying processes involved in effective critical reasoning.
A review of the literature on decision-making suggests that effective critical reasoning requires three things. First, it requires a clear-minded view of the problem to be solved. Too often leaders spend time solving the wrong problem or problems that are not actually problems at all. Second, effective critical reasoning requires a rational analysis of possible solutions to the problem. Some solutions to the problem are bound to be more effective than others. Third, effective critical reasoning requires an accurate forecast of each solution’s consequences. Some solutions may cause future problems (e.g., dumping refinery waste on public lands solves the problem of excess waste, but causes others) and the cost of various solutions needs to be considered. In other words, leaders with good critical reasoning skills (a) identify and understand critical problems, (b) come up with rational solutions to these problems, and (c) act based on the anticipated consequences of each solution.
Like most things, the human capacity for critical reasoning is rooted in our evolutionary history. Our hominid ancestors evolved as group living animals in an environment that was more demanding and less forgiving than ours. In the ancestral environment, survival depended on being able to solve a wide variety of problems on a recurring basis: finding food, water, shelter, and protection from dangerous predators; keeping peace within the group; and defending oneself and one’s family against attacks by competing human groups. If the group members did not solve these problems correctly, they died; those that solved the entire range of problems prevailed. But the demands of survival changed constantly. Only those groups that adapted and improved their survival techniques in the face of constantly shifting environmental pressures became our more recent ancestors—the ultimate winners in the race for survival. Improving one’s performance involves correctly anticipating future problems, recalling past performance that yielded positive outcomes, and figuring out what to do when the old methods and solutions no longer work.
One of the oldest ways to solve problems is to look for patterns in the environment and to use those patterns to predict the future. Early famers learned to predict when the Nile would flood by watching the stars; certain regular changes in the position of the stars guided the planting process. This model of learning is the essence of science. Science emerged and evolved through the process of detecting covariation (“When we do X, Y happens”). For many practical human purposes, this is as far as the analysis needs to go. One does not need to know why the positioning of the stars is related to when the Nile floods to make good decisions about when to plant. In fact, modern advances in artificial intelligence – including machine learning and neural networks – simply amplify this covariation detection process to build predictive models of future events.
Based on these considerations, it is apparent that critical reasoning includes both the ability to detect covariations (i.e., to identify sequences of events that go together reliably) and to recognize when the sequence is recurring or going to reoccur. At an even deeper level, critical reasoning also involves recognizing when covariations don’t occur. An alternative way of saying this is that critical reasoning consists of: (a) accurately forecasting sequences of events in the world, (b) recognizing when those forecasts do and do not apply, and (c) acting appropriately based on those forecasts.
From an ancestral point of view, critical reasoning reflected the ability to solve a wide range of problems correctly. Spearman similarly argued that “g,” or general intelligence, is the ability to solve a variety of problems correctly. Binet suggested that the optimal method for measuring intelligence is to give people many qualitatively different problems to solve. The same logic applies to the evaluation of critical reasoning: give people a series of problems and score them based on how accurately they solve them. It follows that business reasoning – or the ability to make good decisions about business problems – can be measured in a similar fashion.