Because CFOs are not actually superhuman, but just people like everyone else, they too are subject to a lengthy list of cognitive biases that influence our decisions and actions. In the corporate finance context, these biases, if unchecked, can have devastating consequences for company performance.
Finance executives steered by unbridled cognitive biases are less likely to meet their financial commitments, says Thomas Conine, a finance professor at Fairfield University and president of TRI Corp., which helps large companies execute financial-education and leadership-development programs.
“CFOs need to be aware of these biases,” says Conine. “They have them themselves, but they need to do everything they can through open communication with their people to nullify them as much as possible.” There are dozens of cognitive biases, though they’re not all distinctly unique; rather, there are many overlaps. Following is a discussion of some that are particularly relevant to corporate finance.
A confident breed by nature, CFOs are highly susceptible to this bias. It may the most common cognitive bias that leads to missed commitments. “People think they can forecast better than they really can,” says Conine. “While it may from time to time lead to tremendous results — possibly due to luck — it’s dangerous to assume that confidence will always lead to superior performance. While a win is wonderful, a miss can take an entire company down.”
Overconfidence may simply lead to an unrealistic over-promise on financial results, but there are many possible manifestations. For example, supply-chain managers may believe they can push effective internal productivity processes down into their vendors and get similar results, even if the vendors lack the resources, systems or technical ability to perform the asked-for analyses and tasks.
Opposite cognitive biases can exist at both ends of a spectrum. That is, confident executives still may be prone to unhealthy conservatism. For example, there is a tendency to overestimate the likelihood of low-probability events happening, where the consequences would be severe if such an event did happen.
At the same time, a conservative mindset may not fully take into account the reality that most operational risks are higher-probability events. “We underestimate the likelihood of those happening,” says Conine.
Finance does have to counter the enthusiasm of marketing, but excessive conservatism “will restrict your investment and constrain your future,” he notes. “A too-conservative culture leads to lower risk, but also to lower reward. You want to avoid bizarre risks but take prudent ones.”
Illusion of Control
This one is related to overconfidence. Reasonable people can differ with regard to whether something is controllable, but, Conine contends, finance executives think they have more control over basic things like price and sales volume than they really do. Those are driven more by market forces than anything else. There is very limited ability, for example, to successfully adjust prices in response to fluctuations in costs. If companies could always do that, none would ever lose money.
In fact, there are also limits on the ability to control costs. Conine tells of a major retailer that demanded a reduction in the price of its supplies, assuming that its large consumer market share would leave its vendors with no choice but to comply. However, many vendors responded with marketing initiatives aimed at competing retailers and were successful enough that they thwarted the big chain’s pricing demand.
Related to both overconfidence and illusion of control, this is a tendency to underestimate the time or cost of a project. But unforeseen things usually come up, and attention is distracted. “Most people don’t think through what uncontrollable things might happen to create a miss on the project,” says Conine.
He points to the experience of a manufacturer that was consolidating two separate plant operations into a single facility. While the movement and installation of equipment was carefully planned and documented, such other considerations as the time that would be needed to secure permits, hire qualified operators and transition the supply change to the new setup were dramatically underestimated. That led to a delay in anticipated savings and a negative hit to yearly results vs. commitments.
Data analysis is increasingly driving business, but the vast amount of data now available is driving gambler’s fallacy to prominence. That is, there is a tendency to discern patterns in data, even where the “pattern” was actually created by nothing other than random events. “This tendency is critical for any type of forecasting,” Conine says.
A classic example of gambler’s fallacy would be investing in a foreign operation based on recent currency trends. A period of steady improvement in an exchange rate may not reflect underlying economics as much as random events with short-term implications. Or, a business leader may base a financial commitment on cherry-picked pieces of positive information that appear to correlate with one another but actually don’t, when taking the entire operation into account.
This is a tendency to heavily discount the future. Since all we can see clearly is the past, that’s what often drives forecasts. One reason why finance professionals use metrics like net present value and time value of money is to avoid this tendency.
Hyperbolic discounting presents enormous risks. Conine tells of an internet marketing company that underestimated the future financial ramifications of new regulatory pressures on the industry. The company had been subjected to governmental scrutiny in the past but suffered few consequences, so management maintained a business-as-usual posture. In the end, the regulatory changes did have a major impact on business results. The company not only missed its financial numbers but also failed on its debt obligations. In effect, its business model was obsolete.
The thought of losing something you have is more abhorrent to people than not taking advantage of a new opportunity for gain. The pain of losing a dollar is worse than the pain of not acquiring a dollar. It explains in part the phenomenon of rogue traders like the London Whale: someone who experiences losses might go to almost any extent to get the money back, or at least cover up the loss.
Loss aversion can affect financial modeling. An operating plan may elaborately model “win” percentages for each potential client without giving as close consideration to potential or even actual losses from existing clients.
Recent events are weighed more heavily than distant ones. “Recent stock-market results are seen as more important than what happened in 1929,” says Conine, “but there could be a big mistake in that, because stock-market events are random. By resorting too much to recency you can be throwing out valuable information.”
He points to the example of a marketing-services company that acquired a recently launched lead-generation website that offered content similar to its own but was aimed at a different market segment. The acquisition was based largely on the site’s early success. But an extrapolation of that success into a predicted future growth rate didn’t factor in that while many new marketing websites have an initial success burst, greater time and resources are required to maintain the growth rate going forward. The website, while still successful, didn’t achieve the committed levels of traffic until 18 months after the acquisition.
This is a tendency to over-rely on one piece of information or fact set. It flourishes in very optimistic environments. You might be focused on the actions of a particular competitor, whereas you should be thinking more broadly. Or you might favor an approach because you’ve seen it work in the past, but it may not work in another context.
Conine says he has students quickly answer an arithmetic problem: what is six times five, times four, times three, times two, times one? Then he asks the same for one times two, times three, times four, times five, times six. While the two calculations of course yield identical results, when students don’t have time to figure out the actual answer, their average answer to the first is always a lot higher. They over-focus on the initial larger numbers the first time and the initial small numbers the second time.
He gives the example of a franchisor that was trying to grab market share from a larger competitor. Its operating priority in the effort was to employ company-owned (rather than franchisee) assets, in order to move more quickly and surely. But in making that priority, it overlooked factors that varied from market to market, like market size, population density and costs of operation. The misstep led to extremely disappointing financial performance vs. plan.
People tend to believe or do things because many other people do. In business, this often occurs where there is a strong leader who doesn’t invite diversity of opinion. It’s easy for everyone else to hop on board unquestioningly.
A few years ago, the for-profit education space was hit simultaneously with heightened government regulation and media scrutiny. A company that had built a successful marketing business in this area didn’t believe those events would have much of an impact on enrollment, because its research showed that baseline demand remained high. But the company failed to factor in the bandwagon effect. A groundswell of opposition to for-profit schools swept the country, and enrollment levels plummeted.
Image credit: Alejandro Zourilal Cruz, Wikimedia Commons