How Risk Biases Impact Our Decision-Making

4 minute read

During times of uncertainty, decision-making can be heavily impacted. As we have discussed previously, a study examining companies’ performance before and after different recessions found that just nine percent of organizations “roared out of the recession,” and 80 percent still struggled, even three years after the recession. What was the differentiator between the few that thrived and the many that lagged behind? Research suggests that it’s a company’s strategic posture - how an organization adapts to allocate and deploy resources. “Even in the best of times, many companies fail to fund and staff new opportunities, and not for lack of good ideas...In practice, it’s often easier to make a $1 billion acquisition than to find $10 million to internally respond to or prepare for market shifts.” This, in part, has to do with the way that we assess and view risk. 
 
Two major biases influence our risk assessment: loss aversion, and narrow framing. Loss aversion refers to our tendency to over value the prevention of loss rather than the potential of equivalent gains. For example, you would probably be more upset about losing $10 dollars than finding $10. This is why even if there is an opportunity to gain something, we are often more likely to keep the status quo unless there is an overwhelming reason to change it. Narrow framing refers to the tendency to “weigh potential risks as if there were only a single potential outcome...instead of viewing them as part of a larger portfolio of outcomes.” For example, you might be more willing to put down a bet on tails if the coin was flipped five times rather than once. 
 
Putting it together, loss aversion and narrow framing can skew our perceptions and evaluations of risk. In an investment case, if you were deciding whether or not to invest $50 million in a project today that had a 50 percent chance of a $100 million or $0 return a year from now, the $50 million loss feels more large than the $50 million gain. “[T]he upside would have to be almost $170 million to entice the typical risk-adverse manager to make the investment,” despite that rationally, any amount greater than $100 million would be the point when potential gains outweigh the potential costs. Now, consider if that investment was to be made across multiple projects instead of just one. “In this case, the same manager would be willing to invest if the upside were only $103 million, or only 2 to 3 percent above the risk-neutral point.”
 
Given the many decisions that are part of the capital allocation and evaluation processes, how can we ensure we make better ones? 
 
At the organization level, leaders need to break away from making emotional allocation decisions. They should consider a strategic frame for resource reallocation decisions, and focus on a future vision rather than the status quo. Then, leaders can help reform the budgeting process by providing boundaries of what types of projects will be funded, and what metrics will be used to evaluate existing and proposed projects. 
 
Individually, there are a few ways you can improve your rational decision making

  1. Identify the type of data you are working with. Is it salient data, which stood out and caught your attention because it’s irregular, or is it patterned data that appears to have a regular trend. Or, is it contextual data, in which you need to carefully consider the frame to accurately interpret it?
  2. Recognize the related biases this can bring to your evaluation. Salient data can cause salience bias, in which we tend to weigh information that stands out as more important. Contextual data can cause framing bias, it can impact how we interpret the message through the way the data is communicated. Finally, patterned data can cause a clustering illusion, in which we erroneously attribute random events as predictors of future events. 
  3. Understand what you need to know the most. We can’t always have all the information when making decisions, but what is the most important piece of information that you need to understand the situation? What difference would this information make, and how would you use it?
  4. Ask the right questions. Organize your questions to capture the four categories of behaviour, opinion, feeling, and knowledge. “This ensures that you’ll bring both distance and a variety of perspectives to the way you probe your data, which will help you counter preconceived assumptions and judgements,” and understand what lens they are being filtered through.

This work was funded by Viewpoint Foundation.