Biases. A common language, methods and challenges to be considered.

Awareness and interest in the effect irrational decisions have on business performance has grown substantially over recent years. Yet, investors are often left wondering what kinds of irrational decision-making are the most problematic, and what to do about them.

At Behaviour Lab we focus on five groups of biases that have the greatest effect on investors. We identify specific examples of these biases and how they affect performance, and provide practical solutions to mitigate their impact.

Investors are there to make well-calibrated decisions, but unfortunately this is not always what happens. Actions may instead be based on strong convictions that are not necessarily founded in rational facts – leading to unnecessary risks.

The need to act in this fashion is often a result of the investor being driven by a sense of overconfidence in how much she knows in comparison to others, and over-optimism of her own scenarios.

There are several forms of overconfidence and over-optimism, but they all lead to one thing – a loss in performance.

In the 1980s Ray Dalio, founder of Bridge Water Associates, was convinced, based on his models, that the U.S economy was going into a depression. The firm strongly positioned itself in accordance of this scenario. Instead, the US experienced an economic boom.

“I was dead wrong! Being so wrong – and especially so publicly wrong – was incredibly humbling and cost me just about everything I had built at Bridgewater.”

“There I was after eight years in business, with nothing to show for it. Though I’d been right much more than I’d been wrong, I was all the way back to square one”

This one instance of overconfidence was all that we required to nearly wipe out the entire business.

Dalio and Bridge Water Associates has since successfully recovered, in part due to this experience. Dalio learnt, not necessarily to have less conviction in his investments, but to ensure they were also well diversified.

On the other side of the spectrum you have the investor who is more prone not to take action, finding it hard to make decisions and act on them.

This group of biases includes loss aversion, anchoring, status quo and the endowment effect.

All of these biases lead the investor to prefer leaving things as they are. This is why we see asset allocators investing more than 90% of their assets repeatedly in to the same assets , or why fund managers lose on average 100bps per year by ignoring alternative investments.

The list of great leaders and companies that have resisted the need to change is endless. Prominent examples include Kodak, Nokia, National Semiconductor, Sprint, Dell, and the cost of their lack of action is clear to all.

Innovation is occurring at digital speed. It is estimated that 50 percent of the S&P 500 will be replaced over the next 10 years. In 1965, the average tenure of companies on the S&P 500 was 33 years. By 1990, it was 20 years, and is forecast to shrink to 14 years by 2026. There has never been a time when doing nothing, be it as a result of anchoring, status quo or the endowment effect, has been costlier to both companies and investors than now.

Experienced investors bring immense value and expertise to the table, and many rightfully claim that much of that comes from recognising historical patterns. Often, however, such patterns no longer hold true, or were never objectively there in the first place.

With the constantly increasing number of data points investors are exposed to at any given time, they are also at a growing risk of finding miscellaneous data to underpin their views and arguments for patterns.

In his book, “The Little Book of Behavioral Investing: How Not to Be Your Own Worst Enemy.”  James Montier, strategist and member of the asset allocation team at GMO, reflects on this challenge.

With the increasing amount of data available to investors, he says, the whole investment industry is becoming obsessed with learning more and more about less and less. Montier argues that additional data isn’t used to seek more accuracy, but instead is employed to grow confidence in existing theses.

Biases associated with this group of pattern recognition biases include, for example, false analogies, where experience leads you to compare situations that are not directly comparable.

Another is confirmation bias, where investors favour data or evidence supporting their investment case and underrate the importance of contradictory evidence.

Combining preferential data bias with the increasing speed of innovation and change often leads investors to jump the gun and detect patterns where none exist. This leads to costly mistakes and considerable losses to profitability.

There is little need to debate whether misaligned incentives, where personal interest is sought at the expense of a company’s or fund’s overall interests, destroy value for companies, its employees, shareholders and unit holders. We can simply accept that they do, and materially so.

What is perhaps not as frequently thought of, however, is the misalignment caused by peoples’ inappropriate emotional attachment to individuals and elements of businesses. Inappropriate emotional attachment is a major source of bias and significantly harms performance.

Take the example of Bill Ackman, founder of Pershing Square Capital Management, and what has become his infamous short bet against Herbalife. In 2012 Ackman shorted the stock, calling the nutritional supplements company a pyramid scheme that he thought would eventually go to zero. Early on, Ackman stated his position in a three-hour presentation at an investment conference, subsequently having several public disputes with rival hedge fund manager Carl Icahn, founder of Icahn Enterprises. Theirbattle about Herbalife was so notorious it culminated in documentary in 2016 called “Betting on Zero”. Having been this vocal and public it would have been very difficult to remain emotionally unattached to the investment. With his own pride and reputation being at stake, his actions had lead to an inappropriate emotional attachment towards Herbalife. It was not until March 2018 that Ackman finally exited the position, at the cost of one billion dollars to Pershing Square Capital Management.

When working with private equity firms, we have found that risk assessment is particularly prone to interest bias. The responsibility of assessing risk in potential deals is often designated to the younger team members, where it is very unlikely that highlighting risks to investments that could ultimately stop a deal from happening would be in their interest. As a result, these factors go ignored, and the risk of default is significantly higher.

It is generally accepted that the many are smarter than the few, and collective wisdom shapes successful businesses.  As well as adding wisdom and diverse thought, businesses often use committees or groups to reduce individual biases. In many cases this is very successful, in others less so.

The main reason this approach does not always work is that biases often develop within a group as they strive for consensus and look to avoid confrontation. Seeking the path of least resistance can result in groupthink, where realistic appraisals of current or alternative courses of action are lacking.

Another form of social bias is sunflower bias, where groups align with the views of their leaders, whether that be from admiration or fear.

A fascinating example of the two combined was Sir Richard Greenbury, who joined Marks & Spencer at the age of 16 and rose to become chief executive and chairman.

In the mid-1990s, under his chairmanship, it seemed that M&S could do no wrong. The retailer dominated the high street; its management was held up as an example to other businesses. Sir Greenbury led M&S to record success but then failed to admit the need for change in a shifting fashion market, which precipitated a dramatic collapse in the company’s fortunes. This would nearly cost the 100 year-old retailer its independence in 2004.

One problem that led to this incredibly collapse was that nobody around Sir Greenbury would challenge him, firstly because of the tremendous success he brought the organization, then later due to what became a culture of fear. In retrospect, his nickname within the organization “big fellow” says a lot.

In a documentary reflecting on the demise of the fashion business of Marks & Spencer, board members spoke of how, despite great concerns of where the chairman was taking the business, nobody dared to speak up, instead preferring to avoid confrontation.

As a result, the organization has still not managed to recover within fashion, the element of its business that used to be their key driver of profitability.

Corporates are often aware of the risk groupthink poses to decisions made by committee. What they are less cognizant of, and something that we repeatedly see when working with executive boards, is the sunflower effect that occurs amongst those who bring the material and proposals to the committees in the first place. individuals have often formed views of what it is that the committees want to see, and in order to please them, they ensure that this is in fact what the committee gets. As a result, risks are substantially under reported, and alternative investments are missed.

Debiasing Methodologies

Biases are notoriously difficult to overcome in decision-making, but it is possible and there are numerous methods and approaches an organization can use to make the decision-making process more structured.

At Behaviour Lab, we use more than eighty different methodologies, specifically tailored to our clients’ needs. The methodologies fall into the following three buckets:

Implementing formal structures and roles can embed analytical and debate counter measures within the organisation. Some of our clients use for the most pressing problems, for example, separate teams (a “red team–blue team” approach) to independently develop investment recommendations, as well as other techniques such as rolling budgets.

Debate counter measures are practical techniques that debias conversations, meetings, and recommendations that lead to a decision. Techniques may include pre-mortems, reframing and vanishing options.

Automated processes and analytical counter measures. In some cases, the right method to debias a decision-making process can be through automation. We increasingly see our clients use automation to reduce the human judgement to reach decisions in areas such as research.

Other analytical methodologies we help clients to implement include scenario analysis, real option valuation, and reference class forecasting.

Before deciding on which debiasing techniques to incorporate into an organization’s or team’s decision-making processes, there are several factors and challenges that we at Behaviour Lab think need to be considered.

Improving decision-making in an organization is rarely about one individual fighting their own demons in solitude. Instead, to be truly successful, improving decision-making requires a decision-making process that targets different biases throughout the organisation and limits their impact. This demands a significant commitment and, in some organizations, a profound cultural change.

Successfully making these changes will not only improve decision-making processes and reduce the effect of biases, but to do so where it matters and in an effective fashion. This is why we at Behaviour Lab want organizations to think of the following four things:

Investors only have a limited amount of time. A first step is to find the types of decisions that warrant the effort, by considering:

  • Which type of decision would generate the largest benefits, where they improved?
  • Where does the individual, team, or organization believe they can change?
  • How much time and effort would be required?

Which biases result in the most negative impacts are not always clear. At Behaviour Lab we analyse several different types of data in order to draw accurate conclusions, for example:

  • Outcomes of decisions
  • The process leading to those outcomes
  • The driving forces that lead decision-makers to act in one way rather than another

Organizations should select mechanisms that are appropriate to the type of decision at hand, to their culture and decision-making styles, as well as the personalities of their decision makers. In most instances what is needed is not simply embracing off-the-shelf methodologies, but tailored techniques that meet the specific needs of the decision-making process in question. At Behaviour Lab we work closely with our clients to ensure that bespoke debiasing methodologies are implemented into their decision-making processes, and that they do not have any unintended negative impacts on other areas of the decision-making process.

By embedding these practices in formal corporate operating procedures (such as capital-investment approval processes or performance reviews), the organization can ensure that techniques are used with some regularity and not left to the responsibility of the decision-maker alone. This ensures the decision-maker feels supported, receives the help and resources they need, and provides a critical feedback loop from which to learn and continuously improve.

The behavioural-strategy journey requires effort and commitment, but the payoff—better decisions —means it is one of the most valuable strategic investments organizations can make.