This post is the third in a series of posts on the top 5 barriers to digital transformation. In our last post, we talked about the obstacles posed by organizational silos and lack of effective change management. In this post, we will continue on and look at barriers 4 and 5: poor leadership engagement and risk aversion.
4. Poor Leadership Engagement with Transformation Initiatives
The reality of digital is clear; even market laggards are seeing the necessity of investing in digital transformation. But in order for any type of organization-wide change to succeed and be effective, companies need the engagement and support of top-level executives. Unfortunately, for most organizations executive engagement with and support for transformation initiatives remains poor or non-existent:
- 71% of executives identified “understanding the impact [that] digital technology will have on their customer’s behavior” as their top digital transformation challenge (Altimeter Group)
- most companies lack CEO engagement or an organization-wide digital strategy and implementation plan
- fewer than a third of companies have significant executive-level engagement; when there is executive engagement, in most cases it is the Chief Technology Officer.
Without the support of top leadership, it shouldn’t come as any surprise that most of the digital transformation projects that have been implemented have failed to achieve the desired results. A McKinsey survey found that 70% of change programs fail to meet objectives, largely due to employee resistance and lack of support from management. In other words, digital transformation initiatives most commonly start in the middle, and organizations do not succeed in getting employee involvement because they do not have executive involvement.
Even when companies do have some executive involvement, that involvement is almost always constrained to the CTO – with little to no engagement from the rest of executive leadership. IT is expected to do most or all of the work of transformation, with poor support from the rest of the organization. This lack of involvement becomes even more pronounced when companies try to move from the development of digital initiatives to implementation; dedicated cross-functional teams are active at the development stage of transformation initiatives 51% of the time, but are only active 29% of the time during implementation.
So why does this happen? Why do the executives who are responsible for setting the direction of the organization fail to recognize that digital transformation isn’t just “IT’s problem”?
5. Risk Aversion and Unwillingness to Experiment
Business leaders and highly placed executives will often speak at length about the necessity of innovation in a highly competitive marketplace, but often their actions will speak to a deeply-rooted resistance to organizational learning and innovation. There is a fundamental disconnect between what business leaders say they value and the values they exhibit through their actions. The truth is that most organizational leaders will tell you that learning comes from failure, while their organization is structured to punish failure for any reason.
There are any number of biases that influence daily decision making, but the most relevant biases for our purposes are: Loss Aversion Bias, Status Quo Bias, Fundamental Attribution Error, Confirmation Bias, Existence Bias, Familiarity Principle, and Sunk Cost Fallacy:
1. Loss Aversion Bias
Loss Aversion is one of the biases that most significantly impacts organizational unwillingness to experiment. The Loss Aversion Bias shows that loss aversion is disproportionate to gain satisfaction; in other words – the loss we feel from losing $5 is disproportionately larger than the satisfaction we feel from gaining $5. Loss Aversion Bias causes us to avoid courses of action that will necessarily incur failure or loss, even when we know rationally that those courses of action will lead to more long-term benefit.
It is impossible to innovate without failure, but Loss Aversion Bias causes us to want to avoid failure at all costs.
2. Status Quo Bias
Another important bias to consider is the tendency to perceive the status quo as positive. This is an emotional bias rooted in human dislike for change. Cognitively, we tend to set the current state of affairs as a baseline and view any deviation from that baseline as negative. There is a large volume of research to support that Status Quo Bias is a bias that commonly affects many types of decision making.
3. Fundamental Attribution Error
Fundamental Attribution Error is a bias that causes us to attribute the behavior of others to purely internal causes while ignoring the context of their situation, while applying the opposite to ourselves. In other words, if someone else acts badly, we assume it is because of negative character traits or personal failings – whereas when we ourselves act badly, we attribute that to situational causes and minimize our own accountability. This also applies to success: when we succeed, we overestimate how much our successes are caused by our own inherent characteristics and underestimate the role of personal characteristics of others when assessing their successes.
The overall effect and its importance is that people tend not to recognize when failure was directly caused by their actions, and thus are not able to learn from their mistakes and move forward in a productive way.
4. Confirmation Bias
Confirmation Bias refers to the human tendency to gather or recall only that information that supports their pre-existing beliefs. The more emotionally-charged a belief is, the stronger the effect that confirmation bias will have. Additionally, confirmation bias will cause us to interpret even ambiguous data points as supporting our position.
Confirmation Bias creates problems when companies are in the research and investigation phase of their digital transformation efforts, because it causes executives to ignore research that challenges their assumptions and preferences and cherry-pick information that supports the direction that they want to go in – even if that direction is not strategically sound. Unchecked confirmation bias leads to decisions based on emotions rather than logic and information.
5. Existence Bias
Existence Bias describes the human tendency to treat the existence of a thing as inherent proof of its goodness, and to predispose us toward preferring things and ideas that are common over innovations that we are not used to. The importance of this effect is that, similar to the Status Quo Bias, it causes a preference for doing things the way they are commonly done and increases aversion to new products and ideas.
The most serious implication of unchecked Existence Bias is that it can cause cliched thinking and bad ideas to sound more legitimate the more we are exposed to them. Being exposed to an argument once or twice isn’t enough to induce an effect, but being exposed to an idea many times causes us to be more positively predisposed toward that idea.
6. Familiarity Principle
The aptly named Familiarity Principle is a concept developed by social psychology to describe the tendency for people to develop a preference for something mainly because they are familiar with it. The Familiarity effect has been demonstrated across many types of objects.
The Familiarity Principle is similar to but distinct from the Status Quo Bias, in that something can be considered status quo and yet remain unfamiliar to a particular person. It is also similar to the Existence Bias.
7. Regret Avoidance Bias / Sunk Cost Fallacy
Regret Avoidance Bias is more often known as Sunk Cost Fallacy. Both terms describe how humans like to believe that we make rational decisions about the future value of investments, but our decision-making is more often governed by emotion; the more heavily we invest in an object or course of action, the more reluctant we become to abandon it – even when there is ample evidence to show that we are making the wrong choice.
Regret Avoidance Bias is a well-understood phenomenon in finance, particularly in investments, as a phenomenon that drives people to ignore logic and make unsound emotional financial and business decisions.
What to do?
So with all these biases in play, how can companies eliminate bias from decision-making in order to avoid making unsound business decisions? We’ll look at how to overcome bias in our last post in the series.