Artificial intelligence has become an essential part of everyday life across the globe. Today, we rely on AI technologies to perform and facilitate many of our daily activities – from healthcare services to entertainment, learning and business management.

In this article, we will continue our series on the impact of cognitive biases on organizational transformation. To protect our clients against forming such biases, we, at ODEL, have reviewed and analyzed the lessons learned from some of the projects we conducted with our clients, and that were linked to cognitive biases. We will take you on a journey to identify such biases in the context of organizational transformation, with illustrative examples.

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Self-serving Bias
Self-serving bias is the tendency to attribute positive outcomes to personal actions, while blaming failures on external factors. On the organizational level, self-serving bias can be defined as the tendency of the organization or employees to attribute positive business results to internal factors (such as robust management systems, strong leadership, insightful decisions, etc.), while attributing failures and negative outcomes to external factors and force majeure that are out of their control. In both cases, however, the reasons for success or failure may be internal or external. To determine the real factors of success or failure, outcomes must be analyzed fairly and objectively away from self-serving biases.

This type of bias can show in different situations, such as when the organization decides to improve the operational model for one of its main services, which involves multiple parties. If the improvement efforts result in positive indicators and outcomes, the success will be attributed to the organization’s excellence in designing the optimized service model, robust governance framework, and efficient service level agreements. On the other hand, if the outcomes and indicators are negative, failure is blamed on external parties, factors, and reasons, such as non-compliance with the governance framework or service level agreements – among other external excuses. Likewise, when a service is disrupted or delayed, the blame is instantly and impartially cast on impaired capabilities and inefficient technical systems. So, all the blame and anger are unjustly directed at the “poor machine”, while in fact, the root cause of the problem is the organization’s failure to evaluate, assess and deploy the right capabilities and systems from the very beginning. So, instead of looking for the main reason for the failure, organizations fall victims to self-serving bias by putting the blame on endless number of excuses.

Optimism Bias
This type of bias leads you to underestimate your likelihood of experiencing negative outcomes, while overestimating your likelihood of experiencing more success than your peers. Sometimes, we fall into the trap of optimism bias when making decisions related to organizational development due to overconfidence in our decisions. We think that the organization’s current performance is much better than previous performance and our competitors’ performance. We feel that we have more experience and knowledge than our peers or other organizations. This may cause us to make subjective, overly-optimistic decisions, while underestimating the chances of facing negative experiences and, consequently, not putting the appropriate plans to avoid them.

Optimism bias can occur at any stage of organizational transformation, and can take many forms. One examples is when you go on to develop a transformation strategy without taking into account the organization’s culture or lessons learned from previous experiences; you have over trust in your own or your experts’ knowledge and skills, thinking that the current situation is less vulnerable to risks. Similarly, your overconfidence in your transformational decisions may cause you to overlook the need for developing an effective change management strategy, which is essential to ensure that changes are implemented smoothly with the least resistance possible.

The Confirmation Bias
It is the tendency to support the information that are consistent with our existing beliefs, while ignoring any evidence that does not accord with these. Confirmation bias can occur when analyzing a situation or working on a problem. For example, we may misinterpret the information and observations we have because of our tendency to analyze them based on internal motives or pre-conceived perceptions. This can happen when the biased person has gone through similar experiences in the past, causing him/her to use the same observations and conclusions they have previously made in a similar context. In other words, they tend to use the same interpretation they made during a similar previous experience, thinking that it would lead to the same positive results.

Suppose that you are working on improving a certain service/procedure and identifying the underlying problems or challenges. To do this, you need to analyze the efficiency of the operational processes, the employees responsible for implementation, and the IT systems used. If you start the analysis with a pre-conceived belief that the inefficiency of IT systems is the main challenge (based on the conclusion you have made during a similar situation), you will end up blaming the IT systems for the current problem, too. You will unintentionally look for the signs, observations and information which confirm your own pre-conceived belief, while ignoring any other information that does not accord with it. This can cause you to overlook the signs of other potential culprits (such as weak competencies, inefficient procedures,.

Functional Fixedness
Simply put, functional fixedness refers to the tendency to use or think of things in a fixed, specific way. This way of thinking impairs our ability to use objects in any new way other than the one usually used with it, or as the old saying described it: “If the only tool you have is hammer, you will treat everything as a nail. Applying this in the context of transformation projects, we may sometimes fall into this trap by strictly adhering to the traditional methods and solutions when carrying out transformational activities, without trying to look for new methods of doing things , or use the existing ones in a different way to achieve better impact. Falling a victim to this type of bias while working on transformation projects may cause us to stop our transformation effort when we face a challenge that traditional solutions cannot solve. We will not try to find new ways to overcome the challenge and end up with an unfulfilled transformation ambition.

When working on transformation projects, this bias can occur when we set a fixed framework for each element or solution throughout the transformation journey (e.g. human elements, IT elements…), while not trying to benefit from it in any other manner outside this framework. At the human element level, for example, you may limit the duties of the security staff to the conventional framework (guarding, and verifying the visitors’ identity), without giving them the opportunity to express their opinions regarding the major challenges facing visitors, or the complaints they receive from them. At the IT element level, functional fixedness biases can show in using the IT systems’ functions and data in the same traditional way without thinking of adapting them to maximize benefit. For example, you can adapt and expand the functions of your Interactive Voice Response system (IVR) by enabling it to sell your products/services.

Thank You!

Knowledge Library Team

ODEL

Riyadh