Cognitive biases to address
Cognitive biases refer to erroneous interpretations and presumptions that result from the brain’s alternate routes when processing data or applying previous encounters to unfamiliar circumstances. The consequences of cognitive bias in the workplace range from irritation to complete disruption (Cantarelli et al., 2020). Cognitive biases can be so pervasive that they can contribute to common mental illnesses among employees, leading to anxiety, addiction, and depression. Therefore, it is essential for employees to recognize cognitive biases and how they interfere with their productivity at the workplace.
Various cognitive biases impair the efficiency of employees and ruin projects in the workplace, and there is a need to find a way to handle them. The most common cognitive biases that would be necessary to enlighten employees are confirmation bias, false consensus effect, halo effect, Dunning-Kruger effect, and actor-observer bias (Kliegr et al., 2021). It would be critical to address the halo effect of cognitive bias among employees in the workplace. This is because employees tend to assume that colleagues who possess certain positive behaviors are generally individuals with good character. On the other hand, people who may exhibit negative attributes on one or two occasions are often considered bad people. Employees tend to believe that co-workers they get along with are more trustworthy than colleagues they rarely associate with. Such an assumption can negatively influence the delivery of services at the workplace since employees will often prefer those they are close to, even when other employees can do a better job.
Confirmation bias is where employees often associate with the information that supports what they already have or their existing beliefs. In such cases, employees have the tendency to be attentive to only information that upholds their line of thought, and when presented with contradictory evidence, individuals suffering from confirmation bias would either ignore it or alter it to justify their opinions. Confirmation bias can hinder the quality of service delivery at the workplace as it can limit employees from buying into new ideologies because the familiar patterns are so ingrained that change is viewed as an enemy (Kliegr et al., 2021). It may lead to incorrect decisions, an inability to listen to contrasting viewpoints, or even the exclusion of employees who have differing viewpoints. As a result, it is imperative to handle this type of cognitive bias in the workplace to foster healthy relationships among employees.
Identification of cognitive biases
There are effective exercises that can facilitate the identification of cognitive biases in the workplace, for example, creating awareness, conducting research, challenging individual beliefs, and trying a blind approach. Through carrying out research using test messages, an individual can identify various forms of cognitive biases in the way employees communicate with their target audience (Cooper & Meterko, 2019). The analysis of test messages from team members to a team member or employees to customers or subordinate staff to executives can tell if there are any cognitive biases in the workplace among diverse stakeholders.
An individual can identify cognitive biases by creating awareness since many employees and individuals suffer from many cognitive biases without knowing. By conducting an awareness assessment, it can be clear that people’s decision-making and perceptions in the workplace are influenced by various cognitive biases (Singh & Giacosa, 2018). Another exercise that can help identify cognitive biases is challenging the belief system of a group of people by expanding their sources of information and providing them with broader knowledge and several perspectives on the issue at hand. The type of cognitive bias an individual struggles with will be explicit when their belief system is confronted and challenged.
“Push-back” expected from co-workers
Since many people are afraid of confrontations and considering that individuals suffering from cognitive biases may not be aware of what they are going through, employees may oppose proposed changes to address various forms of cognitive biases differently. For example, certain individuals will ignore the strategies put across to help solve cognitive biases. A co-worker undergoing confirmation bias might assume the solution to the problem or argue in a manner that justifies their point of view of the situation (Cantarelli et al., 2020). Other employees might consider the confrontation of their biases as a personal attack due to their inability to admit the reality that they have cognitive biases.
Cognitive biases in different industry
The different cognitive biases that may face employees working in different industries include hindsight bias, misinformation effect, anchoring bias, self-serving bias, and optimism bias. The self-serving bias is where one can take credit for a good achievement and attribute it to hard work while faulting external factors for poor outcomes (Singh & Giacosa, 2018). For instance, a lead surgeon can attribute the success of a particular operation to their determination and work ethic. However, they can often blame other people and certain circumstances whenever the outcome is unsuccessful. This can result in faulty accusations even when the cause of the bad outcome is an individual’s responsibility. The best way to address self-serving bias is by being honest and consistently evaluating one’s progress on the assigned project to keep track of individual mistakes and achievements. When an updated record of the project’s milestones exists, one will know when they made an error or successfully executed the duty to avoid blaming others.
Cantarelli, P., Bellé, N., & Belardinelli, P. (2020). Behavioral public HR: Experimental evidence on cognitive biases and debiasing interventions. Review of Public Personnel Administration, 40(1), 56-81. Web.
Cooper, G. S., & Meterko, V. (2019). Cognitive bias research in forensic science: A systematic review. Forensic science international, 297, 35-46. Web.
Kliegr, T., Bahník, Š., & Fürnkranz, J. (2021). A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. Artificial Intelligence, 295, 103458. Web.
Singh, P., & Giacosa, E. (2018). Cognitive biases of consumers as barriers in transition towards circular economy. Management decision. Web.