In today’s session of Leadership in a Global Context, we individually worked on the Organizational Behavior simulation. In the simulation, I assumed the position of product manager at Matterhorn Health and was presented with the issue of inaccuracies in the company’s GlucoGauge blood glucose monitor. When I was asked to address what was causing the problems with the monitor, I identified the major cause of the situation to be due to consumer misuse. Throughout the simulation, I was faced with different complex problems where I had to make some difficult decisions. 

I learned that cognitive biases are present in almost everybody’s decisions, even subconsciously. I also learned about different types of cognitive biases, how they present themselves, and how to prevent them. One bias we learned about is confirmation bias. This is when people look for information that confirms what they already believe. This was displayed in the simulation during the first choice when we had to decide what we believed the cause of the device malfunction was. We also learned about Sunk Cost bias. This bias refers to when someone continues to invest in something because of previously invested resources. This could be seen in the simulation when we were asked how much money to invest into different strategies to fix the malfunctions in the device. After each investment, there was no success. This was to test whether you would still invest resources after multiple failed attempts. The third bias we learned about is the anchoring bias. Anchoring bias is when the first piece of information made available during a decision making process strongly affects judgments, even when it is known that the information given is arbitrary. This bias was seen in the simulation when we were given a percentage from a doctor about how many patients were properly synching their data using the company’s app. An arbitrary number was given and an estimate was to be made right after. This estimate was likely a result of the original anchor number given. The last bias that we learned about is the Framing Bias. This is when there are subtle changes in the way choices are presented, especially when framed as gains versus losses. When something is framed as a gain, the observer tends to be more risk averse while when something is framed as a loss, the observer tends to be more risk seeking. In the simulation, a decision had to be made that would either save 200 of 600 jobs or have a 33% chance of saving all 600 jobs. The decision that was made was a result of whether the question was framed as saving jobs or losing them. 

To combat cognitive biases, it is important to first be aware they exist. I will begin observing biases in everyday occurrences. To combat decision-making traps, I will work in teams and have an unbiased coworker help analyze each decision to ensure that there are no biases being portrayed. It is important to have facts to back up every decision being made regardless of previous decisions that have been made. It is also important to keep an open mind about different decisions and review each decision with a different mindset. By seeing both the positives and negatives of a decision, a decision can be made fully knowing the consequences. 

The situation was most challenging when a decision had to be made that directly affected the employees of a company. Making the investment decisions was not as challenging because the money was fake and it did not seem as personal as a decision. On the other hand, thinking about how many employees you could save by making a decision, there was more of a personal aspect. I coped with the high level of ambiguity by filling in the blanks of the situations with both negative and positive situations. I tried to view the results of each decision in a way that would negatively affect the company and in a way that would positively affect the company. I made decisions based on what seemed to have less extreme consequences. I coped with the increasing levels of stress by ignoring the time restrictions. I took my time making each decision and did not let the rush of notifications distract me. 

A real-life scenario that mirrors the conditions of the simulation is when Tesla was held accountable for forcing workers to come into the factories to do work during the COVID-19 pandemic. Many of the Tesla employees contracted the coronavirus disease which was viewed with high levels of controversy. This situation was handled very poorly. No apologies were issued and instead when the CEO, Musk, made the announcement that employees could work from home, he later fired the workers that decided to do this.