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A company named Matterhorn just released a new product, a blood glucose measuring device. After launching the product, they received reports from consumers about the inaccuracy of the data measured by the device. There could be two reasons for this data inaccuracy: device malfunction or consumer misuse. So the company did a vast investigation and found out that the main problem was device malfunction due to the uncontrolled condition of the test. They had two solutions for this problem: replacing the device or sending new stripes to the consumers.
They decided to go with the device replacement as it was more cost efficient. But the problem was not fully resolved so the company tried to focus on users misuse by simplifying the product brochure and running communication campaigns for doctors. This leaded to spending some amount of money from the company and laying off some employees. During this process four biases affected their decision making: Sunk cost trap, Framing effect, Confirmation and anchoring bias.
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In this report the effect of these biases and how to prevent them were analyzed. Also the decision style was assessed based on the facts provided in this case study.
During the simulation, I was faced to a crisis in the Matterhorn Company. The new blood glucose monitor device was having some issues with the accuracy of the readings. This information was based on the reports from users as well as their doctors. Our first guess was about the device malfunction due its new microprocessor which could fail to work properly in an uncontrolled condition out of the laboratory environment.
I was informed by other employees at the company that the device was tested both for adverse heat and humidity conditions separately but not simultaneously. The other reason could be patient misuse like misplacing the strip in the device. So, based on the information provided to me, I decided that the main problem was caused by the device malfunction. At this point, I was provided with some more information regarding the reports, but I still preferred to go with my initial decision. In this case, I could clearly see that I was more intended to confirm my initial decision by the new info instead of changing it. This means I was vulnerable to fall for confirmation bias arising in this situation.
Based on my initial decision regarding device malfunction, we had 2 options to solve this problem. First, we could send patients replacement for their devices. This could result in losing a huge loss financially since we had the other option to send new strips as a 3 month supply to the consumers which would save us more money. But the main problem arising from this situation was that we would have to lay off employees to cover the expenses. Our estimation was about losing 600 people. The cost of sending new strips could save us 200 jobs for sure while sending replacement devices would probably save 33% of the job loss and we could also be compensated from the contractor for the microprocessor for sending out new devices. Based on this information, I decided to send replacement devices to higher the chances of saving more money and preventing layoffs. This “preventing layoffs” was a gain frame in this situation which effected my decision. This shows how I fell into this framing trap while making my decision.
Our next problem appeared later as consumer misuse. We discussed about 2 options to solve this problem: 1) Communication campaign with doctors 2) Simplifying our product brochure. During this process, I was offered 4 times to spend some amount of money to support these resolutions. Each time, I decided to split the funds based on the information provided from other colleagues. There was an ambiguity problem here regarding using the funds. I was not informed that I had the option not to spend those funds each time. This lack of information and this sunk cost trap had an effect on my decision which lead me to use all the money each time.
At last, I was informed that the problem was not fully resolved. We had information from a doctor that his patients had problems syncing the data from the device to the smartphone app correctly. He told us that it could result from not syncing the data on daily basis. His estimation was around 10% of his patients doing monthly syncing. Since this information was provided by just one doctor, it got my attention that maybe there are more patients with the same problem. But since the doctor provided an estimation of 10%, I chose a number close to that (20%) to consider a larger group of patients. It can show that I was vulnerable to this anchoring bias based on the data received from the doctor.
The stress caused by the short amount of time that I had and lack of enough information, lead me to have bias towards my choices. I can see that I was most vulnerable to confirmation bias since my 2 choices were exactly the same. Also I was least vulnerable to the anchoring bias since my decision was over the average.
During the simulation, I was trying to consider all the facts for each decision. I was asking myself if there is any self-interest in any of the choices provided by other team members. I also wanted to make sure that we have explored are options fully. I should have been more considered about the alternative options as a solution to our problem (confirmation bias). I was also paying attention to the recommendations from other collages on how to spend the funds. I tried to check if they are making the recommendations based on the passed decisions. (Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before You Make That Big Decision. Harvard Business Review, pg. 51.)
As my main decision making style is both Directive and Analytic at the same level, it is apparent that I have made my decisions rapidly and I preferred simple and clear solutions. This has made me capable of working efficiently under pressure at the same time I was trying to analyze alternative solutions and I was willing to use new method and approaches to solve our problem. (Berkley, R. (2019). [PowerPoint title name]. Retrieved from MBA 522 spring 1 2019 on Blackboard.)
Based on the results and my experience from this exercise, I have learned that I should gather as much as information as possible and consider all the facts provided as the same level. By being more considerate about the small details provided in the reports and increasing the level of my awareness in stressful situation, I can prevent biased decisions. One of the challenges for me in this case study, was to make short-term versus long-term decisions and I had to prioritize my goals and solutions based on this fact. I have also learned that I was overconfident at some point about my decisions which is why I fell into the trap of making some biased ones.
Organizational Behavior Simulation: Judgment in a Crisis. (2021, Aug 17). Retrieved from https://studymoose.com/organizational-behavior-simulation-judgment-in-a-crisis-essay
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