Week 2

Based on observations of my workplace and interactions with colleagues, I have identified confirmation bias as an important theory for writing good consulting reports at my company, specifically how to avoid confirmation bias, or any bias, when writing reports. Confirmation bias is cherry picking specific examples to fit a theory, instead of getting a representative and large sample size. Confirmation bias can even be seen in trying to find examples to fit leadership theories. At my company I have to be weary of confirmation bias, especially when researching exciting tech startups that I find myself rooting for. Especially in the grid-tied battery storage industry, there are numerous startups which claim to have revolutionary efficiency and levalized price per kWh, however many of them are still in the testing state and these are just “claims” that cannot be taken seriously. Although it can be easy to get excited and want to promote these technologies as a way for more renewable energy to take off, I must proceed with caution and not only pick data that I find in support of these companies. Often, after further research, I will find evidence against these technologies which I must also include in my report so clients have an unbiased view that is not marred with one sided evidence. As a result, I now have a greater understanding of why things can move slowly in the industry. Although it can be easy for someone new, like myself, to get excited about several new and exciting startups, more senior team members have seen plenty of these startups make bold claims and fail, and thus are more cynical and careful about confirmation bias. Even using Google can be susceptible to confirmation bias. Depending on how I search things, I will likely only get results which confirm my hypothesis. A trick I have picked up is to pretend I am arguing against something and adjusting my google searches towards this end. The truth is always somewhere in the middle, but reading evidence on both sides gives me a better change of distinguishing biased opinions from factual evidence in my research. Since this is not a fool-proof method, I will also join senior consultants in interviewing experts in the industry. The first level of research is mostly done online, however interviewing various stakeholders is further insurance against confirmation bias. We interview a wide array of experts which also helps keep us unbiased when writing reports.

 

 

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