Downsides of Being Data-Driven (3b Question)

While we usually talk about how important and frankly how much of a positive thing it is for companies to become data-driven from hiring someone for a job to deciding what to invest in, there are some clear downsides too. Some of them are: 1. Lack of good data. If your data is simply inaccurate, biased, incomplete it would lead you to make decisions that is not reflective of the real situation. 2. Being overtly reliant on data. If you’re just too reliant on numbers it can lead you to make dumb decision which without the data you would have not made. 3. Constraining your ability to take certain level of risk. I personally belive that in anything you do there is certain level of risk you take. Consciously or unconcisouly. There is no such thing as risk-free in my opinion. For example me deciding to take MIS 2101 course is a risk. What if I fail the class? Could significantly impact my GPA and will always be there on my transcripts but that does not mean I should not take the class. Without that I won’t be able to take higher level courses and as a result won’t be able to graduate. One another example that I think really kind of put the downside of being too data-driven is this: In 2021, When Bob Iger, CEO of Walt Disney Company retired ( he was reinstated as CEO last year) he gave an interview to NYT. In that he revealed that if Disney were to simply rely on data to make decisions on which movies/shows to make, the movie Black Panther (2018) would have never been made. That movies was a big financial and critical hit. This is just one of the example of the downsides of being too reliant of data.