Interesting post, Manuel! It is fascinating that such analyses were conducted, and even more surprising that the results were that CEOs… may not matter. I agree that this conclusion cannot be treated as a fact because of the reasons you mention, but assuming this is true, I think it might be due to a lot of different factors:
Is it because individual CEOs have little power compared to the board? Or maybe because CEOs are not very diverse in practice (they tend to come from similar backgrounds, have similar experiences…)? Finally, how much time does it take for a CEO to see the results of his/her actions (we might risk attributing the merits of one to their successor)?
Great post, Carla! Microsoft’s example perfectly illustrates how data monitoring by employers is a complex issue and there is both pros and cons. In that case I see more pros, because the intent is 1. to learn how employees’ working habits adapt in this completely unprecedented situation and 2. ultimately improve their well being (which might lead to greater productivity and retention).
I personally can more easily draw a line when the data we are looking at becomes identifiable/personalized. It feels morally debatable to send managers information about the working habits of their reporters, even if the intention is positive. Moreover, it can be irrelevant (What if some employees prefer to work late because of personal obligations) or deteriorate trust (thus producing the opposite effect on productivity/retention). But of course, we can still consider testing this and quantify the impact.
Very interesting article, Tom! And it perfectly echoes my perception that data analysts should be extremely mindful of potential confirmation bias, and as you point out, they may be more vulnerable to these types of biases in the early stages of analysis.
What safeguards can we implement to protect analysts from jumping to conclusions too quickly? Should we go so far as to say that no third-party pressure should be put? I can definitely see that as a challenge when working with demanding clients, just like in consulting.
Very interesting point! Makes me wonder what part of the analyses that we do in business contexts is actually done to reassure ourselves that the problem we face can be broken down into a set of variables (ie. giving the illusion that we ‘understand it’) versus the ones that intend to thoroughly look at data and reach the best possible conclusion.
Thanks for your comment! I agree that being aware of potential biases in analyses can definitely make us better managers, and ultimately more confident in the conclusions we reach.