Every now and then when I catch up with some of my colleagues working at other companies or groups, I hear that they are absolutely miserable in their data science jobs! And it seems like most of the time, it isn’t the nature of the job itself that is the cause of misery, but some of the situations that arise during the course of the job.

Here below are two specific anti-patterns I’ve seen in context of analytics-related work. I’ve proposed some remedies as well, but obviously YMMV depending on your specific circumstances.

1. Data Science As An Insurance Policy

This is a scenario where you are asked to do some data science work to help “verify” a decision that has already been made. The typical offender is a “decision-maker” of some sort. In my eyes, this basically amounts to an insurance policy for the decision-maker. Here’s why:

  • When the analysis aligns with their decision, they have data to support their choice in the case that their decision pan out the way they expected.

  • When the analysis doesn’t align with their decision, they can say that the data quality was poor, the analysis was faulty/inadequate, [insert reason here], etc. In short, they may dismiss the analysis as non-helpful.

Remedy: There is likely more than one remedy for this. My typical playbook is to ask about potential actions the decision-maker will make based on this analysis up front. If there is no measurable impact to the business, the analysis will likely be de-prioritized on my todo list

In fact, this leads me to the second anti-pattern.

2. No Attribution for Insights

Imagine you did some excellent analytical work you were asked to do. In fact, some pivotal, positive business decisions were made as a result of that analysis. Will people remember you were the one that did that analysis 6 months later? As a mini thought experiment, have you heard the statistic that you have a higher chance of being in a car accident than in an airplane crash? Do you remember the exact statistic? Do you remember where that information came from?

My point is that the insight itself is more memorable than the source that generated it. To further complicate the situation, imagine your work environment is fast-paced and that the decision-maker(s) using the information is focused on demonstrating impact/relevance and moving forward as quickly as possible. In two weeks time, will they have a reason to remember the person behind the new insight? How about after 6 months?

Remedy: My proposed remedy for this is directly asking for appropriate recognition, doing talks around your company, or incorporating the “story” of “discovering” the insight, so your colleagues know you are the source of the insight.

Based on polling my own professional circle, it seems like analysts either will encounter, or have encountered these situations in the past. These are obviously challenging situations, and hopefully, these proposed remedies help!

If nothing else, know that you are not alone :-)


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