Worst Case Survival Handbook: Analytics Edition
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Analytics and Sports

Worst Case Survival Handbook: Analytics Edition

Probably the most frustrating situation for an analytics professional (working in sports or not) is to have put together a piece of work that you find completely satisfying and its value is completely obvious to you (whether it be analysis or other tool) and see that it is unused and ignored by everyone who could benefit from it. This is not the same as delivering analysis that was well crafted, only to find the decision makers go against the recommendations of the analysis - that is just a case of losing an argument. No analyst will win every argument (nor should they), and losing the argument is of course frustrating, but as long as the analyst is heard in the argument, the work is having impact.

The worst case scenario described above is the case where the analysis or the tool are just simply ignored. I don't know anyone working in analytics for any period of time that has not run up against this situation. They have had a great idea, poured hours of effort into it, and made sure that they have something that they believe to be truly valuable. They then roll it out for the decision makers only to quickly realize that their time could have been better spent rewatching season one of Friday Night Lights, because great work that goes unused is just wasted.

It is easy for the analyst to blame the decision makers for ignoring their brilliance, but after a pep talk from Coach Taylor (Clear Eyes, Better Data Sets, Can't Lose), though, the analyst needs to come to grips with why the work got wasted, to better position their next bit of genius to actually make an impact. The truth is, that usually when the work is truly insightful and/or useful, it has failed because the analyst has done a poor job of selling it.

Analysts are really good at imagining new tools and analysis and building the relevant systems and reports. When that is done though, too often analysts expect that their brilliance will just be recognized and the decision makers will start utilizing their work to gain the competitive advantage that the analyst envisioned. The reason analysts think this way is because that is how they have been trained. Analysts get trained in school by great statisticians, economists, and computer scientists (and other academics) that are experts in their fields, so believe in the value of the tools. While they are being trained, analysts never have to sell their professors on the idea that new ideas and strategies for analysis are worth pursuing, that is what they are there for. Instead, analysts get feedback on the quality of their work and told how to improve the work itself.

Once the analyst is working for a team or other business, they have to start thinking beyond improving their analytic abilities and work product, and begin to think about how to engage people who are not trained in analytic disciplines in their work. In sports, the analyst is faced with a group of decision makers who have been very successful throughout their careers without ever having to think about regression analysis of data visualization. They are experts in their sport, and have to be convinced that they need to change their process.

This is a different frame of mind for most analysts and it requires rethinking how analysis and new tools are presented. Analysts need to think about what in their work would motivate a highly successful person to change the way they make decisions. Once analysts can think in this mode, they often are able to conceive of better methods for presenting their ideas and tools. Instead of sending raw output from R to a coach (yes, some analysts have actually tried this) they can imagine that a coach could more readily engage with visualizations and/or video that present the concepts the analyst is pioneering, but grounded in a context that is far more familiar to the coach.

The one caution to the analyst though is to not think of this as dumbing down the analysis. Typically, the analyst is no smarter (and often less so) than the decision maker they are trying to communicate with. Instead they are simply trained in a different language, and it is incumbent on the analyst to find the proper translation from their language to the language of the highly successful expert.

While it is probably impossible to have every great idea implemented in a meaningful way, analysts will find their odds of success are greatly improved when they can, once the analysis is done, think through the process of motivating the decision makers to utilize it.

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