Should you know statistical models?

I’m working on an Executive MBA degree and my cohort is a blend of experiences and backgrounds from engineers to CEOs to doctors. During my last statistics class, we were learning about regression. One of my classmates asked whether or not we need to hire people that would do this work( stats) or if that is something we as leaders in the organization need to be aware of. That question is valid: should we at leadership level understand statistical models or should we hire people to do the work?

I think that the answer is both. Leaders within an organization dealing with data (whether business or tech) need to understand how these models can be used.  You also need to know that the people you are hiring aren’t just using tools that blackbox everything into drag and drop, but actually understand the models. I say this with caution as there are many tools out there that reduce development time and allow end users to quickly modify models without a lot of coding.

Let’s take an example: You want to hire a brand new team of data scientists because that is where data is going now. If you don’t have a data science team, you are missing out (says the industry trends).  Now, you’ve only worked with data by running queries in sql to get you averages, totals, and to some extent some forecasting in Excel. Should you understand what capabilities there are outside of the basics in order to grow your business with data? Yes! Absolutely. Otherwise, you wouldn’t know what to look for in your new hires or your new lead of data science. I say this knowing that many leaders may not know the math behind all these models.  So if you are a team lead, executive, or anyone working with data: go learn about what you don’t know. Maybe take a basics statistics course. You will build a stronger team; a team empowered with knowledge.

If you are an analyst that uses a tool that black boxes the model, go learn about it before using it. You will make better decisions knowing how the models work and you will be able to explain to other non-statisticians how to interpret the results and how to further use the models for their analysis.

Happy learning!