In the last few months I have given several talks to students getting graduate degrees in fields that involve analytics. For many of these students, their first question is “How do I get a job?”. Once we move beyond that, I talk about where analytics is used in companies. As exhaustive list would be exhausting, so let me give you some ideas and how you should think about them.
Let’s first look at this in one dimension. On the left we have some of the academic or technological disciplines that make up the broad field of what we call analytics.
You could study these and through examples learn some of the applications. With this approach you might say “I am an Operations Research expert. What are the various fields in which I could work that use analytics?”.
On the right, I list some of those fields of application. If you start on the right, you might ask “I am a supply chain expert. What disciplines within analytics should I learn?”. Those are on the left, though you may not need all of them.
A better way of viewing this is in two dimensions.
Here you get a better idea that the disciplines can be used in different application areas and the application areas need various technical expertise. You might go on from here and weigh the intersection points to understand if, say, Machine Learning is more important for Pricing or Supply Chain.
Here’s my advice:
- Among the disciplines, decide which you love the most and have the best aptitude. Go deep on those, but learn enough about the others so you know when a given solution will require them.
- If you are working on a team, seek out others who have skills that complement your own (this is good advice in general).
- If you are working in an application area, understand that broadly and know how the disciplines are used in each. Become expert in one or two of the disciplines but over the course of your career, learn more and more about the adjacent fields and pick up those skills.
- It is likely that if you start in one application area, you will be employed in another within 3 to 5 years.
- Shift jobs within your organization or between organizations to learn more disciplines and application areas. Beware becoming a mile wide and an inch deep: truly become an expert in some of the areas of technology and use.
- INFORMS – Getting Started With Analytics
- What We Do When We Do Analytics Research
- Some questions to ask yourself if you want to be a data scientist