Reflecting on a Year in Consulting: Operations Research in Practice


It’s been a year since I transitioned from academia to consulting, and I’ve been reflecting on how different operations research feels in these two worlds. Here are a few observations that stood out to me:


1. Simplicity is key. In practice, solutions tend to be much simpler than the ones I worked on in academia. Time constraints and the need to quickly deliver impact often outweigh the drive for optimality or sophistication.

2. Real data brings real challenges. While artificial data is a great tool for research, it only gets you so far in practice. Collecting, cleaning, and understanding real-world data is often more challenging than designing the solution itself.

3. The solution is just one piece of the puzzle. IT architecture, training, lifecycle management, roles, documentation—the list of considerations around the model can easily overshadow the model itself.

4. Impact > Optimality. The goal is rarely to achieve a perfect solution. It’s to improve the current system in a tangible, measurable way. Extendibility and theoretical contributions take a backseat to solving the immediate problem.

5. Communication is everything. In academia, we write papers for people who understand our field. In consulting, the audience often has no background in OR. Explaining complex ideas clearly—and convincing others of their value—requires a completely different approach.

6. Tools and technology are rarely up to you. Clients often have established tools and infrastructure. Working within these constraints adds a practical layer that academic projects don’t typically face.

7. Defining the problem can be harder than solving it. Clients often come with symptoms, not fully defined problems. Framing the problem well becomes as important as delivering a solution.

It’s been an eye-opening year, and I’m still learning how to balance these dynamics. Consulting has its own set of complexities—ones that often go beyond the math and algorithms we focus on in academia.

What has your experience been like transitioning between academia and industry?

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