My home university has a course that teaches intermediate-level Excel operations, made mandatory to all undergrads. On paper it looks great: you learn how to import and summarize data, create dynamic charts, and solve simple models for things like inventory or investment management. The course has a strong reputation, and many alumni speak highly of it.
But here’s my take: for computer science major waste 64 hours of precious course load to teach skill that is key to non-promotable work which is going to be replaced by AI very soon.
Excel is lightweight and easy to learn, but that ease comes at the cost of robustness and precision. In other words, on the Pareto frontier of tradeoffs for a software tool, Excel compromised precision, control, and scalability for instant simplicity.
There are data manipulation tools that give user more control yet being equally applicable—Python, SQL, etc. Excel is somewhat awkward in between—it’s not as powerful and robust—the time spent on debugging Excel’s automatic formatting or struggling to type overly-long formula in a single cell doesn’t seem to worth it.
And more—let’s talk about Excel jobs. In the real world, these jobs tend to fall into what economists like to call Non-Promotable Work (NPT). Excel is good for organizing data, but when you’re spending hours building complex spreadsheets and reports based on your boss’s whims, what are you really learning? You’re not developing cutting-edge technical skills; you’re just making your boss’s life easier by formatting their data the way they want it. You’re not solving problems; you’re stuck in the weeds, dealing with manual, repetitive tasks that don’t push your career forward.
(Just kidding, but seriously—can mastering Excel actually be a negative utility for career growth?)
Doing Excel jobs makes one gradually become the person who “fixes” the data for everyone else but never actually creates the systems that improve the data pipeline. The fact that we have a whole course dedicated to Excel in 2024 just suggests that the university is still stuck in the mindset that data analysis is best done with a tool designed for small-scale data environments. But let’s be real: this is not the skill set or mindset that gets you promoted in any job environment.
It’s not that Excel is useless, but it’s about time the curriculum caught up. So how about we focus on skills that matter? Instead of pure Excel, at least grant students freedom with choice over other equally versatile tools: swap in Python, SQL, and AI the mandatory courses for today’s technical students. That’s how you build careers, not just spreadsheets.