Why I went back to school: wanting to say in data what I used to say by gut feeling

“When can this ship?”

It’s the question I get asked most as a production planner. It’s also the question I’ve always answered with the least confidence.

“Based on past performance, it usually takes about this long, so let’s add three or four more days to be safe.” Not technically wrong. But if someone asks, “where did those three or four days come from?” — honestly, I didn’t have an answer. It was gut feeling. The kind that builds up over years on the job.

Data was piling up, but I had no eyes to read it

Anyone working with SAP and MES is, in a way, closer to data than almost anyone else. Production orders, inventory movements, sales performance — it all lands in the system every single day. The problem was that I could pull the data out just fine, but everything after that was still gut feeling.

Setting a delivery date, reading order patterns, looking at production volume trends, watching inventory build up and draw down, tracking sales trends — I’d plot a chart and say things like “this picked up recently” or “it’s always like this in this season,” but I had no real way to tell whether that was a meaningful shift or just noise inside the usual back-and-forth.

For delivery dates specifically, you need to also look at how erratic past lead times have been before you can say, with any grounding, “build in this much buffer and you’ll make it most of the time.” The same goes for seasonality in orders or sales, trends in production volume, priority among inventory items. I’d heard of all of this somewhere before, but never actually done it myself. I was looking at data every day, and still had no eyes for reading it.

Once reliable data started to build up

This itch became clear once the SAP stabilization and enhancement project wrapped up. Once the implementation was done and the system settled in, data I could actually trust started to accumulate. Production, inventory, sales — no longer someone’s memory or a spreadsheet note, but numbers sitting inside the system.

That naturally led to the next question: was I actually using this data properly? I could plot it into a nice-looking chart, sure, but pulling meaning out of it was still gut feeling. I wanted to handle that with expertise instead of instinct, if I could. That was the real trigger behind deciding to transfer schools.

There weren’t many options

At first, I wondered whether I even needed to study formally. A book, some employer-sponsored online courses, or picking up know-how secondhand from colleagues who’d been through it already — wouldn’t that be enough?

It wasn’t. Fragments of knowledge kept piling up, but without knowing how they connected to each other, I couldn’t actually apply any of it to my own data. I eventually concluded I needed to follow someone else’s curriculum, in order, from the start.

As a working adult and the head of a household, I didn’t really have many options. Quitting my job to go to school wasn’t on the table, and a program that required showing up somewhere at a fixed time every day wasn’t realistic either. So I chose the Statistics and Data Science program at the Korea National Open University — a school I could attend while working. Less a grand decision, more the most realistic choice available given my situation.

Honestly, when I started, there was a part of me wondering if this was just wasted energy. Was it really wise to pile studying on top of an already packed daily routine? I had to keep reminding myself of why I started, over and over, so I wouldn’t lose that first resolve.

Couldn’t follow the lectures, but

That’s how I enrolled at the Open University, and the first semester began.

I took six courses that first semester: Introduction to Statistics, Data Visualization, Python Data Processing, Data Processing and Utilization, Excel Data Analysis, and Understanding Distance Education.

Honestly, there were a lot of moments during the lectures where I had no idea what was being said. I’d feel like I understood it while watching, but the moment I opened the assignment, my mind would go blank. I got through it somehow anyway. Whenever I hit a wall, I’d ask an AI over and over, and sometimes find answers in my program’s online community. It wasn’t studying alone and struggling in silence — it was a semester spent constantly asking questions and running into walls.

What surprised me was that working through it by hand made things click that the lectures alone never did. I didn’t understand it and then do the assignment — I understood it by doing the assignment. Those late nights buried in homework and exam prep were, for someone just starting over, no small adventure.

Picking up a pen again after a long time

I picked up a pen again after a long time, tapped away on an engineering calculator, and wrote things down on paper by hand. In an era where everything happens on a screen, there was something quietly satisfying about that analog feeling of writing by hand and understanding with your head. Along with the small sense of accomplishment that comes with grasping something new.

There was an unexpected change too. Watching me sit down at a desk to study, my kid started sitting down to study alongside me. Seeing that was, on its own, enough reason to stay seated a little longer.

I used to burn a lot of idle time scrolling short-form videos or leaving the TV on in the background. Since starting school, it’s like my hobby has quietly become studying. The steady stream of assignments and looming exams still keeps me on edge, but even that tension doesn’t feel bad.

The results turned out fine too, thankfully. I didn’t push for more than I could handle, just did what I could, and for a first semester, I was satisfied with it. That became a small source of momentum to keep going into the next one.

What I plan to write in this category going forward

In this category, I plan to cover roughly three things: statistical concepts from my coursework, explained at a beginner’s level; SAP and MES data I used to look at, reread through a statistical lens; and a record of the courses and study methods each semester.

I’m only writing this first post after finishing my first semester, but I’ll try to steadily organize what I’m learning along the way. Maybe it’ll be a small reference for someone else, or maybe it’ll just be my own record and a marker of growth.

Things I used to say by gut feeling — I hope I can gradually start saying them in data instead.

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