I used to think of myself as a copy-paste engineer.
When I was a portfolio optimiser, a significant part of my job was maintaining Excel workbooks. Dozens of them. Each one connected to the next through formulas that only I fully understood. Every day I'd open them, update them, save a copy with the date, and hope nothing had broken overnight.
The worst moments were before market closing. The pressure is high, decisions need to go in — and Excel decides to crash. It happened more often than I'd like to admit.
I thought at the time that was just how the job worked.
It's still how many jobs work
Walk into most energy companies today and you'll find the same picture. Critical operations — forecasts, scheduling, hedging, optimisation, reporting — running in Excel. It starts simple: one analyst, one workbook, one market. Then the portfolio grows.
Excel doesn't scale gracefully. It breaks in specific, painful ways.
There's the key person problem: the formulas work, but only one person knows why. When they leave, the knowledge leaves with them. There's the migration risk: a corporate IT upgrade changes the Excel version and suddenly half the macros don't run. There's the audit problem: when a regulator asks what position you held on a specific date two years ago, you're doing archaeology through files named model_v3_final_FINAL_march.xlsx.
And there's the closing risk — the one I remember most. When a decision needs to go in and the workbook won't open.
The trap of "we'll fix it later"
The problem with Excel is that it works well enough, for long enough, that replacing it never feels urgent. You patch it. You add a tab. You hire someone to maintain it. The system holds — until it doesn't.
I recently spoke with a manager at a utility building a new B2B portfolio. He needed historical consumption data. It was somewhere in the data lake — but where exactly, nobody knew. IT told him the cleanup project would be ready in next year's roadmap. Under pressure, he ended up doing what everyone does: hiring people to rebuild everything quickly in Python and Excel.
It's not an isolated story. It's what happens when business urgency meets a data infrastructure that was never designed for speed.
What the alternative looks like
What teams actually need is a platform where every formula is centralised and versioned, every change is logged with who made it and when, and any analyst — not just the one who built it — can open it and understand it.
Not because regulators demand it. Because operations depend on it.
The goal isn't to replace the flexibility that made Excel attractive in the first place. It's to preserve that flexibility without the fragility — so that the next time something goes wrong before closing, you're not staring at a frozen spreadsheet.
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