Why critical formulation and capacity models still live in Excel, and how to govern them

Formulation sheets and capacity models stay in Excel for a simple reason: they change faster than any system built to replace them can keep up. Governing them where they live beats trying to migrate them.

The model is the product

A formulation sheet in a chemicals plant, or a capacity model in network planning, isn’t a report — it’s the working tool an engineer uses every day to make a decision. It changes when a raw material changes, when a line is reconfigured, when a new constraint shows up. A spreadsheet lets the person closest to the problem adjust the model the same day. A request to change a dedicated system usually goes through a queue.

That’s why these models resist migration projects, even well-funded ones. The team isn’t being stubborn — the spreadsheet is still the fastest tool for the job.

What goes wrong without governance

The same flexibility that makes a spreadsheet useful also makes it fragile. A dosage field with no range check can accept a value ten times too high. A formula referenced by three other sheets can be overwritten by someone who doesn’t know what depends on it. And because the file is usually shared by email or a shared drive, there’s rarely a single record of who changed what, or when — until a batch fails and someone needs to find out why.

Governing the model without rebuilding it

The fix isn’t a new system. It’s validation, a record, and a measurement, applied to the spreadsheet that already exists:

• Validation at entry. Define the valid range for each critical field — a dosage, a tolerance, a capacity limit — once, and block anything outside it before it’s saved.
• A full audit trail. Every change is recorded automatically: who, what, when. No separate logging step for the engineer to remember.
• A data quality score. The Insy Sigma score tracks how stable each field is over time, so a team can see which parts of the model are becoming less reliable before that shows up in a failed batch.

See how this applies to Quality & Laboratory and Engineering & Telecom teams specifically, or read about the Lean Six Sigma cycle behind how IT-TIDY keeps improving a field’s reliability over time.