The boring problem I fixed by turning a guess into a number

Every AI pitch eventually hits the same question: “okay, but what would this actually save us?”

And every answer I had heard before building my own tool was a guess. A confident-sounding guess, but a guess. Nobody had real numbers, just a gut feeling that automation “should” pay off eventually.

What I built instead of a gut feeling

I built a self-serve ROI calculator, part of the wider AI Transition Framework. Feed it a handful of inputs, hours spent on a task, how many people do it, what they are paid, how often it happens, and it spits out a payback period, a Year-1 net return, and hours freed annually. If a client does not have their own numbers yet, industry benchmarks are pre-loaded as defaults, so even a business with zero data of its own walks away with a real figure instead of a vibe.

How I actually use it

It is not something I hand a client and walk away from. I fill it out with them, in the room or on the call, because the inputs only mean something if we agree on them together. This is the information I was most interested in whenever I was on the other side of the table, long before I was the one building the tool: a real number I could take to my own leadership, before anyone had even mentioned price.

Why the spreadsheet matters more than the technology

It is a spreadsheet. Nothing clever about the technology behind it. What is clever is what it turns “we should probably do something with AI” into: an actual number someone can take to their own leadership team, before I have even had a pricing conversation with them. Most of the time, the boring fix is not a bigger model. It is just better math, done once, reused every time.

If you are staring at a process you are fairly sure is wasting money but have never put an actual number on it, that is exactly the conversation the calculator is built for. You can find the details on the contact section of this site.