I had a US$100 million decision on my desk and a forecast full of numbers. This is how I finally saw the business behind them.
An anonymised case study. Figures are adjusted, and projections are not guarantees.
Should we build a plant that recycles old electric-vehicle batteries? Our technology partner had built a solid financial model. My job was to understand it well enough to explain it to the board in plain words.
The numbers looked good. But a spreadsheet shows the answers, not the plant behind them.
I understood the answer. I just couldn’t show anyone how we got there.
Each box is something real: a machine, a product, a cost, a team. Lines show what flows from one to the next, all the way into the accounts. For the first time, everyone was looking at the same picture.
Missing inputs are normal in any model. On the map, they just stand out. For this case study we filled them in: blue numbers come from the business case, amber ones are our own assumptions.
Follow one year of batteries through the plant. At each step you can see what goes in, what comes out, and what it costs.
Used battery modules arrive at the plant.
Casings come off. Aluminium and copper are sold as scrap.
54% of each module becomes black mass, the valuable powder.
The chemical plant needs more than we make, so we buy the gap.
Black mass becomes nickel, lithium and cobalt salts.
Nickel and lithium salts bring in most of the money.
Cost share = part of yearly running costs. Labour, maintenance and overhead (about 19%) are shared across all steps. t = tonnes per year.
Black mass is the valuable powder the plant makes. I started with tonnes on the plant floor and worked my way up to dollars.
Move the slider and watch the cost change. It’s a “what if”, not a forecast.
| My question | Spreadsheet on its own | Spreadsheet + BizPal map |
|---|---|---|
| Where does revenue come from? | One total and a pie chart | Each product traced back to the plant step that makes it |
| Are the assumptions realistic? | Buried in spreadsheet cells | Shown on the box they belong to, in plain units |
| What is still missing? | Open inputs are hard to spot | Empty boxes stand out and become a team checklist |
| Can I check the numbers myself? | Walk through it with the modeller | Trace key figures step by step and test the assumptions |
| What if something changes? | Rerun and recheck the model | Change an input and see the linked outputs update |
Now finance, operations and our partner look at the same picture. I don’t just read the forecast. I understand it, and I can explain it.