7 Tactics to Get Non-Finance Teams to Actually Use Your Model

Let’s start with the harsh truth: most non-finance teams hate your spreadsheet.

Not because the math is wrong. Not because they don’t care about performance. They hate it because it feels like a Rubik’s Cube built by someone who thinks in SQL joins and nested IF statements. To them, your model is less of a tool and more of a trap—one where changing a single input might detonate the entire file.

I’ve been on both sides of this. I’ve built models I thought were bulletproof, only to watch a sales manager stare at it like it was written in hieroglyphics. I’ve also been the operator, annoyed that I had to email Finance to get a basic revenue forecast tweak.

Eventually, I figured it out: it’s not about the numbers. It’s about the relationship between the numbers and the people using them. If you want your model to get used, you don’t need more logic. You need buy-in.

Here are seven tactics I’ve learned to get non-finance teams to actually use your model—and trust it enough to make decisions.

1. Build with Them, Not for Them

Most finance teams operate like architects. We interview stakeholders, retreat into our spreadsheets, and return with a “final build.”

The problem? You built what they said, not what they actually need.

I’ve started pulling stakeholders into the build process early. I open up a blank tab and ask questions like:

• What are the 3-5 metrics you look at every week?
• What decisions are hardest to make in your role?
• What have you built for yourself in Google Sheets that works?

Then I reverse-engineer the logic around their habits, not mine. Because if the tool doesn’t feel familiar, it won’t get used.

And here’s the kicker: one of the best adoption stories I’ve seen came from a model we co-built in a live working session. We didn’t even call it a “model”—we called it a “decision map.” It’s been in weekly use for over a year.

2. Hide the Complexity (But Keep It Accessible)

Good models are like good restaurants: the kitchen is complex, but the menu is simple.

Finance folks are proud of their logic. And they should be. But if your operating team has to click through six tabs and unhide columns just to see next quarter’s budget, you’ve already lost.

The fix:

• Put key assumptions and inputs on a single control tab
• Use drop-downs and named ranges to guide behavior
• Lock formulas, not data entry

Let people play with the model without the fear of breaking it. Confidence leads to curiosity, and curiosity leads to use.

3. Make the Outputs Speak Their Language

A revenue leader doesn’t care about gross margin by segment. They care about bookings, quota coverage, and CAC payback.

You need to translate your outputs to match their world:

• Sales wants pipeline vs. target
• Marketing wants ROI by channel
• Product wants cost per feature or user adoption curves

Here’s a simple alignment table I’ve used before:

Speak their language, and suddenly, your model isn’t “finance stuff.” It’s “our stuff.”

4. Give Them a Reason to Log Back In

The biggest lie in finance is that “accuracy drives adoption.”

Adoption is driven by utility. Your model should answer a real question they’re asking on a regular basis.

For example:

• A sales team is trying to optimize territory coverage. Can your model help simulate ramp, coverage, and bookings by rep?
• Marketing wants to know what happens if they shift 20% of spend to a different channel. Can the model show that in real time?

One client I worked with started referencing our FP&A tool in weekly team meetings—not because we asked them to, but because they couldn’t make decisions without it. That’s the goal.

The more your model mirrors their daily decisions, the more likely they are to return. If it doesn’t save them time or unlock insight, it won’t matter how elegant the formulas are.

5. Turn the Model Into a Narrative

Most operators don’t want spreadsheets. They want stories. Not fiction—but a coherent narrative about how decisions today affect outcomes tomorrow.

When I roll out a model, I present it like this:

• Here’s what’s happening now
• Here’s what the model says happens next (if nothing changes)
• Here’s what we could change—and what happens if we do

In one case, a single forecast scenario helped a product team lobby for a hiring freeze—and win. Why? Because we didn’t just hand them data; we handed them a narrative.

If your model doesn’t lead to a “so what,” you’re not done yet.

And by the way: slides aren’t the enemy. I use one-pagers with outputs pulled straight from the model to drive cross-functional discussions. This builds trust without overloading people with cells and tabs.

6. Train Like It’s a Product Launch

If you rolled out a new CRM or billing platform, you’d do onboarding. You’d hold office hours. You’d create documentation.

Why don’t we treat our models the same way?

When I roll out a model for a non-finance team, I:

• Host a 30-minute training (recorded)
• Create a 1-pager on how to use it and what decisions it supports
• Set up a Slack channel or email alias for questions

One time, I added a QR code to a shared model tab that linked to a Loom video walkthrough. It took five minutes to make and probably saved fifty hours of email clarification.

If you want adoption, you have to reduce friction. The first experience with your model should feel like a win, not a homework assignment.

7. Build a Feedback Loop Into the Model

The best models evolve. But most of us treat them like they’re finished once the logic ties out.

Here’s what I do:

• Add a comment box or feedback form directly into the model
• Check in monthly with power users
• Track how people are using it—and what they still need

And here’s the unexpected bonus: when people know their input matters, they start thinking with you, not just about you. That changes the culture of finance from gatekeeper to partner.

Your model isn’t a deliverable. It’s a living tool. And the more your stakeholders shape it, the more they’ll trust it.

If No One Uses It, It Doesn’t Matter

Here’s the uncomfortable truth: you can build the perfect model, but if no one uses it, it failed.

And not because you’re bad at modeling. But because finance doesn’t operate in a vacuum. We’re in the business of influencing decisions. And influence doesn’t come from accuracy—it comes from relevance.

I wrote this because I’ve been that analyst who spent 40 hours building a forecast no one opened. I’ve also been the operator who finally saw their reality reflected in the numbers—and made a better call because of it.

If you found this useful, please share it with someone who’s tired of building beautiful models that collect dust. I put in the time because I believe finance is most powerful when it’s collaborative.

And here’s something unconventional to chew on: What if the best model isn’t the smartest one, but the most used one?

Are you optimizing for precision—or for impact?