Home

/

Blog

The Model Was Right. The Deck Was Wrong. Nobody Noticed for Two Weeks.

The exit multiple changed in the model on a Tuesday. Nobody updated the LP deck. Two weeks later the numbers on the slide no longer matched, and nothing was watching.

Humphry Shikunzi

Humphry Shikunzi

August 26, 2026

·

3 min read

A Word budget summary showing a total marketing spend of $84,200 beside an Excel model showing $79,650, with a red arrow linking the two mismatched figures

The model gets updated on a Tuesday. The exit multiple assumption changes. A small adjustment, the kind that happens a dozen times during any live deal. The analyst who made the change updates the spreadsheet, sends it along, and moves on to the next fire.

Nobody updates the LP deck.

Two weeks later, someone's presenting updated fund performance, and the numbers on the slide don't match the numbers in the model everyone else is working from. Nobody did anything wrong, exactly. The spreadsheet and the deck were built by different people, updated on different timelines, and nothing was watching to make sure they still agreed with each other. That's not a competence problem. It's a structural one.

This happens more than anyone admits

Ask around any PE fund or finance team and you'll hear a version of this story, not usually framed as a crisis, more as a mildly embarrassing thing that gets fixed quietly before an LP notices. But the fact that it's common enough to have a familiar shape should be the actual red flag. If a mismatch like this can happen quietly and go unnoticed for two weeks, it can also happen quietly and go unnoticed until it matters a lot more.

The tools most finance teams use for AI assistance don't help here, because they're built to work on one file at a time. Ask an AI tool to review the deck, and it reviews the deck. It has no idea what the model says, because it's not looking at the model. Ask it to check the model, and it checks the model in isolation. Neither one is positioned to notice that the two documents used to agree and now don't.

A Word budget summary showing a total marketing spend of $84,200 beside an Excel model showing $79,650, with a red arrow linking the two mismatched figures
Two documents, two different numbers, and nothing watching for the mismatch.

What actually needs to happen

The fix isn't “be more careful.” Every team already believes they're careful, right up until the moment they're not. The fix is having something that's actually watching every document in the workspace at once, the way a meticulous, slightly paranoid VP would if they had time to re-check every file against every other file before anything went out.

That's what cross-document reasoning is for. Overten holds the model, the deck and any supporting memos in the same workspace and checks them against each other, not as a one-time audit, but continuously, as things change. When the exit multiple changes in the model, the mismatch with the deck gets flagged before it becomes a two-week-old surprise.

Why this matters more in finance than almost anywhere else

In most kinds of work, an inconsistency between two documents is embarrassing. In finance, it's a credibility problem with LPs, with auditors, with your own investment committee. The margin for “the deck said one thing and the model said another” is close to zero, and yet the process most teams rely on to catch that is still “someone happens to notice.”

That's not a process. That's luck. And luck runs out eventually, usually in front of the people you least want it to.

See Overten AI in action

See how the Overten AI Workspace Agent helps your team cut the document busywork, catch conflicts early, and free up leaders for the decisions that actually matter.

Humphry Shikunzi

Humphry Shikunzi

Co-Founder & Data Science Lead

Overten AI is an AI document intelligence workspace that reads, cross-references, and reasons across every file in a project, so teams catch conflicts, answer multi-document questions, and generate documents in minutes.

Back to all articles