6 Ways FP&A Gets Sensitivity Analysis Wrong

Sensitivity analysis should reveal where your model is fragile.
Instead, most FP&A teams use it like a parlor trick — tweaking numbers without learning anything.

Here are six ways sensitivity analysis fails in FP&A:

1. Only Stressing the “Obvious” Drivers

Revenue growth, churn, pricing. Yes, they matter. But so do implementation delays and adoption rates. The overlooked drivers often break the model faster than the obvious ones.

2. Testing One Variable at a Time

Markets never move in isolation. Churn rises while discounts deepen. Hiring slows while demand spikes. If your sensitivity analysis doesn’t combine shocks, you’re modeling fantasy.

3. Using Arbitrary Percentages

“Flex revenue ±10%.” Why 10? Because it’s round? Inputs should reflect history, volatility, and probability — not guesswork.

4. Ignoring Non-Financial Inputs

Regulatory changes, sales productivity, product launch delays. They’re harder to quantify, but ignoring them blinds you to real-world volatility.

5. Treating Output as an Answer

Sensitivity analysis isn’t about finding certainty. It’s about locating fragility. If you treat it like prediction, you’ve missed the point.

6. Never Feeding Results Into Decisions

If the analysis doesn’t alter strategy, it’s wasted. Sensitivity only matters if it shapes choices.

Why This Matters

Bad sensitivity analysis creates noise. Good sensitivity analysis creates foresight. It tells leadership where the model bends, and where it will snap.

At The Schlott Company, we help CFOs transform sensitivity analysis into a strategic weapon. We calibrate inputs with real data, test correlated shocks, and tie results to decision frameworks.

Because the goal isn’t flexing spreadsheets. It’s pressure-testing reality.