3 ways Financial Analysts deal with uncertainty in a forecast

forecasting
Written By Christian Wattig

Image by Bernd Dittrich via Unsplash

You can’t treat every forecast the same. More uncertainty means more risk.

Here is how to deal with it:

#1 Avoid assumption stacking

The more uncertainty the fewer assumptions you should include. That’s because if you add multiple variables on top of each other, their margin of error multiplies.

Additionally, it’s much easier to learn the drivers of the business if you isolate the variables. That way, you can compare actuals to forecast and make conclusions that reduce uncertainty in the future.

If you base the forecast on many assumptions it's close to impossible to determine which one was accurate and which wasn’t.

#2 Run what-if analysis

It’s our job to quantify the risk of a forecast. That’s even more important when there is a lot of uncertainty. The easiest way to do that is by changing individual inputs and noting how much impact that has on the forecast.

For example, if a change to the price sensitivity of only 5% impacts the revenue forecast by 25% then that’s a major risk you’ll need to call out.

#3 Show a range

Sometimes, analysts make the mistake to assume ranges make it look like they aren’t confident in their forecast. However, a well-measured range is critical for two reasons:

One, it shows the order of magnitude of uncertainty (i.e. risk) in the forecast. That means, your CFO knows what’s a conservative estimate to communicate to investors.

And two, it enables scenario planning. For example, it allows leaders to plan contingency measures ahead of time if results are at the lower end of the range.

In sum, to manage uncertainty in a model:

1️⃣ Don’t layer many assumptions on top of each other

2️⃣ Estimate the risk by running a sensitivity analysis

3️⃣ Provide ranges instead of point estimates

Christian Wattig
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