The five worst forecasting mistakes

Your forecasts are inaccurate? Or worse: People think it’s a waste of time?

Then STOP making these 5 forecasting mistakes:

❌ #1 Only forecasting top-down

Accuracy comes from eliminating bias. To get there, prepare both a top-down and a bottom-up forecast. The bottom-up looks at each project individually. The top-down starts with an end result in mind and works backward to arrive at individual business drivers. Combining both types reduces bias because top-downs tend to be aggressive, and bottom-ups are often too risk-averse since buffers are built-in at every layer.

❌ #2 No accountability

If Finance runs the forecast independently, without business leaders feeling accountable to deliver it, it doesn’t add much value. And most likely, accuracy suffers as a result. The best forecasts are fully aligned with the business. For instance, the assumptions going into a revenue forecast should be co-developed with the sales or marketing teams, and the department head needs to be held accountable to deliver it. As a result, you get more than better accuracy: someone will take action when performance is off.

❌ #3 Assumption stacking

The more uncertainty in your business, the fewer assumptions you should include in your forecast. If you add multiple variables on top of each other, their margin of error multiplies.

Additionally, it’s much easier to analyze your business drivers 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 nearly impossible to determine which one was accurate and which wasn’t.

❌ #4 Skipping sensitivity 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.

❌ #5 Showing only point estimates

Sometimes, analysts mistakenly 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 level-up your forecasts:

1️⃣ Remove bias by comparing top-down vs bottom-up

2️⃣ Create accountability by aligning the forecast with the business

3️⃣ Higher uncertainty requires fewer assumptions

4️⃣ Estimate the risk by running a sensitivity analysis

5️⃣Provide ranges instead of point estimates

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