8 Fundamentals of Forecasting in Business

‘There is no reason anyone would want a computer in their home.’ — Ken Olson, president, chairman and founder of Digital Equipment Corp., 1977

‘640KB ought to be enough for anyone.’ — Bill Gates, 1981

‘I think there is a world market for about five computers.’ — Thomas Watson, Chairman of IBM, 1958

Sometimes forecasting the future is fraught with difficulties. Even those entrepreneurs who we place on a pedestal don’t always have the business foresight we assign to them. What seems certain can turn out to be false and what seems highly unlikely can become every day as the quotes above demonstrate.

Rather than go into a deep discussion about forecasting and modelling techniques, I want to remind you about some core principles.

These 8 fundamentals of forecasting in business can at times be easily forgotten, to the detriment of the quality and accuracy of your financial models.

1. Your forecast will always be wrong

Sometimes we forget this obvious truth. A forecast is just that – an estimate, a predicted future result. The question you should be asking is “how wrong is our forecast?”

2. Simple forecast methodologies trump complex ones

There is danger in complexity. Complicated forecast methods often hide key assumptions built into the model.

When key assumptions are obscured it can lead to unexpected and hard to trace failures.

On the other hand, simple forecast methods are easy to understand, analyse and work out why it went wrong.

3. A correct forecast (or at least a highly accurate one) does not prove your forecast method is correct

It could have been chance. When you accurately project financial and other key performance indicators, it’s still important to check your forecast methods.

If you only question your methods when there is a large variance in the data, you’ll miss all those times your forecast was just lucky – potentially hiding a multitude of sins.

4. If you don’t use the data regularly, trust it less when forecasting

The quality of your data is proportional to how often you use it. When information is not regularly used, errors often remain undetected (and errors are common in financial models).

Regular use of data helps identify mistakes and smooths out inconsistencies over time. You’re usually better off using solid data and adding further assumptions than to work with rarely used data.

5. All trends will eventually end (that’s why they’re called trends)

Many factors will affect the pattern you’re trying to forecast. It doesn’t matter how accurately you predict the trend, in the future the variables will change and the forecast will be wrong.

6. It’s hard to eliminate bias, so most forecasts are biased

Let’s not forget we’re talking about predictions here.

When you have to make a range of assumptions (which factors to include, how strongly to weight them etc.), it’s likely that you will be adding some bias to the forecast.

7. Large numbers are easier to forecast than small ones

It’s usually better to forecast the bigger number and work back the calculation to determine the component parts, than to forecast the component parts and then add them up to determine the bigger number.

8. Technology is not the solution to better forecasting

Robust forecasting comes from sound logic in your methodology.

First, create an appropriate strategy and then use technology to make it more successful and efficient.

Technology is not the answer; it’s the tool to make it better.

Remember these core principles and you’ll be building your forecasts on solid foundations. And try not to make the same mistake as Ken Olson – being that wrong never makes you look good.

Jeff Robson is a guest blogger and CEO and principal business analyst at Access Analytic, a leading provider of business analyst tools and services, specialising in Excel financial modelling, management reporting, training and financial model auditing.

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