It might not be obvious at first glance, but weather forecasting and business forecasting have a lot in common.
Let’s think about weather forecasting first.
Meteorologists forecast a lot of different weather events over different timeframes and each has its own degree of accuracy and uses.
Sometimes weather forecasts can be incredibly precise and mathematical. We can pinpoint down to the minute – or even second – what time the sun will rise tomorrow.
We also know what time high tide will be, although wind and wave height might move the high tide mark by a centimetre or two.
Tomorrow’s maximum temperature might be forecast at 25 degrees. It might turn out to be 23 or 27, but that’s still pretty useful for someone to know they needed wear an overcoat.
The likelihood of rain is usually stated as a percentage likelihood, which means it is neither right or wrong. But even these forecasts are useful. You wouldn’t plan a day at the beach if there was an 80% chance of rain.
Different forecasts are used in different ways
The closer to the present time the forecast it is, the more accurate it is and this is useful in different circumstances. It’s crucial for a Formula One pit team to know it’s highly likely to rain in the next 15 minutes, so they can get the car into the pit and change tyres.
A longer-range forecast of, say, a hot and dry summer will be useful for tourism and bushfire planning.
A two or three year rainfall forecast won’t be able to tell you the chance of rain on a Tuesday three years from now, but it can tell farmers the likelihood of drought and let them adjust stock and feed levels for the future.
Business forecasts such as demand forecasts work in a similar way, where the timeframe and accuracy of the forecasts dovetail neatly with the way they are used.
For instance, an airport might be able to see by the number of people booked to fly in the next 90 minutes and the number yet to check in how many will need to pass through security in the next half hour to get to their flights. They can quickly move staff from other parts of the airport onto security to help manage a predicted rush.
They won’t be as accurate with a forecast on how many people will need to pass through security between 8:15 and 8:45 on a Thursday in September in three years’ time. The airport may however have an strong weekly or monthly forecast for traffic in the next three years and so could make the long-term decision regarding investment in an additional security lane if traffic is increasing.
Why do we need a forecast?
A sailor doesn’t head out to sea without first checking the wind and tide forecast. A farmer doesn’t sow a field without first checking the long-term rain and temperature forecast. And a mountaineer doesn’t leave base camp before first checking for storm warnings.
Although everyone recognises the forecast may not be correct every time, it provides an invaluable (sometimes life saving) prediction of the future.
Business forecasts work in the same way.
Forecasts to guide strategic decisions
Longer-term forecasts lack pinpoint accuracy but are extremely useful for making strategic and capital investment decisions.
Forecasting is also useful for businesses with high-value, low-volume products, such as one which takes on major projects or offers subscriptions. These sorts of companies can use the business equivalent of the rainfall forecast.
It can allocate a percentage of success to its pipeline of potential contracts to build and overall forecast. For instance, it might have a 30% chance of winning a contract worth $1 million while another worth $2 million has a 60% chance of success.
Businesses could use these numbers as a starting point for scenario analysts and come up with three or four most likely scenarios and start planning how it would manage each one.
Just as we know how much reliance to put on different types of weather forecasts, we should also consider the timeframe and accuracy of business forecasts when we use them.