Forecasting is big business. Pundits forecast the outcome of sporting events, economists forecast GDP growth rates, meteorologists forecast the weather, analysts forecast stock prices and most relevant of all, CFOs forecast revneue and earnings growth.
In the Wall Street Journal, (SPACS Fall Short of Lofty Goals , February 26) it was reported that nearly half of all startups with annual revenues of less than $10 million that went public via a Special Purpose Acqusition Corporation or SPAC in 2021 have failed, or are expected to fail, to meet the revenue and earnings growth targets they provided to investors. Many of these aren't just small forecasting errors, we are talking about huge misses. Electric bus and van maker, Arrival, predicted in March 2021 that it would achieve revenues of $14 billion in three years. Eight months later it withdrew all its long term forecasts.
No one doubts that forecasting is difficult. After two years of Covid, in the midst of the war in Ukraine, with rampant inflation and surging volaility, forecasting is never going to be easy. However, we rely on forecasts to make many decisions from whether to carry an umbralla to where to invest our retirement savings. So how can we evaluate forecasts with confidence?
Here are five basic rules to apply when digesting a forecast:
What is the motivation of the forecaster? Is it to be honest or optimistic? Company executives frequently forecast what they would like the future to look like rather than what it they actually think it will look like. Investors won't invest and stock prices won't rise if maangement are not confidently optmistic about the future. Place more weight on forecasters who have no vested interest in the outcome.
Does the forecast include a comment on the level of confidence the forecaster has in the outcome? Is their confidence level supported by facts, planned actions, and credible assumptions?
Does the forecast clearly state the assumptions upon which it it based?
Does the forecast communicate a range of likely outcomes together with the factors that will influence those outcomes?
Is the forecast an outlier where multiple forecasts exist? This does not mean it is necessarily wrong (the herd is not always right) but it should cause pause to consider the rationale behind a divergent forecast.
Forecasts can be a valauble tool that guide planning, investing and execution. However, more valauble than slavish adhrence to a forecast is to be observant enough to a) identify when a forecast is no longer valid and b) agile enough to adapt your behaviour and actions.
The increased availability of data and use of more advanced analytic and data science techniques does not guarantee universally better outcomes. The future is by defintion unknown so take care when relying on a forecast to make decisions.