Right until early 2007, economists and analysts across the world believed that the global economy was inherently stable, healthy and on a growth path. The financial crisis soon unravelled – subprime mortgages collapsed in the summer of 2007, world stock markets sharply fell in January of 2008, and crude oil prices peaked to a record high of $145 later that year. Just a handful of analysts predicted the crisis; the others got their “market forecasts” grossly wrong.

For businesses of all kinds, what matters is the future. As a result, competitive and market intelligence analysts are routinely tasked with forecasting market growth. Very often, business plans are built on such forecasts. But if you ask the users of these estimates, there is more than a healthy skepticism. After all, who can predict the future? Arun Jethmalani tells us there is one common failing that he’s seen with most of the forecasts – regardless of the models or methods used for market sizing and forecasting. And that arises from the simple straight-line extrapolation of the very recent past.

Trying to be prepared for the future invariably assumes that we must have some inkling of what’s in store. Apart from detailed forecasting exercises, it’s important to read and understand early warning signals. In her article, Varsha Chitale explains how even the weakest of signals can help analysts anticipate the future.

Interestingly, many believe that big data is the way out. Powerful algorithms will now crunch their way through masses of data and predict how markets and prices might evolve – helping businesses make better marketing decisions, acquire more customers, improve profitability and beat the pants off competition. Arun tells us whether this is real or plain hype.

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