While scores of analysts and strategists have been offering their 2011 forecasts about how much the S&P 500 will gain or lose, how much gross domestic product will grow or shrink, and a myriad of other financial figures, The Wall Street Journal’s Jason Zweig offers a prediction of his own: Most of those forecasts, he says, will miss the mark, if history is any guide.

“Why do people with years of experience, massive expertise and mountains of data at their disposal so often get the future wrong?” Zweig asks in a recent column. “First and foremost, the future is the realm of surprises; no one, no matter how expert, can reliably foresee what will happen and how people will react to it. As the economist Friedrich von Hayek said … when he won the 1974 Nobel prize in economics, ‘in the study of such complex phenomena as the market, which depend on the actions of many individuals, all the circumstances which will determine the outcome of a process … will hardly ever be fully known or measurable.'”

Zweig says many forecasters have solid forecasting models, but subvert those models by straying from them. “Like cooks going wrong by tinkering with recipes that already work, forecasters defeat themselves with too much fine-tuning,” he says. “One study found that an unvarying computer model of stock analysts’ estimates of future returns was more accurate than the analysts themselves 72% of the time.”

Zweig also notes that the Federal Reserve Bank of Philadelphia runs the Survey of Professional Forecasters, which keeps an extensive database of forecasts from dozens of experts on financial and economic variables. He says the database shows that forecasters tend to be more accurate over a quarter or two than they are over longer periods.

The bottom line, Zweig says, is that you shouldn’t take “expert” forecasts as gospel. But he says that you can use them to your benefit in several ways. For example, he says one researcher has found that by averaging together a diverse group of forecasts, you can cut forecasting error by nearly 60% compared to using one individual’s forecast.