Automated forecasting software and managers who are involved in day-to-day activities each have their strengths and weaknesses. A combination of the methods is likely to ensure more accurate forecasts.“In academics, we often say that managers don't really have anything to say, we need to rely on quantitative methods. My experience is that that isn't really the case. Experienced managers who know their industry have a lot of insight. They come to conferences, they hear the buzz, they know what's happening. So, we really can't just rely on automated packages”, says Sanders, professor and Iacocca Chair at Lehigh University.
“Quantitative methods are consistent. They are objective. They always give you the same results. They can process tremendous amounts of information and data. We as humans can't do that, but they're only as good as that data that they are based on.”
“A manager is biased. We're all biased; we've documented that. We can be tired on Monday morning or Friday afternoon, so our forecasting won't be the same. Our ability to consider a lot of factors isn't very strong. However, unlike an automated forecasting model, we are privy to a lot of insight into the industry that were in, so we need to find a way to harness the strength of both methods. That's really the way forward in terms of forecasting.”