Technology, Managers
Team for Much More
Accurate Forecasting
Editor-in-Chief
Russell Goodman
A conversation with Nada R. Sanders, professor and Iacocca Chair at
Lehigh University.
Automated forecasting software and managers
who are involved in day-to-day activities each
have their strengths and weaknesses. Extensive
research, analysis and consulting leads Sanders,
business professor at Lehigh University, to conclude that a combination of technology and people is likely to ensure more accurate forecasts. The
following interview took place in September, at the
annual conference of the Council of Supply Chain
Management Professionals.
Q: Why is forecasting so much more difficult than
formerly?
Sanders: I’ve been doing forecasting for well
over 20 years, I work with Nike and others, and I
find it has become so much more challenging not
just over the last 20 or 10 or even five years, but
even just in the last couple of years.
kets, we’re forecasting trajectories of those markets, the lifecycles of those markets. We’re forecasting competition, we’re forecasting whether
markets will emerge and collapse. There’s so
much more to forecast and so many more factors
that come into play. It’s much more difficult than
it’s every been.
Q: Quite a number of automated forecasting
packages purport to optimize the process. How
effective are they?
Sanders: Most of the forecasting software
packages are either stand-alone or tied to an ERP
system of some sort. They all work off of quantitative forecasting models, and they’re really the
same kind of models we’ve seen and used for 20
to 30 years. We’re technically still using the same
kind of models albeit they are now part of a soft-
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.
First of all, everybody is global today. Our markets are global, our customers are global, our suppliers are global. So our span of control has
dramatically increased. We also have very short
product lifecycles. We have high expectations of
very quick response times. A disruption anywhere
across the globe affects us immediately, which did
not happen even five years ago. So forecasting is
much more challenging.
And you have to think also, we’re not just
forecasting demand. We’re forecasting new mar-
ware package, and even though we live in a very
different environment that has so much change.
