problematic to be exclusively relying on the
quantitative-model forecasting software.
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
Q: Do you have an example you can
Sanders: In fact, Nike, just a few years
ago, in a highly publicized case—they had
They are objective. They always give you
the same results. They can process tremen-
dous 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.
purchased an i2 software package, highly
promoted, but what happened is that after
they used the package, six months later
they were in court. There was too much
slow-moving inventory, not enough of the
fast inventory that was needed. When they
looked back, what they found is that managers were exclusively relying on the quantitative automated forecasting software and
not enough on managers who actually
knew about their products.
Q: So are you saying we should rely on
managerial expertise instead?
Sanders: Here is the tricky thing. In
academics, we often say that managers
rely on automated packages. We need to
find a way to incorporate what managers
know, what’s the latest they’ve heard. A
quantitative model or software package
can’t incorporate the very latest, what you
as a manager have just found out in the last
three minutes when you were on the
phone with your vendor.
Q: So it’s both technology and people that
make for success?
Sanders: Absolutely. Keep in mind
both approaches have their strengths and
weaknesses. The trick is to combine them
in some kind of way.
Quantitative methods are consistent.
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 we’re 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.
To read this article online or to view the
video interview, visit SupplyChainBrain.com.