Instore - July 2018 - 27

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a robot, he said. It could be an automated
tomato chopper or pasta maker, or a machine
that flips burgers on the grill -always at the
exact moment the meat's internal temperature says they should be flipped.

Accurate forecasting:
a marriage of manager
and machine
Too many open tables. Not enough tables.
Long lines, and the grumbling customers
stuck in them. Not enough help in the kitchen.
Every foodservice operator has been there,
Mary Hamill, vice president of sales for
HotSchedules' Solution Center, told NRA '18
employees in a presentation on forecasting.
"There are a lot of reasons" for those and myriad
other problems, Hamill said. "But I can guarantee you one of them is poor forecasting."
The title of Hamill's talk was "Precision
Forecasting: Partnering Manager and Machine
to More Accurately Predict Performance," but

even an expert like her admitted that "precision" can be hard to attain when it comes
to accurately predicting when and why
customers show up, and whether foodservice
operations will have enough staff on hand
when they do.

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This, despite the fact that industries spend
billions on forecasting, Hamill said. "I wish
there was a silver bullet, but there really isn't.
Even with all the technologies they have
access to, restaurants are still trying to get
good forecasts."
The instability of today's labor market is a big
reason why, Hamill said. "Turnover is super
high, and new managers come in who don't
know the business." Having good managers is
crucial to having accurate forecasts, she said.
The "machine" part of the forecast is good
at generating algorithms that model trends,
seasonality and other factors that make business ebb and flow, Hamill said.
It's the category forecasters call "events" -
sporting events, other activities, weather and
anything else happening locally at a given
time that can affect traffic -that require the
human touch, Hamill said. "This is where your
manager really comes into play, predicting
the outcomes for all the events that are
happening. No one is going to know about
them but your manager. It's something a
machine isn't able to do."

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A machine may get the forecast within 1 or 2
percent of "precision" six days of the week,
Hamill said. But if you're off by 49 percent on
Day 7, she says, it didn't do its job.

Mary Hamill, vice president of sales for
HotSchedules' Solution Center, led a
presentation on precision forecasting.

All that said, too many foodservice operators are still far too likely to rely on human
over machine judgment, Hamill said. "Today,
companies rely a lot more on managers than
machines, even though nine times out of
ten, the machine is more accurate," she said.
"Machines need to do the heavy lifting, with
managers adding in the events. Forecasts
are most successful when they're working
together."

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Table of Contents for the Digital Edition of Instore - July 2018
