TELEMETRY
vend visit
ef fciency
spoil ag e
reduct ion
cash
lit y
accoun tabi
sold ou t
nt
manageme
How to fnd
profts in
telemetry data
By Ben White, Contributing Editor
There are four important operational
"mineshafts" vendors should look for
in their data that will help them grow
their businesses.
iStockphoto
Companies who use data
for self-improvement have
a tremendous advantage.
O
ver the past decade, our industry has done a tremendous job
building data collection systems to effciently operate and manage thousands of vending machines.
I applaud the hard work and dedication of everyone who has advanced
our industry from the era of paper
tickets to modern-day telemetry
and vending management software.
Companies have employed armies
of installers, managers, drivers
and offce staff to move technology forward. In return for their
efforts, operators have received
virtual mountains of data. Billions
of transactions populate databases
around the country. However,
has this push toward automation
resulted in relevant returns? Does
the collection of all this data really
make for better service, happier
22
Automatic Merchandiser
customers and a healthier bottom
line? What benefts can operators
expect to receive for embracing our
computer driven society?
I, for one, am a frm believer in
the data driven organization. I think
companies who use data for continuous self-improvement have a tremendous advantage over companies that
don't. The old adage, "That which
we measure, we improve" is greatly
assisted by computer collected data.
However — the sheer amount of
data streaming into vending companies can become daunting, confusing and even counterproductive
to customer service and effciency
efforts. Building better operational
systems through the analysis of data
requires teamwork, common goals
and an enthusiasm for success. I
think a company willing to systemati-
VendingMarketWatch.com
April 2013
cally mine its data will fnd not only
proftability, but improved working
conditions as well. I see improvement
emerging from four "mineshafts" of
effciency: cash accountability, sold
out management, spoilage reduction
and vend visit effciency.
Before we begin dragging nuggets
of proftability out of our database,
we must frst confrm our data integrity. Any computer science grad will
agree that there is a primary rule
for working with data: Garbage In
— Garbage Out. Once we know our
input data is trustworthy — let the
data mining begin!
Data integrity begins with staff
Tackling data integrity involves the
entire operating team. Drivers as well
as warehouse and offce staff all have
CONTINUED
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