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Wrapping Your Arms Around Big Retail Data
By Derek Rodner
Vice President, Product Strategy
Agilence
 In 2012, the federal government announced $200 million
in research for Big Data computing. Why? Each and every
day an estimated 2.5 quintillion (that is 17 zeroes
after 2.5) bytes of data are created, and nearly 90
percent of the world’s data has been created in the past
two years, according to IBM. In the four years since the
term Big Data was originally adopted within the IT
community, the number of data sources has exploded, now
including smart phones, social media posts, web
interactions and much more. As a result, experts predict
that by 2015, the global market for Big Data technology
and services will swell to $16.9-billion, from just
$3.2-billion in 2010. So what does that mean for retail?
A lot!
Understanding Retail
Big Data
Within the next two years, 30 percent of retailers will
run out of storage capacity, according to The Edgell
Knowledge Networks, and while nearly 80 percent are
aware of the Retail Big Data concept, less than half
understand the implications it has on their business.
One immediate implication is clear, if retailers
continue to ignore this issue they will be overrun by
it.
Beyond the amount of data, the types and sources of the
data are key to understanding and managing this growing
stream of information. There are two types of data,
structured and unstructured. Structured data is
typically numbers and letters laid out in a consistent
format that is readable and searchable by a computer or
person. In retail, this data can come from the POS,
alarms and access control, RFID and EAS, returns
management, customer loyalty programs and much more.
Unstructured data can be much larger, and can spawn an
entirely new category of structured data. The primary
form of unstructured retail data is video. But don’t be
fooled, that single source is a huge data contributor.
To provide some context, storing 30 days of footage from
a high definition (HD) camera, running at 15 frames per
second, requires nearly 1TB of space. And that’s just
one camera!
With that being said, the Retail Big Data concept
becomes a bit clearer, but it still lacks a formalized
definition. Not anymore.
Retail Big Data (n.) – The collection of large
amounts of (structured and unstructured) data from
multiple, disparate, and often unrelated systems into a
single repository to enable retailers to more
efficiently and effectively understand their business
and their customers in a timely manner.
Managing Retail Big
Data
Armed with a definition and a thorough understanding of
the Retail Big Data epidemic, it’s time to take action.
Here are four steps to help retailers turn their Big
Data headaches into Big Data profits.
| Find
the gaps – The
first step to manage Retail Big Data is to
understand the unique data needs. Whether
it’s a chain of two stores or 2,000, there
needs to be a system in place to collect and
process every data point. According to
experts, each store visitor can generate up
to 10,000 data points, for national chains
that can mean millions of data points every
day. |
One way retailers can combat Big Data growth is
through cloud storage solutions. While some retailers
may be hesitant to transition their entire system to
cloud, due to the loss of data visibility, there is a
middle ground that many retailers are taking advantage
of – summary cloud storage. Many retailers are utilizing
the cloud to store summary data from individual stores
and enterprise headquarters for an enterprise-wide view
of the retail chain. This approach allows retailers to
retain their store-hosted data, to meet the individual
store needs, yet also gain the larger bird’s eye view of
integrated data in real-time, through cloud computing.
| Tear
Down the Walls – As the number of data
sources continue to grow, information is
being collected, stored and processed in
numerous locations. Choosing to keep this
data siloed immediately limits a retailers’
ability to succeed. Integrated data provides
a full view of the retail space. It allows
for side-by-side comparisons and enables
retailers to uncover potential savings and
opportunities. |
In one instance, a grocery chain’s inventory and TLog
were not adding up following a recent bottled water
promotion. With siloed data, the retailer would have
needed to identify each of the item transactions, and
then watch hours of surveillance footage to locate each
bottled water scan. However, with a fully integrated
system, a retailer can identify each of the bottled
water transactions, and with the click of a button see
the individual item being scanned. This technology
allowed the grocer to uncover a major scanning issue.
Rather than scanning the case of water that was on sale,
the scanner read an individual bottle’s barcode, thus
accounting for the inventory discrepancy and thousands
of dollars in lost revenue.
| Take
Action – Now that retailers have a full
view of their store environment, they can
determine how to analyze and act based on
the information available. Beyond overall
information access, advanced data
integration systems allow retailers to
create customized reports to review anything
from Human on Transaction (HOT) refunds and
sweethearting, to self check-out (SCO) and
facial recognition. |
Turn up the
Speed – Finally, retailers can take
these insights a step further by increasing
the processing speed. Big Data’s true
potential is realized when the data lag is
removed and retailers are able to interact
with their information in real-time. With
real-time reporting retailers can create
customized alerts for each store, or the
enterprise as a whole, so managers are aware
of issues as they are happening. |
 For example, one client set an alert for drops in
average department sales. Since sales in the produce
department had dropped below the specified figure, the
manager got an immediate alert sent to his phone and
email. Rather than finding out a week later and
searching for an answer, he was able to call the store
manager and determine that the department manager hadn’t
come in, so the department had never been fully stocked
for the day. The managers were able to rectify the
situation in real-time and prevent further revenue loss.
No matter how you look at retail data, one thing is
clear – it’s on the rise. In fact, the world's total
data is more than doubling every two years, according to
a 2011 IDC study. Retailers cannot afford to wait. Now
is the time to get a handle on Big Data and prepare your
company for the data surge. Is your store ready?
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