Loss Prevention Starts Where Self-Checkout Ends

Pulling self-checkout out of stores might solve one theft problem, but it opens up
another one immediately: the labor and awareness that kiosk used to provide has to
come from somewhere else. Mike Korcuba, SVP of Sales at Telaid, and Ross Page,
SVP of Sales, Growth at Telaid, recently broke down what actually reduces shrink
once self-checkout is gone, and how a retailer proves that new technology is worth
the investment rather than becoming another cost to justify.

Fighting Shrink Without a Kiosk to Blame It On
For a retailer pulling self-checkout back out to fight theft, Korcuba starts with the
math: shrink is measured as a percentage of sales, so removing a self-service
option only helps if customer service reenters the equation at the same level the
kiosk once provided. That means rethinking staffing so a transaction still feels safe
and accurate, with someone in place to help enable it, all while balancing the added
payroll against the loss that staffing change is meant to prevent.

When Staffing Is Light by Design, Technology Has to Fill the Gap
In a store that runs one or two people on a shift by design, Korcuba says the
technology has to do the work a human simply cannot. That means basic situational
awareness: was a customer acknowledged when they approached, was the lighting
adequate at night, was the signage clean, did the store look maintained. Every one
of those small details either builds or erodes trust in the brand, and AI powered
computer vision is what makes it possible to flag those gaps to leadership rather
than relying on someone catching them by chance.

The Value That Goes Beyond Stopping Theft
Beyond catching theft outright, Korcuba frames an integrated camera and analytics
system as a stand-in for a manager who cannot be on-site around the clock,
verifying that policy and procedure are actually being followed rather than just
written down somewhere. Low staff equals opportunity, in his words, but an
integrated security system that is monitoring that opportunity and reducing it
incrementally is what turns that risk into a result, and a foundation a retailer can
keep leveraging for other use cases as computer vision and AI continue to learn.

What Has to Be True Before AI-Powered Shrink Analytics Actually Work
AI powered shrink analytics is one of the biggest trends in the industry right now, but
Korcuba is clear that what happens underneath the analytics matters more than the
analytics themselves. Every environment is different, and the decision of whether to
process on-site or in the cloud shapes everything else: on-site compute demands
the right infrastructure in the building itself, while cloud compute requires enough
bandwidth from the store to get there. Telaid's solutions team helps assess that
balance quickly, since some data needs to be real time to support situational
awareness in the moment, while other KPIs a manager wants can be reported after
the fact on a daily, weekly, or monthly basis rather than live. From there, the real
question becomes practical: what type of infrastructure does the store need, how
fast does it need to be, and how quickly does that information need to land in
someone's hands.

Holding One Standard Across Thousands of Small Format Stores
For a retailer running tens of thousands of small format locations with almost no on-
site support, holding one repeatable, low touch technology standard is its own
discipline. Page points to standardizing the technology being deployed and having
enough of it on hand that a rollout never has to shift standards mid-deployment,
paired with staging, kitting, and configuration done centrally before anything reaches
a store. He also points to DeviceWatch, Telaid's monitoring platform, as what lets a
retailer with minimal on-site staff keep tabs on whether security systems, point of
sale, and access points are functioning properly, with self-healing capability built in
to reduce truck rolls and keep stores producing revenue rather than sitting on a
service ticket.

Korcuba adds that a hybrid workforce model, pairing a partner technician with a
Telaid W-2 technician for the first several sites in training mode, is what allows that
standard to scale quickly afterward. Both technicians become proficient enough in
the technology being refreshed to move through the rest of a territory with minimal
oversight, turning training into scale rather than a bottleneck that slows the rollout
down.

Making the ROI Case When Every Dollar of Margin Counts
For a retailer under pressure to prove new technology pays for itself rather than
becoming another cost to defend, Korcuba breaks the case down to a balance
between capital and operating expense: a well chosen capital investment should
reduce ongoing maintenance costs, which only holds up if the CapEx budget was
realistic to begin with, since a new piece of technology should not need major
maintenance for years after it goes in. From there, he ties every investment back to
three factors: its effect on payroll, its effect on cost of goods sold, including spoilage
in some environments, and whether it reduces the time required to do a task.
Retailers honest about those three factors, he says, consistently find the ROI case
holds up, sometimes revealing unintended benefits after the fact that never made it
into the original model, the kind of insight worth documenting and sharing across the
rest of the business.

Page closes the loop by pointing to who is in the room when those decisions get
made. Bringing marketing into the technology conversation early lets a retailer use
the same camera investment to understand customer path and end cap
performance, turning one capital investment into a faster return through loss
prevention and marketing working from the same data instead of two departments
solving the same problem separately with two separate budgets.