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The Profit Hub


Mike Limauro, VP of asset protection for Sunbury, Pa.-based Weis Markets, should change his title to VP of asset expansion — that would be more appropriate, given the functions his team has been performing since deploying new technology from Profitect.

Indeed, Limauro’s asset protection philosophy is that the team isn’t merely protecting the company’s profits, but also growing them by taking the Big Data analytics power of Profitect’s cloud-based Profit Amplification solution, a pattern-seeking predictive analytics tool, and leveraging it across the entire enterprise.

Here’s an example: The system found that while one store received a shipment of two cases of frozen pizza, it hadn’t sold any within 10 days. Meanwhile, that frozen pizza SKU was selling well at other Weis stores in the same geographic area. A member of the Weis asset protection team called the store and asked whether the frozen pizza was still in the back-room freezer. When the store associate returned to the phone, he asked if someone from the asset protection team was watching on camera or had visited the store, because that’s exactly what had happened. But it was done from the Weis corporate office, using data.

Soon, Weis won’t even have to call the stores in such a situation; the system will send an alert to the store manager, suggesting — in plain English — that he or she check the back room for the “shipped but not sold” product.

“We are using loss prevention technology not only to reduce shrink and loss, but also to help improve sales,” says Limauro. “From an asset protection (AP) standpoint, it’s awesome to be able to insert ourselves into the enterprise, and also use it for things like shelf-space allocation, sales, production — areas that are outside the typical AP uses. We refer to it as our ‘Profit Hub.’”

According to Guy Yehiav, CEO of Waltham, Mass.-based Profitect, the solution, a prescriptive business intelligence platform, enables a retailer to load it with data from throughout the business (point-of-sale data, financials, inventory, pricing data) — as well as outside data, including unstructured data (syndicated data, social media posts, reviews) — and looks for patterns and anomalies within that information to alert the organization to opportunities for operational enhancement.

When it finds such opportunities, it communicates to the retailer in plain language, rather than charts, graphs and numbers, to avoid the risk of misinterpretation. “Retail is a very high-attrition business, and you may have employees working together with different retail backgrounds,” notes Yehiav. “If they look at a spreadsheet filled with numbers, they each may interpret it differently, based on their experience at other retailers. With descriptive insights, they will both be on the same page regarding the area of focus, as well as the recommendations on how to act on that data.”

Profitect developed its system based on the premise that small issues that happen frequently throughout the retail value chain can contribute to significant margin and sales leakage. These issues often go undetected in reports using aggregated data, which results in missed opportunities for profit improvement. Profitect enables the retailer to mine massive amounts of data at a granular level to discover such areas for profit improvement.

It still uncovers traditional loss prevention issues, of course. “We had a situation where a cashier was scanning coupons with no merchandise purchased, or ‘outside of a transaction,’” says Limauro. “The cashier would then take the cash, and the register would balance. Not only did we use the Profitect tool to help us resolve this case, but once we closed the case, we reverse-engineered the method of fraud and built a pattern within Profitect that searched for any transaction where a coupon was redeemed outside of an actual sale. Now we are notified as soon as this occurs, so we can respond immediately and minimize our loss. We have dozens of these patterns currently set up.”

Rethinking the Audit

In addition to the Profitect suite’s Point of Sale and Inventory modules currently in use, Weis is piloting a mobile field application that it actually assisted the vendor in developing.

Here’s how it works: When entering the store, the app automatically knows which store it is via GPS, and displays the store attributes, including who the manager is, the store volume and the square footage.

The main screen displays the store report card divided into two sections: point of sale and inventory. On the point of sale side, it displays metrics related to the front end, such as voids, refunds, rings per minute and overall customer service score. To see more the details behind each figure, the user simply touches the appropriate category on the screen, and it will drill down all the way to the cashier level.

“On the inventory side, I walk into the store and it will show me things like known loss,” says Limauro. “For example, it might show me seafood, with a dollar amount in red. If I tap on it, the app will drill down deeper to the actual product, maybe cherrystone clams. Based on that information, we’ll walk over to the seafood department and see maybe we have way too much shelf space allocated to cherrystone clams. The great thing is, it’s all based on factual information and is very targeted.”

The app also enables the auditor to take photographs, record video and take notes as he or she evaluates the store. “What we are working on now — and I think this is going to change the industry as far as how we communicate and tour stores — is what I call a ‘smart audit,’” says Limauro. “I click on an audit button — which is there today — and then that iPad app is going to build me a smart audit based on that store’s key performance indicators (KPIs). So rather than running through an audit checklist in which most of the items are routinely going to be OK, what this does is eliminate all those audit areas in which the store is performing well, and focuses on the areas in which the store has troubling KPIs. So, in other words, it’s instantly building me a customized audit that will be designed to help that specific store improve, based on that time and moment at that store. It’s much more efficient.”

The app also goes out to the Internet and pulls social media data — such as posts about the store on Google or reviews on Yelp — which, along with the other data gathered, provide an overall customer service score for that store.

At the end of the visit, the app compiles all of the information that was discussed, as well as the related notes, scans, pictures and videos, and sends it directly to the store manager, along with action items to improve those areas not meeting KPIs. The store’s progress can be followed by the auditor as the action items are closed out.

What makes the Profitect solution so effective for Weis is that the more it’s used and the more data inputs are added to it, the more helpful it becomes, so Weis plans to expand its use and flood it with data. According to Limauro, users regularly discover new ways of applying the technology, and as more users and more data inputs are plugged into the system, it will continue to evolve. There are already 327 users at Weis, and once store managers are added, which is expected to happen shortly, there will be close to 500.

“We feel that the more data that we can push through it, the more exceptions it’s going to create, but also the bigger picture it’s going to create,” he says. “So instead of having asset protection technology being guarded and being a secret, our philosophy is, let’s get everybody using it and customize it, and continually explore new ways to use it that are really applicable for everybody in the company.”

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