Capstone Identifies Future Cornerstores

Stocking the store must automate, while customer outreach needs the personal touch—enhanced by data.

Those were the takeaways from the two winning presentations out of the six heard at the Capstone conference of the Food Industry Management Program on April 6 at the University of Southern California.

The Food Industry Management (FIM) Program is a continuing education program for food industry professionals at grocery and consumable goods companies. Now in its 48th year, FIM is part of USC's Marshall School of Business and is sponsored by the Western Association of Food Chains.

The program is a sort of continuing education boot camp for mid-level managers, who may or may not have college degrees. The highlight is a series of presentations by teams of six FIM students. The teams are tasked with identifying a trend or area of interest to the food/grocery industry and putting together a presentation, describing its relevance and offering advice, to an audience of executives. The audience then votes for the two winning teams.

Here are summaries of the winning presentations:


The potential for data-driven shopper personalization was the topic of Team Age of You. The presentation was led off by Billy Brink, operations coordinator for the Ralphs grocery banner of Kroger, who raised the possibility of shoppers being greeted by employees who know all about their preferences and past purchases.

Brink talked about his mother, whose own mother and her grandchildren love drinkable yogurt so much that she shops only in stores where it's on sale. He talked about his neighbor, a caterer whose signature smoothies require massive amounts of avocados. A store that targeted him with consistent deals on those items could lock up his patronage indefinitely.

"You can do this by combining data with artificial intelligence," Brink said.

This kind of personalization is especially important for younger shoppers, said Lizette Gonzalez, marketing project manager for Northgate González Markets, a privately held chain in Southern California.

"Generation Z is the new 'Me' generation, or 'Age of You' generation, and they will expect a personalized, predictive shopping experience," González said. "You need to be not only relevant, but super-relevant."

This can be done through predictive data paired with artificial intelligence, she said. Pure online retailers like mostly have the technological advantage in this regard, but they don't have the potential for personal outreach of brick-and-mortar retailers.

"How do we out-Amazon Amazon?" González said. "We do this by giving consumers a reason to shop at our stores. Amazon may know what our customers want online, but they do not truly know our customers....You need to start using your data in a way that will allow you to be super-valuable and provide a personalized, predictive shopping experience for your customers, and that will allow you to cement that relationship for a lifetime."

Retailers already practice customer segmentation, but modern information technology allows that segmentation to be so intensified that each individual shopper becomes his or her own "segment," said Hugo Quimbaila, a regional sales manager with Bimbo Bakeries USA.

Quimbaila cited Sephora, the French cosmetics retailer, as an example of expert shopper segmentation. He said that Sephora's e-mails to customers have a 91 percent open rate, because the customers expect the offers in those e-mails to be "super-relevant."

"Can we imagine if in our industry, we were able to send communications to our customers, and about 91 percent of them anxiously waited for those communications?" he said. "At that point, in our 30,000-customer store, we have divided them into 30,000 segments."

Lonny Reiber, a district HR coordinator for the Fred Meyer banner of Kroger, said that sales data can be enhanced by other data available through social media.

"When we can take our structured transactional data, combine it with social data—from Facebook, Twitter, wearable sensors—we will create super-relevant data, with that convergence of who and when," Reiber said.

Once data are amassed, they must be properly analyzed. Zac Curhan, a product development manager at Niagara Bottling, described the analytical software that can do this as "a black box" with algorithms that can learn with successive data inputs. Curhan acknowledged that specifying such software is a daunting task that is well beyond the technical capabilities of most retailers.

"Our industry is great at many things, but we are behind in technology," Curhan said. "We should stick with our core competencies and partner with firms who can help us bring predictive technology in-house." He suggested pairing with an established data analytics firm or using Kaggle, an online platform that matches challenges in analytics with data scientists.


When Natural Markets Food Group opened a new store in a new market a few years ago, its opening day was a great success—but that success carried the seeds of future failure, said Victor Farr, the retailer's project manager/business analyst.

Sales and customer traffic were great, Farr said: "Two fantastic problems to have. But the issue was that as our associates tried to keep product on the shelf, they were getting in the way of our customers and clogging up the aisles." This hurt future sales: "I'd be willing to bet that a significant number of customers who shopped with us on that grand opening haven't returned since because of their poor experience."

Team Invisible Hands touted an innovation that it said will virtually do away with that problem, as well as help cut the labor costs, out-of-stocks and shrink that cost grocery stores $100 billion a year. Automated stock replenishment, the team told Capstone, has the potential to be the most significant innovation since bar codes were introduced in 1972.

Automated stock replenishment has two components, which can be implemented in phases. The first is backroom automation. This involves putting a pallet of product through a sorting machine, which breaks down the load and checks it against inventory. It then determines which items should be stored in the backroom and which ones need to go out on the floor; the latter get loaded into a shopping cart in the order that they will be stocked.

"When we can take our structured transactional data, combine it with social data—from Facebook, Twitter, wearable sensors—we will create super-relevant data, with that convergence of who and when."

Lonny Reiber,
Fred Meyer

"This technology is already being utilized in a lot of our warehouses," said Shawn Wolek, a manager with Fry's Food Stores, a Kroger banner. "We just have to utilize it at store level." Doing so will allow retailers to use more of the cubic footage in their backrooms, especially the area above human reach.

The second phase is automated shelf replenishment, which takes the automatically sorted product and pushes it onto the shelves. Every facing on the shelf has its own mini-conveyor belt; items get shuttled across ceiling tracks and loaded onto the back. When not loading items, the system will keep the shelves properly faced and conditioned.

Benefits of automatic replenishment include fewer out-of-stocks; fewer facings, which allows more SKUs to be sold in less space; and less opportunity for employee theft. These benefits are intensified for direct-store-delivery items like beer, soft drinks and bread.

Automated stock replenishment should be seen as a way to enhance employees, not replace them, said Jeanie Goodrich, pharmacy coordinator with Smith's Food & Drug.

"We're not suggesting that jobs be eliminated," Goodrich said. "Rather, we're advocating that jobs be realigned to better serve the needs of our customers. Employees will now be able to focus on our customers instead of getting in their way." This will increase job satisfaction and reduce turnover, she said.

Retrofitting a store for both phases, backroom and shelves, would cost about $2 million, Team Invisible Hands estimated. Estimated gains include a sales and margin increase of 6 percent, a 50 percent decrease in shrink of non-perishable goods, and a 15 percent decrease in labor costs. The average estimated payback period is 3.2 years.