Better Retailing With the Edge

Press enter to search
Close search
Open Menu

Better Retailing With the Edge

By Joe Ackerman - 12/13/2019

Data processing, analytics, and storage for retail operations are increasingly taking place at the network edge, close to where users and devices need access to the information. Right now, companies are generating about 10% of their data outside a traditional data center or cloud. But within the next six years, that will increase to 75%, according to Gartner.

Today’s retailers must embrace a reality where they compete not just on the products they offer, but also on the technology they use to sell and deliver those products and provide the desired customer experience. Highly customer-focused companies, with operations and technologies aligned to provide a consistent, omnichannel customer experience for product exploration, selection, ordering delivery, returns and support are using big data effectively and more and more in edge environments in distribution centers and stores. The technology can deliver improved analytics and greater customer understanding from first point of contact to purchase decision and beyond. This includes information gathering and dissemination at the edge.

Edge technology can deliver a lean, fast and reliable IT infrastructure that can run multiple applications. Retailers with distributed networks need the capabilities edge deployments deliver to give their customers the experience they have come to expect – whether making purchases online or in the store.  

Supporting edge computing

In the past, retailers might have used a small server room that allowed the registers, with individual backup power systems attached, to communicate with an enterprise data center. The information exchange was slow and was more or less one-sided. Shoppers now expect information to be as fast as their phone. One such tool used to achieve faster customer service is smart shelves. Smart shelves are fitted with weight sensors and use RFID tags and readers to scan the products on display and stock shelves. These digital technologies provide retailers the ability to detect and manage shelf inventory using machine learning and image and object recognition technology. The shelves can track and quickly alert retailers when items need to be restocked, preventing a missed sales opportunity and a disappointed customer.

Vertiv has found that retailers that need to support smart shelves and additional in-store technology are chiefly interested in IT infrastructure systems that are affordable, can be scaled up quickly, yet are flexible in their configurations. The infrastructure required consists of four layers of storage and compute in addition to the communications infrastructure required to move data between the layers.

At the source, there is typically the device that generates or consumes data and a processing endpoint. The device could be a sensor monitoring anything from the powered status of in-store lighting, the temperature in a cooler or the use of an app in a grocery aisle. The processing endpoint may be as simple as the PC or tablet a consumer is streaming video to, or could be the microprocessors embedded in automobiles, robots or wearable devices. These components are application-dependent and are typically designed in by the equipment manufacturer or retrofitted to existing devices.

A local data hub makes it possible by providing storage and processing in close proximity to the source. In some cases, the local hub may be a freestanding data center. More commonly, it will be a rack- or row-based system providing 30 to 300 kW of capacity in an integrated enclosure that can be installed in any environment.

These rack- and row-based enclosure systems integrate communication, compute and storage with appropriate power protection, environmental controls and physical security. For situations that require a high degree of availability, the local hub should include redundant backup power systems and be equipped to enable remote management and monitoring. Many uses cases also will require data encryption and other security features within the local hub. For most applications, the local hub will require the ability to connect to a metro and/or regional hub, which will provide longer-term data storage and support capabilities such as machine learning.

Local and regional hubs, as the need arises, will require modular designs capable of easily scaling beyond the initial design spec to account for unexpected surges in demand. These facilities also should be designed to scale in terms of density.

Conclusion

In the retail industry, successful IT management of multiple stores in various locations is a critical component to maintaining business continuity. Edge computing provides compute and storage resources for retailers with adequate networking close to the devices generating traffic. The benefit is the ability to provide information and decision-making quicker than in the past and better service to customers.

Joe Ackerman, director, Business Development, Vertiv