Article by: Shobhan Lakkapragada, Senior Director of Product Management, Edge Computing, Red Hat
It’s 2024 and the chaos of holiday shopping is officially behind us. Whether you managed to get all of your gifts ahead of time or you were more of a last minute shopper, I bet there are some notes you’d have for retailers about how to make your shopping experience even smoother. Was the in-store experience chaotic? Did you have the ability to use self-checkout? Was there a buy online and pick up in-store option that actually gave you up-to-date inventory? These are all questions we’re asking ourselves as shoppers, but how are retailers working to make it happen?
There are a lot of pieces to this puzzle, but the most obvious one is AI. It's a crucial part of retail transformation, from self-checkout to inventory management and more. But retailers don’t just “enable AI” for their stores. They’ll need to implement a single, enterprise platform for edge computing that will support AI and other critical technologies in their transformation strategy. And edge computing, in enterprise leadership circles, is a constant discussion topic. Whether it be the far edge in space, software-defined vehicles as edge computing devices or remote sensors in the desert, edge computing is helping drive transformative innovation across industries.
Heightened customer expectations and evolving market dynamics are driving increased adoption of retail technology. Accelerated by the pandemic, restaurants and supermarkets have to shift business models to accommodate options like curbside pickup and ecommerce. Also, the cost of labor is rising but the cost of core technologies are declining, especially those that live at the edge. This means retailers are beginning to explore new solutions to help deliver a more efficient and personalized customer shopping experience including:
Edge computing can help retailers drastically improve consumer experience
As a result, we see retailers, including Red Hat customers, investing in three core areas: point of sale (POS) modernization, computer vision and warehouse automation.
Red Hat Edge’s validated patterns
For example, one customer is serving more than 65 million customers across North America, with 1,200 stores nationwide. Faced with rising operational costs, a need to continuously improve customer in-store experience at checkouts/with loyalty programs and a constant mandate to efficiently manage POS systems across stores nation-wide, this retailer needed to reassess its technology footprint.
To do so, the company chose to reset its POS infrastructure with a single, enterprise platform approach for edge computing using Red Hat Enterprise Linux (RHEL), Red Hat OpenShift and Red Hat Ansible Automation Platform.
The effort addressed 4 key technical challenges, including:
The retailer chose to modernize its POS infrastructure with an enterprise platform that can help address the network edge needs of the retail industry. With this approach, retailers can deploy data closer to where it is collected, and where most customer interactions take place—in this case, in one of our customer’s 1,200 stores. Since their POS modernization, the retailer is now able to better respond to rapidly changing market conditions, create differentiated consumer experiences and improve operational outcomes more efficiently. With a reliable and consistent infrastructure, they’re able to be fully focused on compliance and security measures.
When maintenance or security updates need to be rolled out, automation allows IT teams to deploy at scale, while retaining a security-first mindset. This can mean detecting potential issues before they reach production and mitigating or outright eliminating these issues, all because teams are freed from rote, time-consuming maintenance to focus on what matters: IT security and the customer experience. This results in a more positive customer experience while reducing operational costs and boosting the bottom line.
Journeys may differ, but the end goal is the same - improve customer experience, drive operational efficiency and open up new revenue opportunities.
Red Hat’s open innovation enables modern “in store” experiences
Many customers are deploying modern AI-driven and computer-vision enabled solutions from independent software vendors (ISVs) to enhance the self-checkout experience for consumers, with a more user-friendly experience than scanning barcodes. This means customers can pick up their items, drop them in the basket and walk out without having to “check out” or wait in line to pay. Similarly, AI-driven applications can aid in footfall analysis to understand consumer behavior, and modern loss prevention solutions that don’t rely on RFIDs or security tags attached to merchandise.
To deploy these types of applications, retailers need a modern enterprise application development platform for in-store servers that connect back to their core applications across the hybrid cloud. Red Hat OpenShift and Red Hat OpenShift AI are helping customers deploy these applications - whether homegrown or ISV built - on these platforms.
We’ve also recently announced the availability of Red Hat Device Edge. Red Hat Device Edge provides a more consistent platform designed for resource-constrained environments, especially those that require small form factor compute at the device edge This makes the solution an ideal fit for retail POS systems. Red Hat Device Edge aggregates an enterprise-ready and supported distribution of the Red Hat-led open source community project MicroShift (a lightweight Kubernetes project derived from the edge capabilities of Red Hat OpenShift) along with Red Hat Enterprise Linux and Red Hat Ansible Automation Platform for more consistent Day 1 and Day 2 management of hundreds to thousands of sites and devices.
For more information, you can visit redhat.com/edge.