3 Key Reasons Retailers are Embracing Edge Computing

Scaling Retail Operations with a Cloud + Edge Computing Hybrid Approach

To meet the demands of digital transformation, many organizations have adopted cloud-based systems, such as Amazon AWS, Google, and Microsoft Azure, to improve their operations. These platforms allow retailers to scale their resources as needed and to take advantage of advanced features such as machine learning and big data analytics, but cloud solutions still fall short of the benefits gained when combined with computing at the edge:

• By reducing the need for expensive wide-area network connections and data transfer costs, edge computing can help retailers save money on their IT infrastructure.
• By bringing the computing power closer to the point of data collection, edge computing decreases the amount of data that needs to be transferred over long distances.
• By reducing costs, retailers save on their IT infrastructure, as they will not have to invest in as much bandwidth or pay for as much data transfer.
• By increasing speed of deployment, retailers can also quickly implement new applications or features, such as interactive displays or ML models, without having to wait for connectivity to a distant data center.

Additionally, by decreasing the amount of data that needs to be transferred, edge computing can also reduce the risk of data breaches and improve data security. With fewer data transfers, there is less opportunity for data to be intercepted or compromised in transit.

Because edge computing processes sensitive data, such as PII (personally identifiable information), at the point of collection, rather than transmitting this information over a network to a remote location, it also reduces the risk of data breaches.

In short, edge computing supports the scalability and flexibility required by retailers to meet the demands of the digital age and addresses the challenge of balancing the need for security with the need for innovation and scalability.

Adapting to Digital Change: How Retailers Can Maintain a Competitive Edge

AI and machine learning can be used for a wide range of applications in retail, such as product recommendations, inventory management, and customer segmentation. However, these models require large amounts of data for training and operation, which can be challenging for traditional computing infrastructure. Running these models in cloud infrastructure may result in high latency, which can impact the customer experience negatively. Because edge computing processes and stores data closer to the source, it results in faster, more reliable decision-making.

Example: WalMart has implemented edge computing in their stores to improve the accuracy of their inventory management system by processing data in real-time. This allows them to optimize their stock levels and reduce waste.

Rich content is becoming increasingly important in retail, as it allows retailers to showcase their products in the best possible light and create an immersive shopping experience. However, delivering this content through traditional computing infrastructure can be challenging, as it requires large amounts of bandwidth and storage.

Example: Nike has implemented edge computing in their stores to enable the delivery of high-resolution product images and videos to customers. This allows customers to view products in great detail and make more informed purchase decisions.

A high degree of interactivity is crucial for retailers as it allows them to create personalized shopping experiences for customers and increase sales. However, achieving this interactivity through traditional computing infrastructure can be challenging, as it requires low latency and high availability.

Edge computing enables faster processing and real-time data analysis, which is crucial for new applications such as real-time inventory tracking, predictive maintenance, and personalized customer experiences. It can also improve operational efficiency and enhance the customer experience. By incorporating an edge computing solution that integrates seamlessly with existing infrastructure, you’re able to focus on identifying and implementing new technologies that will benefit the company, regardless of hardware requirements.

Integrating New Technologies with Edge without Overhauling Infrastructure

Retailers often have large and complex technology infrastructure, which can make it difficult to manage and maintain. Additionally, many retailers have legacy systems that are challenging to integrate with new technologies. Edge computing allows retailers to host their legacy systems along with newer microservices components, bridging the old with the new. This can be used to improve the operation, scalability, and reliability of systems such as point-of-sale systems, with newer technologies, such as IoT sensors or ML models, allowing retailers to take advantage of the latest advancements without having to completely overhaul their infrastructure.

Edge computing doesn’t necessarily replace legacy hardware in-store, or cloud-based systems already in place. When used in conjunction with existing systems, edge computing provides powerful solutions to everyday retail problems, such as inventory management and product placement.

For example, a fashion retailer could use edge computing to deploy interactive kiosks in their stores that allow customers to browse the entire inventory of the store and make purchases through the kiosk. The kiosk would have the ability to access cloud-based inventory data and real-time analytics, allowing the retailer to make better decisions on restocking popular items and displaying them prominently.

Another example is a grocery store that uses edge computing to deploy cameras and sensors that track customer behavior and product placement in the store, enabling them to optimize their product placement and displays based on real-time customer behavior data and analytics.

By using edge computing in combination with cloud or legacy hardware back-ends, retailers can deliver new and innovative applications that improve customer experience and increase efficiency, while also reducing costs and improving reliability.

Adopting Edge Computing as a Strategic Solution

Edge computing is a key solution for retailers looking to take advantage of new technologies and stay competitive in the digital age. With edge computing, retail brands can create a platform that is foundational to the modernization of store infrastructure. This includes:

1. Edge as the launching point for new microservices applications
   
   The next generation of retail applications including those that feature AI and ML models are typically delivered as microservices software designed to run in lightweight containers. An edge platform is the optimal way to deploy these systems and can be used to deliver multiple internal or 3rd party applications on an edge platform rather than on individual dedicated servers.
   
   
2. Edge as an approach for modernization of legacy applications
   
   Edge computing can be used to virtualize legacy systems where virtual machines can run at the same time alongside new lighter-weight containers and microservices applications, providing a path for moving workloads out of monolithic systems into a more agile architecture. Workloads can also go from a monolithic architecture and be delivered as lightweight containers.
   
   
3. Edge as platform for reducing TCO while improving agility and reliability
   
   Edge computing supports high availability multi-node clusters which are inherently able to continue to operate even if a single small edge server in a cluster were to fail. They can also recover automatically from software or OS level failures, bringing unprecedented levels of reliability to hosted store systems, whether legacy or next generation. In addition, edge solutions should use devops and SRE best practices to allow for automated cloud management and programmatic operation at significant scale, allowing a very small number of remote retail IT support staff to manage a large number of edge systems. In addition, edge platforms provide elastic agility, with the ability to allocate resources, deploy new VM and container-based applications, and make significant system changes on an automated basis, reducing the time and cost of application delivery and support.

To be competitive, retail CTOs should consider these three key drivers – adapting to change throughout digital transformation, identifying methods to lower overall costs, and bridging the gap between legacy systems and emerging technologies. The only way to make all these a reality is by integrating legacy systems, next-generation applications, and innovative IoT technologies using edge computing. 

Edge computing gives retailers the speed, consistency, reliability, scalability, low latency, and security needed to create digital experiences that customers expect and will come back to over and over again.

Learn more by downloading our E-book on Accelerating Innovation at the Edge with 5 next-generation use cases.