In my role as an advisor on Internet of Things (IoT) and smart cities, I often get asked “What trends will shape my industry in the next five years?” The answer is applicable to every industry — data and your ability to create a competitive edge from that data.
We live in the data era, characterized by an explosion of data sources and the race to collect data — both from us and about us — and innovations in analytics and artificial intelligence (AI) that help us extract more value from data. One of the hottest topics we discuss with customers in this context is the edge. Although there are many definitions of edge, I prefer a simple one that describes edge as any place where data is acted on near its point of creation to generate immediate, essential value.
The ultimate goal is to generate new business insights and move toward becoming a data-driven organization. Edge will be an important factor in making this happen. IDC predicts that by 2024, due to an explosion of edge data, 65% of the G2000 will embed edge-first data stewardship, security and network practices into data protection plans to integrate edge data into relevant processes. This is very significant as it means a shift of focus on many fronts. Your organization will have to consider what data to capture at its edge locations — such as branches for banks and stores for retailers. You will have to think about what infrastructure will host the data, where that infrastructure will run, what applications are needed to analyze the data and, most importantly, how to manage and secure these remote edge locations.
A key discussion we often have with customers is about what business insights their data can provide. The answer is dependent on the industry, the use case and the individual company’s needs and capabilities. We often refer to specific use cases in each industry to show customers the potential of data, but what we end up with might be a completely new scenario that is very specific to that customer’s environment. The following are just a few examples.
The retail edge
In retail, the use of video analytics and computer vision has made it feasible to collect insights on customer behavior at the retail store level. This data, collected at the edge, can inform many departments within the retailer. Marketing can understand customer demographics in relation to the time of day, the weather or local events and deliver targeted content accordingly. Operations can use computer vision to detect unusual customer behavior and inform the store manager in real time. The customer experience department can analyze information on total store foot traffic, link it to actual sales and possibly change a store layout in response. Analyzing video data at the edge is key for these use cases because it’s not practical or cost effective to transport video data to a central location for analysis.
The healthcare edge
Healthcare is another vertical where edge use cases are gaining traction. Hospitals are looking for real‑time tracking of people and assets and combining it with other sources of data to generate meaningful insights. A use case we worked on recently started as patient and staff tracking but turned out to be extremely useful for compliance. By combining edge data on staff and patient location with sanitizing station events, the hospital was able to confirm, with data, that the staff has performed the sanitization protocol before attending to the patient. In another use case, advances in AI along with digital pathology are enabling pathologists to speed their image analysis, all while reducing human error. This analysis requires powerful GPU-enabled servers that are sitting at the edge, where the images are produced.
The manufacturing edge
In the manufacturing industry, where margins are tight and competition is fierce, many manufacturers are looking for ways to optimize their operations, minimize waste and create a better workforce experience. Data is leading them to deep operational insights driven by edge analytics. By collecting real-time data from programmable logic controllers (PLCs), edge analytics is enabling the monitoring of manufacturing process quality and providing early warning should something go wrong on the production line. For example, a steel factory we recently engaged with plans to deploy edge analytics to minimize irregularities in the steel beams it produces, which will result in significant savings in cost and time.
The edge is for every industry
Whatever industry you are in, you can bet edge will play a role today, and in the future, to drive efficiency and innovation through data. Be sure to start looking at what data you have and what insights you could generate, to stay competitive in the new data era.