A New Year Pushes New Ambitions to the Edge of Possibilities
By Matt Jackson, Vice President of Digital Innovation, Insight Enterprises
So much has changed in recent times with how we work and interact with one another. This blog is the second installment in Insight’s Be Ambitious series, exploring the unique ways companies can forge into the unknowns of an ever-evolving future by embracing bold changes through technology.
As we kick off a new year, business and IT leaders are thinking about how to productively set and successfully reach goals for their organizations in 2022.
Whether it’s efforts to enhance customer experiences, improve employee satisfaction, or drive cost optimization, technology investments are expected to take center stage for businesses across sectors as they continue to adapt to today’s digital-first requirements. In fact, Insight’s recent Intelligent Technology Report found that 60 percent of IT decision-makers are reporting increased IT budgets for long-term innovation.
Specifically, leaders are turning to the Internet of Things (IoT) and edge computing to drive digital transformation across their organizations — one in four IT decision-makers expect IoT and edge computing to have the biggest expected impact on business transformation over the next three years.
Because there are various competing priorities for IT, it can be difficult to determine where to strategically invest resources, time and expertise. However, leaders can look to crucial IoT edge trends and applications to consider more ambitious approaches to moving innovation initiatives forward.
And now is the right time to invest in intelligent edge solutions. An overwhelming majority of North American enterprises (95 percent) have reported that the pandemic has either accelerated business transformation initiatives, highlighted gaps in their roadmap to transformation, or prompted them to develop a roadmap in the first place. Disruption often creates a need for innovation in order for businesses and their people to adjust to a new normal, and the frontier of innovation is at the edge.
Unlocking the Potential of Edge Computing
First and foremost, we must define the intelligent edge and understand how it plays an integral role in data analysis. This technology is an on-premises system that collects, processes and acts upon data gathered on-site and helps users process data near its source, as opposed to having to send data to a central computing system for processing.
Edge computing works in tandem with IoT because connected devices help gather data on-site. Then, intelligent edge technology provides the ability to process the data without any latency, dissolving the need for time-consuming transport of workloads back to a central computer.
Ultimately, because it’s in proximity to the actual data source, edge computing — with the help of IoT — allows for more real-time, predictive insights, along with dramatic cost optimization.
The speed achieved by this duo can enable more efficient operations across sectors.
For example, grocer Harris Teeter has begun exploring greater automation of food handling in its stores by utilizing our scalable IoT hub, the Insight Connected Platform. By adding to appliances sensors that are connected to the all-in-one edge and data analytics platform, store staff can prevent potential food loss through instantaneous temperature alerts if a freezer malfunctions. Providing automated temperature and humidity monitoring with real-time notifications enables any restauranteur or food handler to simplify food-safety compliance, ensure consistent quality and reduce food waste.
Similarly, applied in mining locations with expensive and temperamental equipment, edge and IoT solutions are making a tremendous impact. As underground machinery like crushers and loading bins collect and process ore, if the wrong minerals are processed or if bins overload, the entire machine can break easily, not only costing millions in repairs but causing safety risks and shutting down operations until the machine is fixed.
Edge computing enables sensors to gather visual data then used to develop models for predictive analytics that can evaluate the mineral content of ore being processed by the machines, completely mitigating the risk that the wrong rocks break the machine. Likewise, a sensor-driven Artificial Intelligence (AI) platform incorporates soft or virtual sensors using signals produced by system software to create advanced analytics in the cloud and the model to take advantage of thousands of different data points. The built-in intelligence allows the mining company to predict the level of crushed ore in bins to prevent overfilling or underperformance through continuous fed from the crushed ore bins.
Intelligent edge technology is only growing in prominence: Gartner predicts that by 2025, 75% of enterprise-generated data will be created outside of centralized data centers. In fact, other technology advances — like 5G and AI — improve how we process data at the edge.
The money and time saved from intelligent edge solutions like these produce a massive return on investment, not just for mining companies, but for manufacturers, logistics, healthcare and retailers who are increasingly adopting computer vision AI and data analytics to provide new views into their business.
Other use cases include helping cities and schools to improve health outcomes with state-of-the-art patient analytics.
5G Drives Predictive Data Analytics
5G enables high-quality video for augmented and mixed-reality devices that allow for predictive maintenance and remote monitoring for quality inspection and employee safety. This is especially relevant in heavy-duty manufacturing or transportation and logistics environments that benefit from edge computing.
For example, IoT edge servers can attach directly to gas distribution sites, providing a read-out of telemetry data — or remote monitoring data that would otherwise be inaccessible to gather without these devices. This process ensures there is safe, cost-effective transportation of resources from start to finish.
Mining companies, along with companies transporting essential but combustible goods like natural gas, require clean, fast, and safe, operations to get the job done; 5G-enabled edge and IoT make this movement of resources possible. Similarly, autonomous vehicles become more accessible as 5G eliminates latency issues.
AI Chips Enable Data-Driven Decision Making
Insights gleaned from using AI chips are used to imbue edge solutions with the ability to develop AI models for predictive analytics that garner valuable insights for businesses, cut costs and improve customer experience.
Take large healthcare systems, for example, that deal with massive amounts of patient data that must be processed in a secure and timely manner. Edge IoT servers can process data across all these disparate networks and generate insights based on AI models to improve patient outcomes and streamline operational costs. And these solutions can maintain the necessary security measures to keep private health information safe and secure as the data is processed.
Better data drives improved decision-making in the areas that matter most for businesses. And as organizations scale out edge and IoT solutions, AI chips are in high demand. In fact, Deloitte has predicted that edge AI chip units will exceed 1.5 billion by 2024.
As intelligent technology becomes more prevalent, businesses can think more creatively about how they adapt to today’s rapidly evolving business landscape. IT leaders who can channel big ambitions into strategic innovation and digital transformation will see more meaningful results — especially if it means pushing their organizations to the edge of what they can really do.
Matt Jackson leads Insight’s digital innovation team of 1,300 architects, developers and engineers in consulting on digital transformation strategies. They create modern solutions for applications, data, AI, IoT, networking, security and productivity. His passion goes beyond achieving operational excellence and deeper into transforming how organizations conduct business. Read more thoughts from Matt.
