According to Gartner, the current economic challenges will see enterprises prioritise projects that enable them to downsize their data centre footprint and move their workloads to either colocation or edge compute environments.
This will see the edge computing market grow by a staggering 24.51% between 2022 and 2030. If companies don’t manage and make sense of the increase in data and understand how to integrate their edge and cloud environments, they will leave tremendous business value on the cutting room floor.
Edge and cloud are frequently viewed as competing platforms, but they are synergistic in nature. They complement each other to help organisations understand and action data from all areas of the business. By harnessing the strength of both edge and cloud and the intelligent analysis they provide, businesses can reduce costs and maximise their productivity and efficiency.
Edge delivers real-time actionable insights
Edge is critical in leveraging new data sources to drive specific and differentiated business outcomes. Many businesses have a significant operational technology footprint – anything from industry-specific machines like an MRI machine or conveyor belt to those in almost any building, such as HVACs and elevators, can contribute to this footprint. These resources, however, have typically remained unconnected to a larger ecosystem and therefore offer little business insight based on their activities. Edge provides a unique opportunity to take what was once offline and bring it online, allowing organisations to understand and act on data from their physical business activities.
In the case of a retail setting, edge can play a vital role in offering real-time insights where needed. For instance, when a customer scans an item through the self-checkout, the speed at which pricing is downloaded to the self-checkout can be accelerated to speed up the transaction time. Localised analytic capabilities can identify customers’ purchases and generate real-time coupons for related products. Moreover, local analytics can help retailers prevent loss by mitigating scanning errors and other mishaps at checkout. It’s an opportunity to create DAOs in a retail location. All of which contribute to more efficient processes and a better customer experience.
Consumer trends have continued to shift to online ordering and curbside delivery, shifting the cost of physically picking and packing goods from the customer to the retailer. This shift is costing retailers billions per year in a time of rising labour costs and increasing labour shortages. Edge intelligent automation can help meet retailers where they are, in retrofitting existing retail and warehouse spaces into efficient micro-fulfillment centres, either with robotics or with software designed to guide workers through goods to more efficiently pick and pack goods.
Real-time data often requires immediacy in actions. Here’s where edge can play a critical role. Edge environments are best suited for applications that require accelerated response times. When you pre-process data and perform light analytics locally, you can uncover real-time insights – such as an overheating asset in your manufacturing plant or an unusual motion detected – and act on them within seconds.
Cloud: providing second life to data generated at the edge
While data used at the edge loses value once analysed and processed, it could regain value when transferred to a private or public cloud. The cloud complements edge computing by providing the scalability to keep up with data growth. It also offers native access to services that enable advanced analytics, artificial intelligence, and machine learning. By applying these services to the data collected at the edge, business leaders can gain additional insights and realise their long-term value.
In the retail example referenced above, in-store trends can be analysed by comparing store data over time using advanced analytics activities such as inventory, pricing, and improving employee scheduling. In addition, a 360-degree customer profile could be created by comparing in-store aggregate data and matching it with other data sets, such as loyalty programmes to enable more personal engagement methods. There is no need for immediacy or real-time action in such scenarios, but accumulating data over time can ensure businesses reap long-term benefits.
Using edge and cloud resources in tandem requires consistency
Organisations are realising the need for a distributed architecture to meet their modern-day requirements. One inhibitor of this is the complexity across edge and cloud environments. Each environment supports multiple applications and has its own management capabilities and operations. Hence, businesses must establish consistency across private and public clouds and edge environments.
Establishing consistency across environments will help balance the environmental constraints of the edge with the latency and data gravity of the cloud, as well as leverage the appropriate environment to meet data and application needs and allow businesses to determine where applications reside. It also reduces management complexity and enhances security across every environment.
Looking at this through the lens of the retail example, where physical and digital touchpoints complement each other, customer engagement can be established across multiple mediums to create omnichannel engagement. Advanced analytics can even lead to predictive purchasing, where data is applied to in-store and online activity to determine future buying patterns and consumer intent. This means the store can optimise its selection accordingly.
The key to unlocking the power of edge and cloud-based platforms is identifying and segregating which business-driven tasks and/or operations are best suited for each environment. While time-critical operational tasks sit better in real-time processing capabilities of the edge layer, continuous improvement analysis and overall asset performance analysis, which are less time-critical, operate better in cloud-based environments. Hence, by leveraging both benefits, businesses can maintain optimal operational efficiencies and drive productivity. The possibilities of edge computing are infinite, but ensuring it works in tandem with your cloud computing environment will be absolutely critical.