The global Industrial Internet of Things (IIoT) market is growing at a rapid rate, permeating industries across all sectors. Recent studies estimate that IIoT will add $14.2 trillion to the global economy by 2030. And as IIoT continues to grow, the buzz around edge computing is growing in parallel. Operators are beginning to drive more computing power to the edge of their networks, where IIoT functions really live. By observing industrial enterprises, we can see an interesting evolution taking place as companies implement IIoT systems. Operational technology (OT) teams have historically focused on the automation equipment – both hardware and software – in their wheelhouse, but are increasingly beginning to focus less on the tools themselves and more on the data generated by their systems. Enterprises are becoming more focused on data than they are applications – further recognising that data and analytics have great potential for unlocking business value.
What’s Driving This Shift?
The top priorities for driving value with IIoT include uninterrupted production and driving new cost efficiencies. While this is not expected to change, a number of enterprises are also beginning to adopt hybrid clouds to distribute workloads more efficiently – particularly for mission-critical functions as well as real-time processing. With increased automation, data will make the IIoT a long-term business objective – and serve as a competitive differentiator for industrial operators.
This shift is also being driven by the explosive growth of data – and business proof in that data’s value. Data and analytics are currently capable of producing insights that help enterprises make informed decisions. However, as more data becomes available, we’ll see how those insights will become more intelligent and invisible – systems will soon enable real-time optimisation and make decisions autonomously based on artificial intelligence (AI), without the need for human intervention.
Data Criticality
Along with increased usage of data from IIoT and automation systems, the criticality of that data will also increase, thus requiring greater protections. In fact, operators may realise that the data being produced is the most valuable asset of their IIoT efforts; data must be protected if industrial companies hope to be successful with analytics. Therefore, protecting important data requires ensuring reliable infrastructure, predictive servicing, performance applications, and secure connectivity. Operators must protect their hardware while also addressing the need for unified edge infrastructure that evolves their existing capabilities.
How Edge Can Help
As IIoT adoption continues to increase – especially as devices themselves evolve to become less expensive and more powerful – edge computing is escalating in importance for managing large amounts of critical data. Enterprises should consider merging their IIoT applications and software, along with comprehensive predictive modeling capabilities. In fact, this will be the future platforms of next generation edge processing. Edge computing will simplify these solutions to reduce costs and help minimise the burden on IT teams. Moreover, it will enable OT to lead the IIoT transformation and eliminate production downtime.
There is so much possibility for the future of IIoT – and computing at the edge magnifies that potential for enterprises. Understanding what’s driving this ongoing shift in IIoT from a focus on applications to data, tapping into the true value of that data, and leveraging the power of edge computing will help enterprises succeed as they take off on their IIoT journey.
