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Post-Covid Industrial IoT Spending Set to Quadruple


Industrial IoT paves the way for industrial companies to shift from selling products to delivering services and solutions.

Industrial companies intend to spend $20 billion on Industrial IoT data analytics over the next five years. This was spurred in large part by the Covid crisis, which revealed weaknesses in their digital transformation strategies.

In the most recent year measured, industrial firms spent $5 billion. That’s the word from ABI Research, which found that all industrial digital initiatives are created equal, however. Select digital transformation initiatives that gained momentum over the past year include cloud for collaboration and synchronization across teams and departments; digital twins for monitoring and maintenance; and analytics and AI for system-wide, software-driven automation.

See also: IoT Careers, 2020: Many Hands On Deck

“The reality is that most manufacturers did not have these capabilities going into the pandemic,” says Ryan Martin, research director at ABI Research. “Yet today technologies like cloud, simulation, and SaaS are viewed as table stakes.”

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SAP’s Thomas Saueressig also has seen an uptick in IIoT plans in the aftermath of the Covid crisis. “Even before the pandemic, manufacturing companies operated in an increasingly volatile environment, requiring them to adapt quickly to shifting priorities,” he says. “Covid-19 accelerated this trend. As consumer demands changed dramatically and manufacturing capacities were constrained, supply chains broke, forcing businesses to cope with the disruption of their daily operations.”

Companies that overcame the challenges of the Covid era were highly digitalized businesses making decisions based on real-time data, Saueressig says. “IIoT technologies played a major role in helping them to repurpose production, provide help where needed, and find alternative routes to maintain supply chains.”

Industrial IoT paves the way for industrial companies to shift from selling products to delivering services and solutions. “The underlying idea of outcome-based models is that customers pay for what they get out of a product rather than for the product itself,” Saueressig says. “IIoT opens the door to a fully personalized customer experience. Data exchange between a customer and a smart factory makes it possible to produce a highly customized product within just a few days — from receiving an order to shipping the goods.”


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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