How 185-year-old John Deere is embracing digital transformation

by | Aug 1, 2022 | Technology

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John Deere is known for its industrial-grade agricultural, forestry and heavy equipment, as well as its consumer lawn care line. 

But many probably don’t realize that it is also incorporating leading-edge capabilities including AI, computer vision, data analytics, digital twins, sensors, robots and co-bots — proving that 185-year-old manufacturing companies can go through digital transformation, too. 

In June, we reported on how John Deere is using AI to harvest data. At VentureBeat’s Transform 2022 event last week, its CIO Ganesh Jayaram reiterated this and highlighted the other innovative efforts the company is embracing to propel it forward. 

“You can think of that as ‘Industry 4.0,’” John Deere CIO, Ganesh Jayaram, said in a livestream keynote during last week’s Transform 2022. 

Manufacturing at the edge

John Deere’s tech strategy is built around two tenets, explained Jayaram: the public cloud and the edge. 

“There’s a need for both,” he said — it’s just a matter of defining what types of workloads take place where. 

The edge is best for applications with low latency, “where you really don’t have the time to be sending the information back to the cloud.” 

For John Deere, that edge is factory and warehouse operations, said Jayaram. The company is scaling knowledge at the edge and investing in private server networks. 

“We’re trying to drive compute and analytics, leverage intelligence at the edge, as close to the point of impact as possible,” he said. “We want to translate intelligence at the edge so that those applications with high bandwidth and low latency can perform there.”

The manufacturing tech stack

Along with this, Jayaram described an emergent tech stack. The best way to conceptualize that in the manufacturing world is to combine IT and OT, he said — that is, adding manufacturing components to a core IT stack. 

The top layer of this stack combines applications and analytics. Just beneath that is the data platform. Under that are platforms of connectivity and software (enterprise resource planning software, for example). Lastly, hardware and services. …

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