A survey of more than 3,000 companies by Forrester Research found that more than half were either already using or planning to adopt industrial internet of things applications to improve how they operate and interact with customers.

Kaeser Compressors Inc., minimizes downtime of its industrial air compressors by building into the machines sensors and software that report back when maintenance or a replacement is required. That kind of internet of things, or IoT technology has enabled it to operate with a new business model: Providing its machines to customers for no cost other than paying for the actual compressed air they use.

Kaeser Compressors, the Fredericksburg, Va.-based U.S. arm of Germany-based Kaeser Kompressoren SE, is using a system of IoT sensors and machine-learning software that monitors how its machines operate under various conditions on each customer’s site, and can predict when they need maintenance or a replacement part. The system automatically sends Kaeser an alert when necessary to schedule service, reducing or even eliminating downtime.

Kaeser’s “customers can now opt to consume compressed-air-as-a-service, only paying for the air they use,” Forrester Research Inc. says in a report released last week. “Kaeser absorbs the capital cost of the machines and commits to their delivery, upkeep and maintenance. It’s in Kaeser’s interests to build a robust product, to actively monitor those products in the field, to predict failures and minimize customer downtime, and to optimize the efficiency of service visits.”

Kaeser is just one example Forrester cites in the report, which covers the trend of industrial companies deploying some form of industrial internet of things technology to improve their operations and better interact with customers. The report, “Put Data to Work in the Industrial Internet of Things,” was authored by Paul Miller, a senior analyst for information technology, and other Forrester analysts.

Forrester surveyed 3,289 industrial companies of various sizes, and found that 25% were already using machine-learning IoT applications, and 27% were planning to deploy them. Another 27% expressed interest in adopting some form of IoT system. Machine learning with IoT systems occurs when the equipment that companies operate use software to compile and analyze data on machinery operations, producing reports revealing how well the machines perform and alerting operators when attention is needed to maintain top operating condition.

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In a complementary report also released last week—“Untangle Your IoT Strategies,” by vice president and IoT analyst Frank Gillett and other Forrester analysts—Forrester advises companies that use IoT technology to take a hard look at how they interact with their customers, then “work back into internal operations” to see how IoT sensors and related software can identify voids in customer service. An IoT system gathering information from sensors in a fulfillment warehouse as well as information on customer orders, for example, could reveal better ways for warehouse workers to arrange high-volume products for faster and more efficient fulfillment of orders.

“Start with customer-facing processes, such as customer service or order fulfillment, to explore ways to improve revenue and profits,” the “Untangle Your IoT” report says. “With that customer-first focus, you’ll be in a better position to ensure the IoT solutions you pick can deliver improved revenue as well as cost savings.”

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