OEMs, once limited to managing after-service for their equipment to a break fix model, are hopeful that artificial intelligence (AI) Manufacturers are moving in a new direction, throwing away the reactive model in favor of one that is proactive and focuses on maximizing machinery uptime.

“Maximizing product uptime is a critical milestone in a manufacturers’ journey to servitization,” said Gary Brooks, CMO of Syncron. “This research illustrates manufactures’ desire to close the gap between their customers’ growing expectations and what their after-sales service organizations can deliver today.  It’s exciting to see a growing group of industry-leading manufacturers completely reexamine their after-sales service operations and take the necessary steps to evolve from break-fix service models focused on repair execution, to a new paradigm focused on dynamic repair prevention and maximizing product uptime.”

This week, Syncron, a provider of cloud-based after-sales service solutions, released research titled “Maximized Product Uptime: The Emerging Industry Standard,” that finds that most manufacturers are on the cusp of investing in predictive analytics, machine learning, and artificial intelligence technologies. The study, which was done in conjunction with Worldwide Business Research (WBR), polled 300 decision makers including both OEMs and end users and found that this push toward technology adoption is being driven by customer’s demands for manufacturer’s ability to guarantee and deliver equipment uptime.

This points to the move toward servitization, in which manufactures sell the performance of their products as a service rather than selling the product itself. Intrinsically, this move puts the responsibility for maintaining the equipment squarely back with the OEM—and it addresses the demand from customer to be freed from the cost and complexity of equipment ownership. “The drive to servitization is a reaction to the customer sentiment of ‘I want it when I need it, I only want to pay for it when I need it and when it breaks, I want it to be someone else’s reasonability,’” Brooks told EBN.  “On-demand is driving massive change to the OEMs business model.

To meet these expectations, after-sales service efforts must become an intelligent part of the OEMs value chain that now stretches from design and procurement throughout the lifecycle of the product.  Today, 82% manufacturers report that product uptime plays into customer buying decision, while 57% of end users report they would pay extra for an uptime guarantee.

Currently, in terms of maximizing product uptime, there is a gap between what manufacturers offer and what customers expect.  In fact, nearly all end users said they want OEMs to offer service agreements that promise uptime. Eight out of ten indicate that predicting parts failures before they occur are extremely important. However, only one third of OEMs actually offer this type of service contract today.

“Today’s manufacturers are well aware of their need to evolve their after-sales service functions to meet their customers’ increasing demands for maximized product uptime,” said Sara Mueller, Field Service Portfolio Director at WBR.  “While a growing list of industry leaders take steps to implement the appropriate systems, technologies and resources to meet their customers’ evolving service expectations, the laggards reject the need for change and cling to the ‘status quo’ break-fix service model.”

Currently, most OEMs are gathering data from sensor-equipped products in the field—a key requirement for predictive maintenance. However, only 25% are currently using the data to support their service efforts. More than half of OEMs plan to make AI and machine learning a major investment, while 90 percent intend to invest in predictive analytics within the next 12 months.