While the more advanced forms of maintenance, predictive and prescriptive, still account for just 23 percent of this year’s market, at the end of the forecasting period they will collectively represent 60 percent of all revenues.
Senior analyst Aapo Markkanen comments, “Today, predictive maintenance is one of the commercially readiest forms of M2M and IoT analytics, possibly second only to usage-based insurance. It helps asset-intensive organizations transform their maintenance operations and eliminate waste, reducing costly downtime. Infrastructure, vehicles, and industrial equipment can all benefit from it.”
Predictive maintenance is being championed by likes of GE, Bosch, plus other large and increasingly software-centric manufacturers, but its key enablers are the technology suppliers that allow customers to employ similar approaches regardless of their OEMs. In the latter group, one can find horizontal analytic vendors of various sizes, ranging from BI giants (SAP, IBM) to agile and fast-moving start-ups (RapidMiner, Blue Yonder). Predikto and Mtell, meanwhile, are examples of vendors specializing in predictive maintenance in certain verticals. Finally, maintenance represents an opportunity for many M2M players to add value to their offerings.
Practice director Dan Shey envisions, “Analytics is where much of the money in IoT will be ultimately made. This means that application platforms like Axeda, ILS Technology, ThingWorx and Xively need to facilitate big data if they want to gain a competitive edge. Mnubo and MachineShop, two recent designed-for-analytics start-ups, will make an interesting comparison on that front. Besides the platforms, some of the IoT-savvier telcos – AT&T and Telefonica, for example – could possibly leverage analytics to move up the stack.”
These findings are from ABI Research’s “Predictive Maintenance Solutions and Strategies” study, which is part of the firm’s M2M Service Delivery Platforms and Internet of Everything Research Services.
Source: ABI Research