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Manufacturers need to break their dependence on just selling products to selling services if they’re going to grow. Smart, connected products with IoT sensors embedded in them are the future of subscription business models and a key foundation of the subscription economy.<\/p>\n
In a subscription economy world, whoever excels at product reliability and uptime grows faster than competitors and defines the market. Airlines with the highest on-time ratings have designed in reliability and uptime as part of their company’s identity; their DNA is based on these goals. Worldwide Business Research (WBR)<\/a> in collaboration with Syncron<\/a>, a global provider of cloud-based after-sales service solutions focused on empowering the world’s leading manufacturers to maximise product uptime and deliver exceptional customer experiences, recently surveyed to see how manufacturers are addressing the reliability and uptime challenges so critical to growing subscription business.<\/p>\n The research study, Maximised Product Uptime: The Emerging Industry Standard<\/a> provides insights into how manufacturers can improve their after-sales service solutions. A copy of the study can be downloaded here<\/a> (PDF, 23 pp., opt-in). Please see pages 20 – 23 for additional details on the report’s methodology<\/a>. WBR and Syncron designed the survey to gain a deep understanding of manufacturers’ ability to deliver on their customers increasing demand for maximised product uptime, surveying 200 original equipment manufacturers (OEMs), with respondents evenly split between the U.S. and European markets, as well as 100 equipment end-users<\/p>\n Key insights from the study include the following:<\/p>\n 39% are planning to have one in two years, and 22% are predicting it will be in 2020 or later before they have on in place. Capgemini<\/a> found that manufacturers’ plans for smart, connected products would extend beyond these projections, making it a challenge of manufacturers to realise the new subscription revenue they’re planning on in the future.<\/p>\n 51% of manufacturers have systems in place for analysing the inbound data generated from sensors, yet report they still have more work to do to make them operational. The 25% of manufacturers with systems in place and at scale will have at least an 18-month jump on competitors who are just now planning on how to make use of the real-time data streams IoT sensors provide.<\/p>\n Autonomous product operation (56%) and implementing stronger analytics on ROI ( 50%) are also extremely important. These findings further underscore how manufacturers need to design in reliability and uptime if they are going to succeed with subscription-based business models.<\/p>\n Creating meaningful data models from the massive amount of manufacturing data being captured using automated sensors and IoT devices is making predictive analytics, AI and machine learning extremely important to manufacturers’ IT planning budgets for 2019 and beyond. Combining predictive analytics, AI and machine learning to gain greater insights into pre-emptive maintenance on each production asset, installed product or device is the goal. Knowing when a machine or product will most likely fail is invaluable in ensuring the highest uptime and service reliability levels possible.<\/p>\n34% of manufacturers are ready to compete in a subscription economy and have created a service strategy based on maximised product uptime<\/strong><\/h3>\n
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<\/a><\/p>\n71% of manufacturers are using automated sensors including IoT for real-time monitoring and data capture of a product’s condition and performance, yet just 25% have the infrastructure in place to analyse it and maximise product uptime<\/strong><\/h3>\n
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<\/a><\/p>\nPredicting part failures before they occur (83%), optimising product functionality based on usage (67%), and using stronger analytics to evaluate product performance (61%) matter most to manufacturers pursuing subscription models<\/strong><\/h3>\n
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<\/a><\/p>\n91% of manufacturers are investing in predictive analytics in the next 12 months, and 50% consider artificial intelligence (AI) a major planned investment for 2019<\/strong><\/h3>\n
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