SyncronTM has announced the launch of Syncron UptimeTM, a new solution offering that uses Machine Learning and Artificial Intelligence to efficiently analyze real-time sensor data, predict failures, prescribe optimized maintenance actions and ultimately maximize product uptime. Servitization, which is the transformation from selling products to selling products-as-a-service, has ushered in a new generation of customers that prefers access over ownership. This increasingly popular consumption preference is driving original equipment manufacturers (OEMs) to shift from product-centric to service-centric business models. "While servitization will enable OEMs to create more customer value and reduce cost, it will also require many to redefine the way they operate and serve their customers," said Henrik Lenerius, Chief Product Officer at Syncron. "OEMs not only need to optimize their traditional, break-fix after-sales service operations, but also future-proof their businesses to meet the customers' evolving consumption preferences. Subscribers expect their equipment to be up and running at all times – putting previously unseen demands on manufacturers' service organizations. The launch of Syncron Uptime, coupled with increasing data-transfer bandwidths (5G), IoT, artificial intelligence and Machine Learning, is paving the way for OEMs to facilitate predictive and prescriptive maintenance, optimize productivity and maximize product uptime more efficiently than ever before."
As new technologies like artificial intelligence (AI) transform organisations across industries, the potential business benefits are a powerful argument to help a business go through the transition. An example of this would be within the ever-evolving nature of the field service industry; companies can now schedule a technician to come and check a network fault or conduct a service call for their customers almost immediately, thanks to AI. This is worlds away from ten years ago when the only option would have been to call and talk to a dispatcher as they flicked through employee logs and schedules manually to find an available, and properly skilled, technician. And often, the right technician required to resolve the issue was generally not available for a week, or longer. For any business, seven days without a resolution is a definite failure.
In the past, manufacturers naturally focused on sales of their products, such as drills or aircraft engines, as standalone offerings. Servicing those products was considered a cost center for those businesses--an expensive, back-end operation required when products failed in the field. Today, the manufacturing landscape has shifted, and servicing now opens the door to better customer outcomes, decreased operational costs and even potential new revenues for manufacturers, as well as an opportunity to differentiate from competitors. As formerly offline tools become connected, and service moves from reactive to predictive, we see the manufacturing sector is moving towards services as a core business model. According to a study of field service organizations by the Aberdeen Group, 26 percent of respondents have been able to generate new service-driven revenue streams1.
"If you don't innovate fast, disrupt your industry, disrupt yourself, you will be left behind." To orchestrate this transformation, organizations must revamp their IT strategies and roadmaps and ingest the value of artificial intelligence and enterprise resource planning (ERP) integration. These technologies go hand in hand because they cover the same spectrum. AI-enabled ERP solutions will by default impact the heart and soul of day-to-day operations. The mix of people, process and technology is going to change.