Companies that develop or support products in the field need to transition from reactive to predictive maintenance and service. Such a transition is possible using ubiquitous connectivity and predictive analytics on machine data. Here’s how.
The pandemic brought to the forefront issues that have plagued companies that develop and support products in the field. Namely, the costs and inefficiencies of sending someone to every site to service those field-based products.
This approach had long been impractical, and with the pandemic locking down site access, it often became impossible. If they have not done so already, companies must transition from reactive to proactive remote maintenance and service to stay competitive, rein in operating costs, and better enable expansion and growth.
Fortunately, enabling technologies through the Internet of Things (IoT) and Augmented Reality (AR), as well as new services (e.g., 5G, LP-WAN, Wi-Fi 6, and more) now enable companies to easily incorporate connectivity and data collection of machine status into their products, for seamless, predictive remote maintenance.
Organizations can use predictive analytics and artificial intelligence (AI) on various data sources from machines in the field to modernize their maintenance and repair operations, reap the benefits of predictive maintenance, and offer enhanced services.
Predictive analytics also allows a company to deliver more insightful intelligence and become more deeply embedded into customer operations.
These are strategic moves that can develop more profitable long-term customer relationships. Such capabilities can also help companies transition to new business strategies, such as moving to recurring revenue or pay-per-use models (versus a one-time purchase).
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