Predictive maintenance helps field service operations get a better handle on whatever’s coming up just down the road. If you’re not familiar with how predictive maintenance can help you, we’ve pulled together a quick cheat sheet to help you get up to speed.
1: Preventive maintenance – checking and making any needed infrastructure repairs on a fixed schedule – has long been the norm for field service operations. But predictive maintenance – anticipating likely breakdowns before they happen – is much more efficient for several reasons, such as eliminating unnecessary site visits that often do little more than confirm that everything is in proper working order.
Learn more about how predictive maintenance can help tackle challenges like the 5G buildout
2: Predictive maintenance is just one of many functions that are part of the purpose-built Zinier platform. Other key functions include scheduling & dispatching and inventory, asset, and work order management.
Dive deeper into how the Zinier platform can address your needs
3: The advent of the Internet of Things (IoT) has created a “tipping point” for many field service operations, opening the door for predictive maintenance and other strategies for reducing breakdowns and repair costs and boosting overall visibility and workplace satisfaction.
Dig in to what the IoT can do for you
4: By automating field service operations, a back-office coordinator can easily support five times as many technicians. By coupling this evolution with solutions that enable predictive maintenance, field service operations can enjoy significant increases in crucial metrics like uptime and availability.
Read more about how automation is changing the field service landscape
5: As companies wrestle with the impact of the pandemic, solutions such as predictive maintenance provide their operations with a healthy dose of much-needed resiliency.
Get the full story of how you can make your operations more resilient
Get a heads up whenever there’s something new on the Zinier blog – follow us on LinkedIn.