Predictive analytics can help companies prevent catastrophic equipment problems and save money by operating their machinery more strategically.

Equipment failures occur all the time, but while they typically only impact only a handful of people for a short amount of time, in some settings, outages can have a much broader reach. A recent equipment failure at a plant in Oklahoma caused about 13,000 customers to lose power for several hours in Tulsa, Broken Arrow and Coweta, reported ABC Channel 8 Tulsa. These kinds of outages occur all the time because companies don't have a clear understanding of how their equipment is performing and if they are at risk for equipment failure. 

One way that organizations can be smarter about their equipment monitoring is by collecting and analyzing data about machinery, systems and other equipment. ZDNet's Andrew Nusca explained that new software and sensor technologies can use big data to identify abnormalities, calculate their potential risk and help companies make decisions about how to operate their machinery to avoid slowdowns or failures.

"The ramifications are massive," reported Nusca. "If there's a slowdown (or outright stoppage) in the supply chain, the losses pile up immediately. That's the downside to being extremely fast and efficient: that speed can come back to bite you when the operation goes off the rails."

Nusca explained that there is a large market opportunity for this approach to equipment maintenance, from the upkeep of roads and bridges to electrical grids to automotive facilities. Predictive analytics can help companies prevent catastrophic equipment problems and save money by operating their machinery more strategically.