If you want to reinvent the service supply chain, why not just turn the whole thing on its proverbial head? That’s what Minnesota software company Verisae is trying to do.

The company is spending plenty of time with predictive maintenance, figuring out and refining how to detect and avert equipment problems before they happen. And while no system is perfect, this one seems to have enjoyed plenty of early success. “We’ve hooked up 70,000 pieces of equipment” for one of our British customers, CEO Jerry Dolinsky says, “and we’re now getting that data and predicting a day to 10 days before that equipment could have possible failure.” Pretty good window, and it should get better, especially with more and more information from which to cull, and lower and lower costs.

“With the advent of the cost of technology coming down, to deploy devices to sensors to take alarms and telemetry data, we built a … closed-end loop,” Dolinsky says. “We take big data in, and” — by basically automating the workflow — “we make big data small.”

Big data, sensors, and plenty of algorithms are big parts of the process. The supply chain itself, though, is at the heart. “If I’m XYZ company and I’m buying this piece of equipment from this manufacturer,” Dolinsky says, “what I’m demanding right now is that uptime of that equipment should be 100%. Because if the machine is smarter and has the ability to send data and predict when it will fail, then why would it ever fail? … The other thing I’m demanding is that I no longer want to see the brochure for maintenance costs and efficiency. Just guarantee it. It’s allowing buyers to be much smarter with the data.”

The three primary scenarios — and your equipment probably falls under one of these wide umbrellas — are break fixes, where equipment is broken and needs to be fixed within a certain time period; planned preventive maintenance; and new installation or replacement. Those are allowing end users to redefine “the way they look at things, service things, do business. That’s the most exciting thing, and we see it on all sides of the supply chain.”

Companies are “getting smarter,” Dolinsky says, “and they’re building smarter equipment that sends them data, and they’re using different solutions to change the way they do things.”