It’s a Matter of Trust: Using Location Intelligence to Make Utility Data More Accurate…and Drive Efficiency

Can you trust the infrastructure-related data that every aspect of your operations relies upon? Did that transmission line get installed the way your systems say it was? Are those poles located where you think they are? Will your crew find what they are expecting to find when they look inside that junction box or dig up that pipe? Did that subcontractor perform the maintenance the way they were supposed to? Too often the answer to those questions is “no.” Or just as challenging, the answer is too often “maybe?”

The unfortunate reality is that most utilities do not have data they can trust. The infrastructure-related data that is the foundation for their operations is either long out of date, incomplete, inaccurate or full of contradictions. For utilities, the volume of inaccurate data is daunting, given that it involves geographically distributed infrastructure including utility poles, water lines, underground and above-ground cables, vaults, transformers, gas line connections, water pumps, DERs and so much more. These data problems are not trivial. Utility operations rely on this data, not only during normal operational conditions but particularly in emergency situations.

The source of these data problems is not a mystery. Manual, paper-driven processes are the culprit. Utilities GIS systems too often don’t receive accurate information. Or they receive it too slowly. Or the information they receive is incomplete or contradictory. To compound that problem, utilities often have more than one GIS systems in their operations, and those GIS systems often don’t agree. The impact is enormous. Because there is no single body of data that can trusted, and because so many data points are not accurate, teams are forced to make educated guesses about the truth. Even then, the true truth typically isn’t determined until a truck is rolled to evaluate the infrastructure in person. All of this causes massive inefficiencies across the organization, with a lack of trustworthy information paralyzing processes ranging from day-to-day maintenance tasks to high-stakes emergency response efforts.

All of this is despite the best efforts of everyone involved, from the field crew to the GIS departments, who wrestle with these data issues all day, every day. The problem is structural, not a shortcoming by those involved. But there is a solution, and both field crews and GIS teams are the key players in solving it.

By equipping work crews with location intelligence-powered mobile devices, utilities can validate data in the GIS system each time those team members are on a work assignment. Location intelligence applications on these devices capture accurate information before, during and after a work assignment, even when the device is not online. When they first arrive at a site, they use these devices to capture accurate information that on-site and in-the-office team members use to make more informed decisions about the work to be done. Then after the work crew carries out work orders for maintenance or construction, they us utilize the location intelligence applications to re-capture information about the site post-project to ensure that the GIS system accurately captures those changes.

This automated process is far faster, more accurate and more reliable than the manual processes I discussed above. This provides a trustworthy source of digital information that is immediately available to the entire chain of decision-makers involved in that project. It is information they can trust, and information that helps them make better decisions in a far more efficient way.

Day by day, project by project, this enables utilities to make their data steadily more accurate and trustworthy. With every truck that rolls, they are giving every department in the organization a data set that can be trusted more. The benefits are enormous: far more efficient operational processes, including faster progress on implementing work orders, fewer truck rolls to send crews onsite, fewer processes that need to be re-done due to faulty information.