On more than one occasion when I’ve been out for a family walk, my kids have caught me staring at a utility pole with a funny look on my face. “I bet they have no idea that pole is there…and not there,” I’ll be saying to myself, while my kids are no doubt saying to themselves, “My dad is so weird.” Yes, I’m staring at a pole, but what I’m really looking at is a data problem that every utility struggles with. Can the utility trust the information in their operational systems when it says that this pole is here? Can the organization trust the data when it says the neighboring pole is 90 feet away? Can it trust that those underground wires are where they are supposed to be? Which data should it trust when two systems say two different things? Which information is the truth?

This philosophical-sounding question has massive practical importance because so many aspects of utilities’ operations depend on something that is in very short supply: accurate information about the location and status of infrastructure such as utility poles, vaults, circuit length, transformers, DERs, underground cables and more.

That utility pole I was staring at up above caught my attention because it looked like the crew installing it had to make an adjustment on the fly to locate it across the street to work around an obstacle — rather than on the side of the street where all of the other poles were lined up. But there is a high likelihood that the decision never made it accurately into the utilities’ GIS systems, which rely on multiple layers of manual, paper-driven processes to record information. That GIS system likely thinks the pole is 30 feet the other way, doesn’t take into account the additional circuit feed used to reach across the street and back again, and other details that would only be discovered when a truck comes out for a service call and realizes nothing matches the information in their work order.

When you multiply that by all of the infrastructure in a utility’s inventory, which is a massive amount of unreliable information — so much, in fact, that it undermines the trustworthiness of all the data sets. As a result, the GIS teams, operations teams and work crews at utilities do not have a single body of data that they can trust. They often have to interpret multiple data sets across multiple systems to make their best bet about the truth. But even then, so often it is not until a truck hits the road and crews look at a site with their own eyes that there is solid enough information for teams to make decisions. 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.

This data accuracy problem has been an intractable one for decades, but a combination of next-generation technologies and analytical best practices — which provide a foundation for true location intelligence — finally provides a way for utilities to solve this data trust issue. Location intelligence refers to real-time actionable insights from location-based data and analytics that enable organizations to make faster, smarter decisions and solve problems that other technologies cannot address. That includes the pole dilemma and other data trustworthiness challenges that I discussed above, which utilities can now solve with a two-step process driven by work crews in the field.

The first step is to equip work crews with location intelligence-powered mobile devices that can validate data in the GIS system each time they are on a work assignment. That device uses a variety of spatial technologies to make a note of exactly what I saw on that walk with the family: that a pole was across the street from the expected location, that the distance between poles was therefore different than what was in the GIS system, and so on. But rather than requiring a paper-driven process to submit those observations and measurements by hand (requiring a lengthy and perhaps inaccurate process of data entry that may take weeks), the work crew can submit an update to the GIS system in real-time using digital tools that make the process accurate and instantaneous. This provides a trustworthy source of digital information that is immediately available to the entire chain of decision-makers involved in that project. It provides truth where doubt previously clouded decisions, and that leads to faster, better decisions.

The second step is equally important for transforming utilities’ data sets into more trustworthy assets. After a work crew carries out work orders that involve maintenance or construction, they can register the updated information using those same mobile devices to ensure that the GIS system accurately captures those changes. This is a dramatic change from the paper-driven processes that involves hand-written notes and red lines on project paperwork that so often led to erroneous information being recorded, for example, with that pole that I was staring at so intently during the family walk. Using the same mobile devices that work crews use to validate information when they first arrive on-site, they do another round of validation at the end of projects to ensure that there is an accurate picture of the infrastructure entered into the enterprise asset management (integrated with GIS) system before they hop back in their trucks and move on to the next work order.

These two steps use location intelligence-based mobile devices to turn every work crew (including subcontractors) into a “trust task force” that steadily makes utilities’ data sets more accurate every hour of the day. With every truck that rolls, they are giving every department in the organization something they have never had before: a unified data set that is a single source of truth, the whole truth and nothing but the truth.

That leads to enormous efficiencies for electrical utilities. In the case of a crew heading out to conduct a repair, it can lead to multiple efficiencies, including eliminating the need for preliminary visits to visually inspect a site and multiple subsequent sequential steps that involve filing written reports for engineering and GIS teams to review before decisions can be made. Location intelligence makes it possible for those decisions and actions to take place faster, with fewer steps, and less opportunity for confusion or mistakes. But at the macro level, having more trustworthy data and real-time access to updated information enables efficiencies across the entire organization.

In my next article in this series, I will discuss the impact of that on the complex planning, implementation and management process for delivering power to new developments like new neighborhoods, large apartment complexes and other real estate projects. This will provide another view into the way location intelligence can solve complex challenges that also deliver transformative efficiencies.

Editorial Note: This is the first in a series of three articles by Brandon Raso about the impact that location intelligence is having across the operations of electrical utilities. Location intelligence uses next-generation GIS technology and analytics to deliver actionable insights that utilities have not previously had access to. In this first article, Raso discusses how location intelligence transforms location-based data into a reliable, accurate foundation for far more efficient field operations and decision-making.