“What’s Where, and Who Cares?”
That simple line from my favorite geography professor has always stuck with me. In utilities, the “what’s where” is straightforward: assets and the features that support them. The “who cares” is everyone beyond GIS—engineers, designers, operators, planners, construction, regulators, finance, and the list goes on and on.
As many organizations migrate from the geometric network to the ArcGIS Utility Network model and Network Management, there’s a temptation to design mainly for GIS teams. But the real value of this data is to support decisions made outside GIS. Those one-off spreadsheets and shadow systems that IT hates so much? They exist because the core GIS hasn’t met users’ needs. The Utility Network may not be everything to everyone, but if you include the right stakeholders in data modeling sessions ahead of migration, you’ll avoid blind spots and make the data much more useful to the entire organization.
When properly modeled and supported by good data, the Utility Network empowers utilities to perform condition-based asset maintenance, resulting in cost savings, reduced risks, improved capital planning, and better alignment with regulatory compliance. This article explores the work plan management capabilities of the Utility Network and presents data modelling considerations specific to electric transmission utilities aiming to maximize their data transformations.
The Reality in Electric Transmission
Transmission owners don’t just build new lines. They maintain, refurbish, and replace thousands of miles of structures, conductors, and substation equipment. The biggest spending decisions happen in lifecycle planning: whether to rebuild or refurbish, where to harden against wildfire or flooding, and which aging paths to upgrade for capacity or reliability, all while balancing the delicate dance between Capital and Operations and Maintenance (O&M).
Data needed for these decisions is often fragmented. Condition assessments sit in inspection tools, costs are managed in Enterprise Resource Planning (ERP) systems, planning constraints are tracked elsewhere, and GIS shows only location. When properly modeled, the Utility Network offers a way to weave these strands together, so you can evaluate projects based on system impact, not just age.
Where ISO 55000 Fits
While not all US utilities follow the International Organization for Systems (ISO), an organization that sets international standards, many follow the spirit. ISO 55000 is the international standard for asset management. ISO 55001 lists the certifiable requirements, while ISO 55002 gives guidance on how to meet them. At its core, ISO asks you to deliver value through assets across their lives, manage risk, use reliable information, and prove that your system works and improves over time. This is valuable for utilities to follow because it provides a structured and defensible framework for managing complex, high-value infrastructure transmission networks. Additionally, it can unlock financial and operational benefits, such as lower insurance premiums, reduced revolver interest rates, and improved supply-chain pricing for planned transformer replacements.
The Utility Network can provide practical evidence for that system. Your asset register is expressed through asset groups, types, containment, and associations. Your risk method appears in fields for condition and consequence, polygonal boundaries that highlight transmission line sections at risk, and in trace results that quantify customers or megawatts affected. Information quality shows up in attribute rules, validation, versioning, and editor tracking. None of this is paperwork. It is a working process that aligns with ISO 55001 in a way both auditors and executives can understand, while also strengthening reliability-centered maintenance, condition-based maintenance, and predicted-through-fault-centered maintenance approaches.
Turning the UN into a Decision Engine
A transmission model is only as good as the data feeding it. A strong model typically includes spans with the following attributes: conductor type, install year, clearance findings, fault counts, LiDAR vegetation clearance, and sag or tension class. Structures should carry material, foundation type, corrosion class, inspection date, and defect counts. These attributes are crucial for turning asset data into actionable intelligence that supports engineering, maintenance, and investment decisions. Exposure layers for wildfire, flood, coastal, or critical crossings add context. On top of that, trace results for downstream megawatts and critical site counts help quantify consequence, while fields for unit cost and mobilization allow you to calculate net replacement cost.
While inspection and asset systems may store similar attributes, modeling them within the Utility Network allows these values to participate in network traces, spatial analyses, and consequence scoring—something external systems can’t inherently perform.
Condition Data
When you treat condition data as first-class information in the Utility Network, you’re elevating it to the same level of importance as location, connectivity, or asset identity. In practice, that means things like corrosion class, inspection results, SF₆ leak rates, or breaker operation counts aren’t buried in notes fields or external spreadsheets—they’re modeled, validated, and maintained as part of the authoritative system of record. When condition data is treated this way, it can support tracing, risk scoring, work prioritization, and downstream systems like enterprise asset management (EAM), outage management system (OMS), and analytics tools.
To take full advantage of this in the Utility Network, utilities should consider the following data-modeling suggestions:
- Establish a standardized attribute schema for all condition indicators (e.g., corrosion class, inspection frequency, defect rating, and asset health index).
- Use coded value domains and lookup tables to ensure that condition scores remain consistent across inspectors and asset types.
- Include temporal fields (inspection date, next-due date) so the data model can support lifecycle analytics and trend tracking.
- Relate condition features to their physical assets using containment or structural associations, so inspection and device data are traceable to the right network elements.
- Plan for data refresh cadence and integration with external inspection systems to keep condition fields current.
Traces
Traces allow you to measure consequence, not just connectivity. With a few saved configurations, you can calculate megawatts downstream from a given line or breaker, count the number of critical facilities such as hospitals or water plants, and overlay exposure zones like wildfire, floodplain, or river crossings. At a bare minimum, you must accurately model connectivity by ensuring every conductor, device, and subnetwork is properly connected with valid terminal configurations and network rules.
Data-modeling suggestions for setting up traces include:
- Store load or customer data at the correct network level (e.g., substation, feeder, or service point) so trace results yield meaningful megawatt values.
- Tag or classify critical customers (e.g., hospitals, water plants, emergency centers) in GIS attributes or related tables so they can be counted automatically in consequence traces.
- Incorporate spatial overlays by maintaining current hazard and exposure layers (wildfire zones, floodplains, seismic corridors) as separate feature classes linked through geometry or ID relationships.
- Define and save trace configurations with consistent parameters (stops, barriers, output fields) to produce repeatable, defensible results.
Cost Data
Finally, you can align cost data with how your organization actually builds: unit costs by asset type, bills of materials, mobilization rates, and bundling benefits.
Your data model can focus on:
- Including cost-related fields in the Utility Network schema (e.g., unit cost, mobilization multiplier, project bundle ID) and ensure units of measure are standardized.
- Mapping asset groups/types to energy resource planning (ERP) cost categories so GIS features correspond directly to financial and work-management systems.
- Designing the model to support aggregation—allowing costs to roll up from individual spans and structures to projects, corridors, or substations.
- Using domains or reference tables to keep unit cost libraries current and auditable.
- Considering rule-based calculations (Arcade Attribute Rules or Python Notebooks) to compute total replacement cost or compare build vs. refurbish scenarios.
Getting Started
Thinking of Utility Network as a decision engine—not a data conversion project—changes how transmission organizations plan their transformations. Building this engine successfully requires planning before any migration tasks take place. With the right stakeholders at the table and the right attributes modeled from the start, utilities can create a system that aligns decisions, data, and strategy.
Contact UDC to learn how you can maximize your digital transformation and read about our Utility Network services and solutions. Look for Part 2 of this series, where we’ll explore how to turn these concepts into actionable data with an operational Priority Index using condition, consequence, and cost.