Five Ways Utilities Can Make Better Decisions with the Data They Already Have

Utilities have invested billions in grid modernization over the past decade. In 2023 alone, U.S. utilities spent more than $50 billion on distribution infrastructure, according to the U.S. Energy Information Administration. Yet many control rooms still struggle to translate growing volumes of operational data into better decisions.

Many modernization efforts focus on deploying sensors and data-generating systems with the expectation that greater visibility would improve operations. Instead, operators often face alert overload, fragmented systems, and data that lacks context. During major events, hundreds or even thousands of alarms can appear within minutes. Without tools that correlate these signals, operators must manually sort through alerts, pushing utilities into reactive operations rather than faster, more informed decision-making.

The following five practices can help utilities translate existing data into meaningful operational intelligence.

1. Unify Operational Data Across Systems

Most utilities rely on dozens of operational platforms, including SCADA, outage management systems (OMS), GIS, AMI head end systems, asset management tools, and weather feeds. While each provides valuable insight into grid conditions, these systems often operate independently. As a result, operators must move between multiple screens to piece together what is happening across the network. This fragmentation slows decision-making and increases the risk that critical information will be missed.

The impact becomes especially clear during major grid events. During Tropical Storm Isaias in 2020, for example, PSEG Long Island’s outage management system failed, forcing operators to revert to an older platform and slowing outage tracking and crew dispatch. Creating a unified operational data layer that aggregates key data streams can help utilities establish a single operational view of grid conditions without replacing existing systems.

2. Reduce Alert Saturation Through Event Correlation

As utilities deploy more sensors and monitoring tools, the number of alerts entering control rooms continues to grow. Line sensors, AMI meters, weather feeds, distributed energy resources, and cybersecurity systems all generate alarms. During storms, thousands can appear in rapid succession.

Without intelligent filtering or correlation, operators may be forced into reactive triage. Staff must review alarm lists, suppress duplicates, and attempt to identify the root cause among many secondary alerts. This cognitive overload slows response times and increases the risk that important signals will be overlooked.

Utilities can address this challenge by correlating alerts across multiple operational data sources. When telemetry, outage data, and grid topology are analyzed together, systems can group related alarms into a smaller number of meaningful operational events.

Instead of reacting to hundreds of alerts, operators can focus on a unified and manageable set of prioritized incidents.

3. Add Context to Operational Data

Raw data rarely answers the most important operational question: what action should the operator take next? Voltage readings, outage notifications, weather inputs, and asset telemetry all provide useful signals. However, when these signals remain isolated, they often fail to explain what is happening across the broader network.

 Operational intelligence emerges when data is interpreted within the context of grid topology, asset condition, and historical patterns. For example, a voltage anomaly may represent a minor fluctuation or an early indicator of a feeder overload. Without contextual analysis, operators must rely heavily on experience to determine the appropriate response. By combining telemetry with asset models, topology information, and historical behavior, utilities can convert raw data into insights that guide operational decisions.

4. Move Beyond Monitoring to Predictive Operations

Many utilities still operate primarily in a monitoring mode. Monitoring systems provide visibility into what has already happened or what is currently occurring on the grid. While this improves situational awareness, operations often remain reactive.

Predictive operations go further by identifying potential risks before they become incidents. By analyzing telemetry alongside weather forecasts, asset conditions, and historical performance data, utilities can anticipate failures and reliability issues earlier. The key difference is not the amount of data collected. It is whether systems can transform data into forward looking operational guidance that enables operators to act before disruptions occur.

5. Align Organizations Around a Shared Operational Model

Technology integration is a challenge, but organizational alignment is often the larger barrier. Utilities typically divide responsibilities across IT teams, operational technology groups, and grid operations staff. Each group tends to describe the grid differently. OT systems organize information around devices and telemetry. IT teams focus on data structures and applications. Operations teams think in terms of feeders, switching procedures, and restoration workflows.

Utilities that successfully deploy operational intelligence initiatives often align these groups around a common grid model. When teams and systems reference the same operational structure, data integration becomes easier, and decision-making improves.

Preparing the Grid for a More Dynamic Future

As distributed energy resources, electrification, and EV adoption continue to grow, grid operations will become increasingly dynamic. Utilities must manage conditions such as reverse power flows, voltage instability, and rapid load fluctuations. These changes require faster decision-making and stronger situational awareness inside the control room.

The next phase of grid modernization will not be defined by collecting more data. It will depend on giving operators the tools and context they need to understand what the grid is likely to do next. Utilities that focus on transforming their existing operational data into actionable intelligence will be better positioned to maintain reliability and manage the complexity of the modern power system.

 As CTO of Delta Energy, Everardo Camacho brings over fifteen years of experience architecting and deploying distributed, internet-connected systems at an industrial scale. In previous roles, Everardo led the development of mission-critical infrastructure for the U.S. Department of Defense and the National Science Foundation. Connect with him on LinkedIn.