Why utilities need structured intelligence, not just data

Posted: December 02 2025

Over the past decade, utilities have invested heavily in enterprise data lakes designed to collect and store massive volumes of data from AMI, SCADA, GIS, CIS, and IoT systems. These enterprise repositories are valuable for business intelligence and cross-departmental reporting.

But when it comes to operational decision-making, data lakes often fall short.

Why? Because storing data isn’t the same as understanding it.

When engineers need to trace a voltage anomaly from a customer meter back through the transformer and feeder to a substation event, the answer doesn’t live in a flat dataset. It lives in the relationships between those assets, their changing configurations, and the operational context of each reading.

This kind of insight requires more than just access to data; it demands a clear operational objective and a model that reflects how the system actually functions. Whether you’re supporting real-time network operations, complying with FERC 2222, or transitioning from a Distribution Network Operator (DNO) to a Distribution System Operator (DSO), your analytics solution must be operationally centric, not IT centric.

Context is the core of network intelligence

PowerRunner on AVEVA^TM PI System^TM isn’t just a place to store data; it’s a system that understands the meaning and relationships of the data it manages.

At its foundation, PowerRunner on AVEVA^TM PI System^TM contextualizes every incoming measurement from smart meters, sensors, and SCADA points within the network model, incorporating asset and customer attributes. This means every voltage, current, or flow reading is automatically tied to:

• its parent transformer, feeder, and substation;
• the correct phase and topology configuration (including as-built and as-operating states);
• and the operational and business attributes that define its behavior and purpose (Including customer class, rate class, solar, EV, and location).

This governed, network-aware model transforms raw data into actionable intelligence — enabling analytics that reflect how the grid truly operates, not how a table organizes it.

“We're moving from the haystack mentality — where all of our devices are in a haystack and we're trying to find the needle — to where [PowerRunner on AVEVA PI System] is actually presenting you the needle that says, ‘here’s the needle, go do something with it.’”

– Senior Engineering Solutions Specialist at ComEd
 Watch ComEd’s full presentation

Operational analytics that scale

Many utility data lake projects begin with good intentions, centralizing data to support analytics and innovation. But in practice, they often evolve into bespoke data science projects: complex, resource-intensive, and slow to scale. Each new use case (whether it’s feeder balancing, voltage optimization, load forecasting, etc.) requires custom pipelines, scripts, and transformations.

PowerRunner on AVEVA PI System takes a different approach. Because relationships between assets, telemetry, and topology are pre-modeled and governed, many use cases become straightforward – often “just arithmetic”. Calculating feeder losses becomes a traversal and aggregation, not a data engineering project. Once data is structured within the operational model, engineers can derive new metrics, run validations, or deploy AI-driven forecasts – all without rebuilding the entire data flow.

Examples of operational analytics made simpler:

• Identifying overloaded transformers using meter and SCADA data
• Calculating system losses by feeder or zone 
• Detecting topology errors or phase misalignment automatically
• Feeding accurate, structured data to machine learning models for forecasting or asset health

This approach accelerates time to insight and reduces dependency on custom code. PowerRunner on AVEVA PI System has helped customers cut engineering review time by up to 90%.
 

Complementing the data lake with network-aware data

While enterprise data lakes remain foundational for reporting and long-term storage, they aren’t designed for real-time operational insights. PowerRunner on AVEVA PI System bridges that gap, integrating with the data lake to deliver contextualized data that reflects the live state of the grid or network.

By feeding governed, validated data – instead of raw telemetry – into the lake, PowerRunner on AVEVA PI System transforms the lake from a passive repository into a reliable source of operational intelligence, so it’s ready to support forecasting, AI, and decision-making.

Want to see how this works in practice?

Watch PowerRunner’s AVEVA World presentation to learn how utilities like UK Power Networks and EMACSA are using structured intelligence to overcome legacy system limitations.

Bridging the gap between IT and operations

Utilities don’t need more data analysts to wrangle data; they need data that understands itself.

With PowerRunner on AVEVA PI System, you bring operational context, temporal awareness, and governance to the forefront, transforming disconnected datasets into a coherent, actionable model.

In doing so, you bridge the gap between IT-driven data strategies and the real-world needs of engineers, operators, and planners delivering the true value of analytics—insight in context.

Explore PowerRunner on AVEVA PI System’s operational intelligence capabilities.