The Blind Spot in Your Meter Data

Utilities have spent years making AMI data more accessible and more useful across the enterprise. Usage data feeds customer portals. Outage events flow into operational systems. Load profile data supports forecasting and analytics. Meter data that was once primarily collected for billing has become a valuable source of insight across the business.

But there may be an important gap in that enterprise view: some of the utility’s largest customers.

Large commercial and industrial (C&I) customers often have metering requirements that differ from the rest of the customer base. They may require greater meter accuracy, connections to SCADA, different types or granularity of load profile data, or other capabilities that a utility’s standard AMI fleet does not provide. As a result, utilities often rely on specialized non-AMI meters and systems such as Itron MV-90 to collect, validate, and store that data.

There are good reasons for this architecture. The problem is what can happen next.

As utilities have expanded the use of AMI data across the enterprise, C&I meter data has often remained comparatively isolated. Access may be limited to a small group of users, integrations may exist only for specific operational or billing needs, and only a fraction of the available data may reach the wider business.

Historically, that may have been enough. If billing received what it needed, SCADA received what it needed, and load forecasting received what it needed, the data was doing its job.

But the job of meter data is changing.

Leading utilities are increasingly looking to their data to answer bigger questions about their customers, their loads, and the future of the grid. Where and when is demand growing? What is driving system peaks? How are customer usage patterns changing? Where could new load create capacity constraints? What opportunities exist for new rates, demand response programs, or other customer offerings?

Answering questions like these requires more than a good view of the customers connected to AMI. It requires a good view of the entire load base.

And that is where treating C&I meter data as a separate category can become a blind spot. Large C&I customers may represent a smaller number of accounts, but their loads can be significant. If their interval data remains outside the broader analytics environment, utilities risk making enterprise-level decisions with an incomplete picture of what is happening across their system.

The answer isn’t necessarily to replace MV-90 or eliminate the specialized systems supporting C&I metering. Those systems exist for a reason and continue to perform important functions.

The system can remain specialized. The data doesn’t have to remain siloed.

That distinction matters. Instead of organizing the utility’s analytics strategy around where data happens to originate, utilities can begin with the business question they are trying to answer and bring together the data needed to answer it. Residential AMI data, commercial data, large C&I interval data, and other relevant sources can all contribute to a more complete enterprise view.

That shift—from system-centric thinking to data-centric thinking—opens the door to more comprehensive load forecasting, demand and peak analysis, customer insights, rate analysis, electrification planning, anomaly detection, and grid and capacity planning. More importantly, it allows utilities to extract greater value from data they are already collecting.

Utilities have invested heavily in making AMI data available beyond the systems that collect it. It may be time to apply the same thinking to C&I.

Because the question shouldn’t be whether meter data came from AMI, MV-90, or somewhere else.

The question should be: What could your utility learn if all of its meter data were available to the business?