The modern distribution grid is managing a level of complexity that traditional data structures may not fully accommodate. From wildfire risks to the proliferation of behind-the-meter assets, utility leaders could face a data quality crisis that directly impacts grid resilience. When GIS, outage management, and DER registries maintain conflicting interpretations of the network, response times can slow and operational risks can rise. Transitioning to a Common Information Model (CIM) can provide the shared semantic framework needed to bridge these gaps, to help ensure that as-built data and real-time connectivity finally stay in sync.

Across many systems, critical operational platforms maintain their own data structures and interpretations of the network. Over time, these differences may create friction—slowing updates, complicating integrations, and obscuring a unified operational view. Against this backdrop, utilities should take a closer look at CIM.

The cost of systems that don’t speak the same language

Most utilities already gather the data required to strengthen reliability and operational awareness. But much of this data is produced and stored by systems that were not designed to work together. Each platform—such as GIS, ADMS, outage management, meter systems, and DER registries—represents equipment and connectivity in different ways.

Frequent changes in field conditions can make it difficult for platforms like GIS and ADMS to stay aligned. Switching activity, maintenance work, and device replacements can introduce discrepancies that slow operational workflows and reduce confidence in system outputs. When upstream data is inconsistent, even advanced platforms such as ADMS may struggle to deliver their intended value, underscoring the need for a standardized model utilizing CIM.

This fragmentation appears in familiar operational gaps:

• GIS typically contains detailed as-built information about grid assets, but it is not designed to represent real-time connectivity.
• ADMS captures connectivity and switching states, yet it often lacks the attributes and field details maintained in GIS.
• EAMs typically contain as-built data but no connectivity or spatial information.
• In many cases, meter systems provide customer usage and status data but do not show how those customers connect within the physical network.
• DER registries record where devices have been approved or installed, although they usually do not reflect how those devices influence circuit conditions.

CIM creates a shared standard for representing grid assets and connectivity. With a shared structure in place, utilities can expect to spend far less time reconciling data and more time applying it.

For operations teams, the benefits of standardization can translate directly into improved workflows:

• Faster and more reliable mapping of DERs to substations
• More reliable switching order validation
• Clearer outage triage
• Better-informed event response

A common language for describing the grid

CIM presents a shared semantic model for describing equipment, connectivity, and operational data, enabling consistent representations of assets and network relationships across systems. It also defines the structural model that supports these representations, specifying consistent models for grid assets and connectivity across platforms thereby creating a shared foundation for interpreting and exchanging operational information.

The Common Information Model is not a database or a software platform. It functions as a blueprint layer that any tool can interpret, enabling data to move more freely among systems.

What international utilities can teach us about CIM in practice

While CIM adoption is still emerging in the United States, several international utilities offer clear examples of how a common data structure can improve grid visibility and customer transparency. In the U.K., distribution operators have used CIM to publish open network data, giving customers, developers, and third parties better visibility into available capacity and planned upgrades.

Across parts of Europe, some multi-utility providers have used CIM to support more advanced operational modeling. In these environments, CIM helps to enable creation of digital twins that reflect how electric, gas, and telecom infrastructure interact, fostering more coordinated planning in shared corridors and complex urban settings. While few U.S. electric utilities operate across multiple domains, these projects show that CIM can scale to support large, multi-system environments when needed.

Why operational leaders are taking a fresh look at CIM

Increasing demands on grid visibility

Operational demands are shifting quickly, and many utilities are finding that traditional data structures no longer keep pace. The rapid growth of DERs can intensify the need for real-time visibility from the substation to behind the meter. Leaders need clearer insight into the impact of new devices on loading and reliability.

Heightened resilience expectations

Wildfire management and broader resilience planning can depend heavily on integrated modeling. Utilities need to increasingly combine data from vegetation, weather, grid assets, and customer devices to understand evolving risks.

Growing interest in digital models

Digital twin models rely on accurate, connected representations of the network. CIM supports this need by defining consistent representations for assets and connectivity across systems.

A low-risk framework for CIM implementation

CIM adoption does not require a system overhaul. Utilities can begin within the systems they already rely on by introducing more consistent structures where they will have the greatest operational impact. A key early step is to identify priority use cases—often visibility gaps or recurring integration challenges—and determine where a shared data model could remove friction.

Teams can then map current data sources and pinpoint areas where inconsistent definitions slow down operational workflows. Even a small, well-chosen CIM-informed initiative can demonstrate value quickly. Examples include creating more consistent representations of feeder-level DER data or improving the alignment of information shared between GIS and ADMS.

The goal is steady progress toward higher data maturity, not a large-scale system replacement. By starting with targeted improvements, utilities can build momentum and create a foundation that supports more connected, data-driven operations over time.

Positioning for the next era of grid operations

As the grid evolves, the ability to connect information across systems will become as important as the data itself. CIM provides a practical foundation that enables utilities to use existing platforms more effectively. The most successful early adopters treat CIM as a way to prepare for expanding DER portfolios, rising resilience expectations, and more data-intensive operational models.

Small, targeted steps can reveal where a shared model adds measurable value and highlight areas where deeper alignment will pay dividends over time. These improvements help build a data environment that supports current priorities and the innovations shaping the grid’s future.

About the Author

Stephan Segraves is a Senior Manager in Logic20/20’s Grid Operations practice, where he advises utilities on modernizing operational platforms and data foundations to support a more complex, distributed grid. He brings more than a decade of experience leading mission-critical energy and utility solutions, spanning DERMS, EAM, outage management, network modeling, and large-scale systems integration. Known for translating complex operational challenges into practical, scalable solutions, Stephan works closely with utility leaders to strengthen reliability, visibility, and decision-making across grid operations.

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