De-risking Risk: PG&E’s Strategic Asset Management Plan

Electric utility operations and maintenance requirements are more complex than ever, yet the tools supporting operations and maintenance are, in parallel, enabling leading utilities to stay ahead of the curve. This is where Enterprise Asset Management (EAM) and Asset Investment Planning (AIP) solutions have become invaluable.

Addressing Complex Risk with Integrated, AI-driven Asset Management

At Pacific Gas and Electric Company (PG&E), recent developments from IFS and IFS Copperleaf highlight a powerful trend toward integrated, artificial intelligence-driven asset management that promises to transform the utility industry and other asset-intensive enterprises.

Few U.S. investor-owned utilities have more mileage of high-voltage transmission lines than PG&E, and few have been putting in as much planning effort and sophisticated risk analysis effort as PG&E has.

PG&E’s well-documented Asset Management Plan (AMP) is made up of a constellation of highly detailed plans, including an Asset Data AMP. In parallel, PGE& has been making investments for distribution line undergrounding and system upgrades to reduce the risks associated with the thousands of miles of distribution assets the company owns.

Like other utilities, PG&E has been seeking to optimize its efforts to enhance safety, mitigate risks, and ensure ongoing performance excellence, all while navigating an increasingly AI- and data- driven digital landscape.

PG&E's strategic approach to asset management is a prime example of this shift. The company’s Asset Data AMP outlines a comprehensive strategy for managing electric asset data to improve safety and operational efficiency. This plan is part of the company’s "True North Strategy" 10-year plan and is complemented by eight other AMPs that focus on physical assets.

Smarter grid planning and complex risk assessments at PG&E are driven by a collaborative and agile approach, where cross-functional teams use an integrated platform to optimize investments and ensure system safety.

A key component of this strategy is the System Needs Analysis Platform (SNAP), which is built on Palantir Technologies Foundry and integrated with IFS Copperleaf. This platform is designed to rethink grid planning and optimize multi-billion-dollar investments by providing a clear, scalable path forward.

Pilot results demonstrate strong alignment with utility executive priorities, including millions of avoided outage minutes, smarter work bundling that leads to fewer planned outages, and significant cost savings that are reinvested back into the system.

Strategic Grid Planning

By using the analysis platform, PG&E is able to make consistent, value-based, and risk-informed decisions. James Hansell, principal data scientist at PG&E and a tech lead for the project, explained that SNAP provides a common framework for risk modeling and ensures that all sums on assets roll up and align with enterprise expectations.

“The system models risks related to reliability, capacity, wildfire, financial performance, and public safety, all calibrated to enterprise-level risk assessments,” Hansell said. “This coordinated approach across different risk types is enabling a significant shift in how the utility operates.”

Planning for Value-Driven ROI

The collaboration between IFS and PG&E highlights the growing focus on integrated asset lifecycle management solutions. The combination of enterprise asset management and investment planning tools provides organizations with a unified view of assets, supporting more informed decision-making, better resource allocation, and improved operational efficiency from planning through execution.

For instance, integrated asset and investment management tools can significantly reduce the time and effort needed to develop plans, demonstrating measurable benefits in efficiency and outcomes. Cloud-based enterprise asset management solutions are designed to streamline operations and maintenance, while providing accurate, actionable data to guide decisions across an asset’s full lifecycle.

Kevin Price, IFS Global Head of Enterprise Asset Management, highlights the importance of this shift toward integrated solutions. He emphasizes that niche solutions, while important for specific tasks like understanding fuel consumption or emissions, often fail to address the interconnected nature of asset management.

Price advocates for a "composable enterprise approach, which allows companies to build a comprehensive solution piece by piece as their business demands, ensuring success upon success.” Price’s vision for asset management in five years is one where solutions are "vertical available, meaning they are pre-configured to the specific needs of an industry, like food and beverage or utilities, and are composed of various components that can be picked and chosen as needed.” He also stresses the critical role of education and communication in driving a culture of reliability and sustainability.

This move toward integrated platforms aligns with broader industry trends. Technology research and advisory firm ARC Advisory Group sees that EAM systems, which focus on the optimal operation and maintenance of physical assets, provide a strong foundation for infusing AI due to their standardized asset models. The integration of AI into EAM can help address skills gaps by extracting knowledge from maintenance records and providing decision support to less experienced technicians.

The foundational Asset Registry data managed by PG&E, combined with its efforts to improve data quality and governance, is consistent with this approach. Furthermore, the challenge of siloed data, which hinders the effectiveness of AI models, is being addressed by PG&E through the use of Palantir Foundry as a central data repository, creating a data fabric that integrates data from disparate systems.

In essence, the work being done by PG&E is a model for the future of asset-intensive industries. By combining a strategic, risk-informed approach with an integrated, AI-powered platform, utilities can move beyond reactive maintenance to proactive, data-driven decision-making. This not only enhances operational excellence and financial performance but also ensures a safer, more reliable, and more sustainable future for customers and communities.