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As utilities evolve and face new challenges, the need for resilient infrastructure remains paramount. Leading utility and energy companies are now distinguished by their reliance on solution provider and platform ecosystems that intelligently integrate AI-powered analytics and cloud-based capabilities. The result is enhanced visibility and resiliency across assets, personnel, and activities.
Recent developments and partnerships from companies like GE Vernova and SAP highlight this trend. These collaborations support an optimal industrial data fabric, allowing utilities and other asset-intensive organizations to make real-time, data-driven decisions that improve efficiency, reduce downtime, and strengthen their infrastructure.
While legacy systems have often started out as a source of strength, many have not kept pace with rapid changes and have therefore become a source of weakness due to fragmented data and a lack of real-time insights.
Traditional, siloed operations are no longer sufficient to navigate the complexities of modern infrastructures and grids. The migration to next-generation platforms like SAP S/4HANA is part of the much-needed transformation, along with their association with partner and solution provider ecosystems that promote holistic approaches.
Specifically, truly resilient infrastructure requires an integrated ecosystem that combines core business systems with adjacent systems like Asset Performance Management (APM) and Manufacturing Execution Systems (MES). These must be integrated in ways that break down data silos and allow for scalable, reliable, and fluid processes for the exchange of information.
This is the way to create a single, comprehensive view of operations—from the plant floor to the executive suite.
The key to building resilient infrastructure lies in moving beyond simply reacting to problems and instead using data and AI to predict and prevent them. The goal is to create an ecosystem that can monitor asset health, forecast downtime, and optimize maintenance strategies before a failure occurs.
This proactive approach is being enabled by the growing adoption of AI and digital twins. Examples include:
GE Vernova's Digital Wind Farms: The company uses digital twin technology to create virtual replicas of its wind farms, which allows engineers to design the most efficient turbine for each location and continuously improve performance by analyzing real-world data. This can increase energy production by as much as 20 percent. (Two related links of interest are: Benefits of Expanding APM during SAP S/4HANA Migration – GE Vernova, and GE Vernova's New AI-Powered Autonomous Software to Transform Energy Asset Inspections).
Thames Water's Digital Replica: Thames Water is using a digital twin of its water supply network to find and repair leaks that would otherwise go undetected. By compiling data from smart meters and acoustic loggers, the company can simulate the effects of repairs and save millions of liters of water. (See SAP blog, Digital Twins at Work).
SAP S/4HANA Integration: The new SAP S/4HANA platform provides the core business system, but its power is unlocked when it integrates with modern APM and MES solutions. This allows for APM-generated insights to automatically trigger work orders in SAP S/4HANA, creating a seamless and intelligent workflow.
The partnership between GE Vernova and SAP also illustrates the value of upgrading APM or MES systems in parallel with an S/4HANA migration. In this way, organizations can combine resources into a single project, significantly reducing the potential for costly rework.
By leveraging the right platform to create a cohesive, AI-powered ecosystem, organizations can ensure ongoing operational excellence and more resilient operations—all driven by a smarter, more connected use of data.