The utility sector is undergoing a seismic shift, with nearly every player worldwide embracing digital transformation. The goal? To harness data and make operations swifter and more efficient. Traditionally, utility data has been siloed, but as these barriers crumble, a new challenge emerges: how to activate that data and extract value. It’s one thing to collect data from drones, weather stations, IoT sensors, and smart meters; it’s another to turn that data into actionable insights.
Utilities are grappling with the complexity of integrating diverse data sources into a unified dataset. This data must be processed and analyzed by both humans and AI to yield insights. However, turning these insights into action is where many utilities are stumbling. It’s akin to having a pantry full of ingredients but no recipe or chef to prepare a meal. Recent research from Gartner forecasts that global AI software spending in the utilities market will reach $17.8 billion by 2027. This substantial investment puts immense pressure on utilities to deliver immediate results. But it’s crucial to consider the long-term scalability of data. Utilities must establish workflows that direct and store data efficiently, even if it can’t be used right away. This ensures that as data volumes increase, utilities can handle the influx without being overwhelmed.
As central data silos within utility companies continue to disintegrate, different functions can harness this information to enhance decision-making. One area that stands to benefit significantly is asset management. According to the Department of Energy, 70% of utility assets are over 25 years old and nearing the end of their lifecycle. This aging infrastructure increases the risk of power outages, cyberattacks, and emergencies. Extending asset lifespans is a critical metric for North American energy companies, and achieving this will require more intelligent asset management strategies. Here are three ways utilities can activate their data to optimize asset management:
Better Mapping & Cross-Functional Capabilities: For decades, field crews relied on paper maps to track utility asset locations. This manual process was inefficient and prone to errors. Today, virtually all utilities use Geographic Information Systems (GIS) technology to digitally map infrastructure. As silos break down, GIS data can be shared across multiple departments. For instance, an asset manager can use GIS records to create a digital map for drone operators, who can then upload images for AI to process. This real-time data sharing improves operational effectiveness.
Predictive Maintenance: Utilities are constantly monitoring asset health with visual data from drones, helicopters, and field crews. By outfitting equipment with sensors and layering in AI, utilities can identify potential anomalies before they occur. This proactive approach optimizes maintenance operations, reduces the risk of major failures, and increases system reliability. Predictive maintenance also enables data-driven decisions, fewer truck rolls, reduced response costs, and improved customer relationships.
Work Order Prioritization: Work order management is how utilities create, assign, and track maintenance tasks. Traditionally, this was a manual process. But as utilities become smarter with their data, the work order process is modernizing. By tracking key performance metrics and using AI to identify patterns, utilities can prioritize work orders more effectively. This ensures an efficient operation with minimal service disruptions.
In the year ahead, the utilities industry will face numerous challenges as it works to enhance grid reliability and resilience. The companies that thrive will be those that operate with a mindset of continuous improvement. Now is the time for utilities to think creatively about their data and find new ways to use as much of it as possible to improve decision-making. Because when it comes to the future of utilities, knowledge is power.
