Asset Performance Management: Overcoming the Big Data Challenge

Asset management is one of the most complex elements of the utility business. Many utilities’ current practices are plagued with archaic technologies, practices and strategies. Traditionally, it has not been uncommon for power utility asset management to consist of spreadsheets populated with asset counts, purchase dates, expected life, and suggested maintenance schedules—each housed in various utility silos.

Asset performance management (APM) is an emerging field of technologies and strategies that aims to improve and optimize asset management by centralizing asset information in a way that it can be usefully analyzed. APM builds a bridge between software such as enterprise asset management systems, workforce management systems, and other relevant sources of data that pertain to assets. Upon consolidating this information, analytics can translate data into meaningful insights that cut costs and improve the safety and reliability of the power grid.

Whether it be improving the operating efficiency of the workforce through more intentional management and planning or implementing predictive analytics around asset failure and grid malfunctions, APM technologies offer a more streamlined approach for utilities to pursue continuous improvements.

Data, Data Everywhere

One perceived head wind for utilities considering a holistic APM program, however, relates to the sheer volume of data—and its diverse formats, homes, structures, and accuracy—involved in APM program development. But with a systematic, well-defined plan in place, utilities can overcome each of the following data challenges and realize the many benefits of APM programs:

  • Identify available data sources across the organization: Datasets are stored within different systems and in different operational silos. At a time when many large utilities are consolidating, the level of data granularity available within different operating companies may also vary widely.
    The APM implementation team’s first task will be to survey for datasets and formats across all relevant divisions within each operating company. Do not underestimate the importance of this initial data mapping exercise.
  • Cleanse data to reflect consistent and accurate values: Once all the key datasets have been identified, it will be necessary to validate the accuracy and consistency of formats from various sources. There may also be missing data that will need to be added in. Corrections to the data should be done at the source level so that correct data flows through to all end users. Ultimately, the output of the APM system will only be as good as the input.
  • Map data to ensure all relevant data for accurate analysis: Once the datasets have been catalogued and cleansed/filled in, the utility, probably with help from its vendor, will need to identify its current and future goals in terms of output—and then ensure that the necessary data is being collected.
    In some cases, new networking/connectivity may be required. For example, if the utility expects to monitor and analyze substation assets at the distribution level, it may need to deploy connectivity and data collection devices to those substations. Even if the utility intends to begin at the transmission substation level—where connectivity and data collection are already in place—it may want to design its program with the future goal of incorporating distribution-level assets in mind.
  • Consolidate IT and OT data sources to a centralized system: More and more utilities are evaluating their data storage needs and investing in data centers or data lakes. This is, however, a relatively new phenomenon, and utilities without these centralized resources may have to invest in substantial data storage resources—or acquire the capacity from a third-party provider. Data security—whether the data facility is in house or acquired from a third-party service provider—is of paramount importance.

From Evolution to Revolution

The concept of real-time APM, with visibility of assets throughout the grid tied to sophisticated analytics with predictive capabilities, is revolutionary for electric utilities. Asset lifecycles and maintenance practices that have been in place for decades are beginning to evolve into condition-based systems. The efficiency gains and reliability enhancements promise to be extraordinary—in time.

For more information on this topic, please join us for a free webinar as we explore how to overcome the data challenges utilities face when digitizing their APM systems and processes. 

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Richelle Elberg is a principal research analyst contributing to Navigant Research’s Utility Transformations program and heading up the Smart Grid research services, including Connected Grid, Digital Grid, and Dynamic Grid. Her primary focus is on communications networks for utility applications, including AMI and substation and distribution automation applications. Elberg has more than 20 years of experience in the telecommunications industry, including an extensive background analyzing and writing on the wired and wireless communications industries from operational, financial, strategic, technical, and regulatory perspectives.

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