The utilities industry is facing a range of challenges, including evolving regulatory requirements, aging infrastructure, and the need to reduce costs while improving service levels. To address these challenges, utilities must maintain and manage a vast and complex network of assets. Effective asset management strategies are critical for utilities to optimize their operations, minimize downtime, and ensure customer satisfaction.
However, according to a report by Experian, 98% of utility companies surveyed expressed a desire to improve their data quality and use it to draw actionable insights. The report also revealed that businesses spend as much as a quarter of their yearly revenue remediating errors caused by sub-standard data quality. Duplicate entries in customer data, incorrect recording or omitting data points are some of the common issues lowering quality of data collected and rendering it useless to provide valuable insights for the company.
Investing in accurate data collection and maintenance can be used for building an efficient organization and lead to significant benefits for utilities, including:
1. Predictive maintenance: Accurate data collection can help utilities predict when equipment is likely to fail, enabling proactive maintenance and reducing the risk of unplanned downtime. For instance, data analytics and machine learning techniques can be used to identify patterns in asset performance and predict when an asset is likely to fail, proactively, reducing the risk of unplanned downtime and improving asset reliability.
2. Condition-based maintenance: Real-time data on an asset's condition can be used to schedule maintenance activities, reducing the risk of failure and improving asset reliability. For instance, if a transformer is operating at a higher temperature than normal, it may be an indicator that the transformer is starting to fail. By detecting this early, utilities can schedule maintenance activities to repair or replace the transformer before it fails and causes an outage.
3. Asset-lifecycle management: Accurate data collection enables utilities to track an asset's lifecycle from installation to retirement, allowing for proactive replacement activities and reducing downtime.
4. Outage response: Data can be used to quickly identify the source of an outage and determine the best course of action to restore service. For example, data from smart meters and other sensors can help utilities pinpoint the location of the outage and dispatch crews to the affected area quickly.
5. Regulatory compliance: Many regulators require utilities to collect and report data on their assets' performance, safety, and environmental impact. Failure to meet these requirements can result in fines, legal liabilities, and damage to the company's reputation.
Investing in data collection and management may seem costly, but it can lead to significant long-term benefits, including reducing operational costs, improving asset reliability, and enhancing customer satisfaction.
To improve data collection and maintenance processes, Engineered Intelligence provides expert guidance on what data to collect, how to collect it, and how to maintain it for accurate and actionable insights. Contact us today to learn how we can help your organization become data-efficient.
Nitin Kohli believes that businesses are built and sustained on relationships. He is a business-minded data professional experienced at executing data-driven solutions. He utilizes his strong business acumen and analytical skills by designing frameworks to anticipate requirements, uncovering areas of improvement, and developing and implementing solutions.
At Engineered Intelligence, Nitin ensures that ENGIN’s data solutions are tailored to client’s requirements while being transparent and comprehensible.