Using analytics for asset management within utility operations is not a new concept. Today, many organizations are under tremendous pressure to seek efficient ways to monitor and maintain their critical assets. Many asset managers are also challenged to put into practice the necessary process and technology to boost reliability, resilience, and security. So, how can advanced analytics help organizations optimize their utility asset management? In this article at McKinsey, Anjan Asthana et al. explain how applying advanced analytics to asset management can accelerate a broader organizational transformation.
An Asset Management Example – UtilityCo
The authors share a stand-alone example of UtilityCo. They shed light on the approach taken to implement advanced analytics, the lessons learned, and the best practices the company adopted.
Challenges Faced by UtilityCo:
- The organization had decentralized asset management operations. Each operating unit took a distinctive approach and methodology.
- Utility asset management teams did not take a risk-based approach when deciding or prioritizing preventive-maintenance activities.
- The valuable data collected by UtilityCo was underutilized and stored in multiple systems.
How Did the Company Overcome the Challenges?
- UtilityCo realized that implementing advanced analytics demanded changes in the process. Therefore, the company discovered that leadership buy-in and push from the top was crucial for technology adoption.
- Different departments across the organization were encouraged to collaborate to achieve the sprint goals.
- The organization urged its asset managers to make changes to their management processes. To gain the leadership buy-in, UtilityCo engaged the asset managers early in the process of building the models.
Benefits of Advanced Analytics in Utility Asset Management
The benefits of implementing advanced analytics in asset management helped UtlityCo in multiple ways.
- The company “optimized capital expenditures either by maintaining current risk and spending less—and letting the excess capital expenditures flow into the profit and loss (P&L) or be reinvested to deliver more reliability—or by spending the same amount and achieving higher reliability through replacing the riskiest assets,” say the authors.
- It lowered operating expenses by optimizing preventative maintenance activities.
- It reduced the corrective maintenance operating expenses too.
- Advanced analytics helped the organization achieve higher reliability, causing fewer failures.
To read the original article, click on https://www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/a-new-approach-to-advanced-analytics-in-utility-asset-management.
