For decades, power utilities relied on a simple philosophy: repair equipment when it fails.
While effective in the short term, that approach has proven increasingly costly and disruptive as infrastructure ages and system complexity grows.
According to energy systems reliability expert Bismark Kyere Yeboah, the future of power infrastructure depends on moving decisively away from reactive maintenance.
“Reactive repairs are expensive, unpredictable, and often preventable,” Yeboah said. “The future lies in predictive reliability — understanding failure patterns before they turn into outages.”
Yeboah has spent much of his career working at the intersection of engineering, analytics, and operational governance. His experience spans large distribution networks, institutional energy systems, and reliability-focused modernization programs.
Across these environments, he has advocated for maintenance strategies driven by condition monitoring, performance metrics, and data-based forecasting.
Predictive reliability differs fundamentally from scheduled or time-based maintenance. Instead of servicing equipment at fixed intervals, predictive systems continuously evaluate asset health using operational data.
This enables engineers to identify degradation trends early and intervene only when risk indicators justify action.
“Infrastructure doesn’t age uniformly,” Yeboah explained. “Two transformers installed on the same day can experience completely different stress levels.
Predictive maintenance recognizes that reality.”
According to Yeboah, one of the most important shifts occurring in the industry is the integration of maintenance decisions into broader reliability governance frameworks.
Predictive analytics alone, he notes, cannot improve performance unless organizations adapt how decisions are made.
“Technology provides insight, but policy determines whether insight is used,” he said. “Without governance structures, predictive tools remain dashboards rather than solutions.”
In utility environments where predictive models have been fully implemented, results have been substantial. These include reductions in outage frequency, lower transformer failure rates, improved workforce planning, and measurable cost savings.
Equally important, predictive reliability enhances public trust by improving service continuity.
Yeboah emphasizes that workforce development is also critical to success.
Engineers and technicians must be trained not only to operate equipment, but to interpret data and apply reliability principles consistently.
“Predictive reliability is as much a cultural transformation as it is a technical one,” he said. “Organizations must shift from firefighting to foresight.”
As renewable energy adoption accelerates, the importance of predictive frameworks continues to grow. Variable generation and distributed resources place new stresses on traditional grid designs, making proactive maintenance essential for stability.
Looking ahead, Yeboah believes utilities that fail to modernize maintenance strategies will face escalating costs and reliability risks.
“The grids of the future will not be maintained the way they were built,” he noted. “Reliability must be engineered continuously.”
For infrastructure leaders navigating modernization challenges, predictive reliability is no longer explained as innovation; it is increasingly viewed as a necessity.
By Vera Owusu