The survey of 166 industry professionals reveals a disconnect between the perceived reliability of five-year capital expenditure projections and the underlying physical data. While many firms maintain confidence in their planning, 69% of respondents admitted to paying premiums on capital work that could have been avoided through earlier maintenance interventions. For 35% of those polled, these delays resulted in cost increases of at least 25%.

Emergency repairs remain a persistent drain on resources, with 63% of participants noting that unplanned events account for more than 10% of their annual capital spending. Despite the prevalence of these reactive cycles, only 20% of organizations have adopted predictive analytics or condition-based monitoring. Austin Rabine, CEO of SITE Technologies, noted that the industry often suffers from a false sense of security, where operators struggle with the symptoms of a broken planning process while simultaneously viewing their long-term forecasts as robust.

The report suggests that integrating machine learning and computer vision to assess asset conditions could shift the industry toward evidence-based planning. By replacing subjective assessments with consistent, portfolio-wide insights, owners could potentially reduce unplanned expenditures by more than 10% annually.