Across industries, maintenance and reliability leaders are navigating a growing paradox: organisations have more operational data than ever before, yet confidence in decision-making continues to decline. Even with advanced systems in place, teams often find themselves spending more time validating and reconciling data than actually using it to drive insights. This panel will explore the widening gap between data collection and effective utilisation across sectors such as mining, energy, utilities, and infrastructure.

Rapid digitisation hasn’t just increased the volume of data - it has also introduced fragmentation, inconsistency, and a loss of historical context. Field technicians and engineers are feeling the impact, with increasing demands around data entry and quality checks. In many cases, technology risks overshadowing experience and intuition, while poor data quality begins to undermine trust in analytics and maintenance decisions.

Our panel will examine the root causes behind this “data quality versus quantity” challenge. Drawing on real-world experiences, they’ll discuss how clearer governance, stronger alignment to purpose, and improved data standards can transform raw data into meaningful, actionable intelligence. The conversation will also look at how aligning data strategies with operational and business priorities can rebuild trust and ensure data genuinely supports better outcomes.

By challenging common assumptions about digital maturity, this session reframes what it really means to be “data-driven”- shifting the focus from accumulation to relevance, and ultimately helping organisations regain confidence and clarity in their maintenance data ecosystems.