It has been recognized for some time that many mining operations do not meet their forecast production or realize their projected financial value. In many (most?) cases, this is due to technical failures during feasibility studies—i.e., insufficient orebody knowledgeOre body knowledge (McCarthy in AUSIMM Mining Risk Management Conference Proceedings, 2003 [1]). Recent work by Gillis et al. (Resour Policy 90:104821, 2024 [2]) has pointed out that poor orebody knowledge may be a leading cause of financial underperformance of the Canadian mining industry, with impairmentsImpairment related to technical errors recognized as a significant driver of financial loss. The global cost to the industry exceeds more than USD$1,000,000,000 per year. Therefore, poor orebody knowledgeOre body knowledge represents a significant financial and environmental risk to the mining industry. Conversely, emerging technologies and new data integration and analytics mean that more orebody data is being collected than ever before and is seen as a panacea to improving mining industry performance. However, we argue that the most serious challenge is to convert the abundant, high-quality data being collected into actionable knowledge with a stated robustly determined financial benefit. We suggest this will require an “exploration to mill” effort with enhanced collaboration between teams across the value chain, new data integration and visualization tools, and data analyticsData analytics and support.