How Las Bambas Successfully Deployed Readi with Widespread Employee Acceptance

The Challenge

Las Bambas, one of the largest mining operations in Peru, had experienced challenges implementing fatigue management technologies in the past. Previous tools like SmartCap were poorly received due to physical discomfort and a lack of change management—leading to low operator trust and resistance.

As a 24-hour operation , the mine needed a fatigue solution that could address safety concerns in their MineOps, Exploration, and Engineering teams without disrupting operations or alienating its workforce.

The goal was clear: implement a predictive solution that could work alongside Hexagon’s in-cab camera system to anticipate fatigue risks in advance—rather than relying solely on reactive alarms triggered during critical fatigue events.

Implementing Readi to Predict and Prevent Fatigue

To meet this goal, Las Bambas deployed Fatigue Science’s Readi platform in tandem with Hexagon’s OAS driver-facing camera system. While Hexagon served as a reactive safety net, Readi provided supervisors with predictive fatigue insights—enabling action before alarms ever sounded.

The mine applied a structured ADKAR change management framework to ensure operator buy-in. Rather than pushing a broad rollout, the site opted for small-group deployments—training 160 operators in controlled batches of five. This approach allowed for hands-on supervisor engagement, personalized communication, and clear explanation of how Readi would enhance, not hinder, daily operations. It also supported the site’s change management success metric: achieving at least 70% operator adoption during deployment.

To support adoption, operators received a custom kit including the ReadiWatch, charger, and instructional guides. Visual materials and team-led briefings made the new program easy to understand, helping reinforce its purpose: improving safety through proactive, data-driven decision making.

Improving Safety Through Engagement and Predictive Technology

By prioritizing communication, personalization, and union collaboration, Las Bambas achieved strong frontline engagement—an essential factor in the success of the deployment.

Supervisors now rely on ReadiScores daily to proactively identify elevated fatigue risk and take early action, well before operators reach the threshold likely to trigger in-cab camera alarms. A ReadiScore below 70, for instance, correlates with a 14.5x higher likelihood of a fatigue-related event.

The decision to train operators in small cohorts also proved effective, enabling faster learning, reducing resistance, and improving overall perception of the fatigue management program.

With this foundation in place, Las Bambas is continuing to expand Readi across the operation to further strengthen its safety culture and operational resilience.