Quantitative and Qualitative Validation
Bielsa’s Mistake and Its Connection to Virtual Reality Simulators
In recent weeks, we received two pieces of news that made us proud because they show we are on the right path. The first is the result of years of hard, systematic, and persistent work. The second is an unexpected event involving Marcelo Bielsa that qualitatively validates our view of how new generations learn.
Part 1: The Long Road and Validation (The Quantitative Evidence)
In 2020, together with ACHS, we carried out one of Chile’s first large-scale Virtual Reality (VR) training implementations. We delivered machine-safety training at six manufacturing companies. It was not easy: the technology was still cumbersome, and the environments varied widely. We identified several issues, but instead of becoming discouraged, we treated every design and implementation error as an opportunity to improve.
After six years of continuous iteration—developing, piloting, and testing, not in the comfort of a laboratory, but with workers under the desert sun, at wind farms, solar plants, and mining sites—we established a robust methodology. Our simulators have now been tested by thousands of users.
For mining workers, our simulators are used throughout every stage of their careers:
Childhood: Children play at being miners by operating haul trucks at KidZania.
Education: Technical high-school students prepare to enter major mining companies.
Operations: Active workers train in critical scenarios to prevent fatal accidents.
Leadership: Managers use VR to identify cognitive biases in critical decision-making.
This accumulated experience enabled us to export our solutions to Peru, Central America, the United States, Europe, and Asia (Bhutan).
The crowning achievement of this effort arrived unexpectedly: an independent study by one of Chile’s most prestigious universities measured the impact of our LHD and Jumbo simulators at a major mining company, recording productivity increases of 30% and 29%, respectively, and concluded that operator age was not a barrier to adoption. This quantitative validation, conducted without commercial interests, clearly confirms the value of the hard work completed.
Part 2: Bielsa’s Mistake (The Qualitative Evidence)
The second confirmation came from the football field. After Uruguay was eliminated from the 2026 World Cup, Marcelo Bielsa took responsibility in his farewell press conference. He explained that the squad, whose average age was 28, demanded a drastic change in his working methods. The team’s complaints focused on:
Information overload: Technical talks and videos that were too long and repetitive, causing mental fatigue.
Loss of effectiveness: Because the analysis sessions were so long, the key concepts became diluted before the players took the field.
The players demanded short, concise, and dynamic analysis. Bielsa, an old-school coach, had to change course and admit that the group needed some “relief” and less rigidity to absorb the tactics.
What Bielsa understood too late is that we are experiencing a profound generational shift that affects football players just as much as workers at industrial plants and mining sites. These young people are digital natives: they consume information in dynamic, interactive, and direct formats. If a professional footballer becomes bored during long lectures about the sport they love, what can we expect from a mining operator facing a three-hour technical PowerPoint? The obvious result is no meaningful learning.
Our virtual reality solutions are a natural fit for this new generation of workers. We see it whenever we arrive at a site: workers embrace the technology and our training enthusiastically because it speaks their language—the language of interaction, immersion, and gamification.
Conclusion
We are experiencing a major technological and industrial transformation alongside clear generational changes that affect work, production, safety, and more. Meeting this challenge requires bringing knowledge and experience closer to workers through accessible solutions that improve productivity. At Yoy Simulators, we are excited to take on that challenge because these quantitative and qualitative validations show that we are on the right path.
