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A few days ago, while presenting on in-house training, I realized something: I’ve been teaching in one form or another for more than half my life. In the last 15 years, these moments have included teaching secondary-school students and university classes, guiding company teams, and founding and leading nonprofit training programs. But it was only during the pandemic, while homeschooling my children, that I realized just how broken our education and training models can be. As I prepared lessons and tried different formats during those stressful times, memories returned of classmates labeled “problematic” (the kids who talked too much, couldn’t sit still, drifted to the back of the room, or fell behind). I recoiled at how harshly they’d been judged. In hindsight, many of them might have thrived under different circumstances. If we pause long enough to ask better questions, we realize: Learning isn’t one-size-fits-all. But our systems act as if it is. How training models filter who succeeds Here’s the harsh truth: If you design training for one type of learner, you’ll filter out others. Those who succeed aren’t necessarily the most talented but those who best fit that model. When organizations hire graduates of those models, whether they admit it or not, they’re selecting for conformity. Subscribe to the Daily newsletter.Fast Company's trending stories delivered to you every day Privacy Policy | Fast Company Newsletters Employers often say they can’t find the right talent—the creative thinkers, problem solvers, those who can adapt. Yet they continue sourcing from the same pipelines and the same hiring and onboarding processes. When newcomers don’t fit neatly, employers try to force them into the mold, only to lose them later to attrition. The feedback loops never change, so the problem repeats. We rarely ask new hires: “How do you learn best?” Instead, we expect them to adapt to our systems. In education, that means forcing students into rigid schedules, lectures, and exams. In companies, it means onboarding and training in the same way, regardless of individual strengths or styles. The result is predictable: people drop out, become demoralized, or never reach their full potential. The cost of one-size-fits-all training It’s true. Customized training and flexibility cost more. But the cost of not doing this is even higher. The average organization in the U.S. spent $1,207 per learner in 2022 for employee training. Companies with formalized education initiatives report 56% higher retention, versus only 21% for those with ad hoc programs Employee turnover is expensive. Replacing an employee making $60,000 per year can cost $30,000–$45,000 in recruitment and training costs. In one study, training, development, and management support explained a large portion of the variance in employee retention. These figures don’t just reflect dollars. They reflect lost opportunity, disengagement, and talent mismatches. Learning styles involve nuance, not a silver bullet You’ll often hear people talk about “learning styles” (visual, auditory, and others), and it’s tempting to take the idea as the gospel truth. Some research supports tailoring instruction to divergent learning preferences as a way to improve engagement and outcomes. However, matching teaching to a self-reported learning style doesn’t reliably improve retention. Instead, research shows that multimodal instruction (presenting content in varied formats) boosts attention, reduces monotony, and helps learners integrate knowledge through multiple senses. In practice, this means combining visuals, storytelling, hands-on work, discussion, and reflection, without rigidly demanding that each student stick to one learning style. Basically, we are talking about flexibility in training. advertisement A better path features flexible, adaptive, human-centered training If we accept that our systems exclude many talented people, we need a new approach. Here’s a proposed blueprint: Ask learners first: Don’t assume their preferences. Use quick surveys or conversational intake to identify how they like to engage Offer multiple paths: Present the same core material via lecture, videos, reading, hands-on labs, and peer discussion. Let participants choose how they want to learn. Allow pacing and catch-up: Not everyone moves at the same speed. Provide asynchronous options, review sessions, or office hours to fill gaps. Rethink onboarding and progression: Don’t force new people into a rigid mold. Let them demonstrate competency in different ways. Invest in feedback loops: Use assessments, surveys, and observation to see which paths are working—then iterate. Reward adaptability, not conformity: Recognize learners who take ownership of their journey, even if they did it differently. When companies adopt these practices, they broaden the pool of who can succeed. They stop filtering for conformity and start enabling diversity. Why it matters for equity, not just productivity When we force people into a narrow training model, we disproportionately exclude those with different life constraints. If we make training models more flexible and inclusive, we achieve higher retention, better performance, and open doors for people who wouldn’t otherwise have a chance to shine. It’s not enough to ask, “Are we finding talent?” We also need to ask, “Are we designing systems that allow talent to emerge?” Because when we exclude people at the training stage, we lose far more than we realize. Final words For too long, we’ve blamed students, employees, or candidates for not fitting into our existing systems. But the truth is: The problem lies in the systems themselves. If you design only one pathway, you’ll inevitably lose many otherwise-capable people. We have the responsibility to experiment, adapt, and build training infrastructures responsive to the diversity of learners in front of us. Because it’s not the learners who are failing the system. It’s the system that’s failing the learners. And if we want innovation and resilience, we need to start rebuilding from the ground up. Pablo Listingart is the founder and executive director of ComIT.
