Research tagged with "Motivation"

Most organizations fail with OKRs, turning a promising framework into a bureaucratic chore that kills motivation and growth. The five most common mistakes are: confusing OKRs with KPIs, focusing on goals instead of strategy, creating silos, chasing only what’s easy to measure, and making the process demotivating. Reclaim OKRs as a tool for strategic alignment, cross-functional collaboration, and genuine performance. Distinguish growth from business-as-usual, prioritize problem-solving, measure what matters, and build a system that actually motivates teams to achieve real results.

Traditional and hierarchical job grading systems are failing modern organizations, and a performance-based level framework can unlock growth, reduce burnout, and foster a high-performing, people-first culture. Drawing on recent research and real-world examples, it shows how clearly defined job levels—anchored in tactical and adaptive performance, observable behaviors, and skill-based compensation—help organizations adapt to the AI era. The article provides a practical 10-level model, details how skill-based pay works, and demonstrates how this approach makes performance management more transparent and motivating for all employees. The authors argue that embracing this framework is critical for companies seeking to thrive in a rapidly changing, AI-driven world.

While EOS provides valuable structure and accountability for small teams, it often strains as companies grow, leading to alignment gaps and missed opportunities. Factor builds on this foundation, offering evolved rhythms and tools designed to scale performance, align complex organizations, and empower teams to solve critical problems effectively.