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<p>This paper examines how organizational learning leaders define and use workplace performance support and learning in the flow of work, including the strengths and challenges of these approaches and tools. We surveyed 84 individuals working across a variety of roles and industries and interviewed 21 individuals representing various learning and development functions across 21 different organizations. Our findings provide a contemporary understanding of how workflow learning is evolving and describe changes in how performance support is developed and utilized by individuals and organizations, particularly around Artificial Intelligence technologies and data capabilities. We found three common themes for perceived strengths of performance support and workflow learning: just-in-time support for work, skill building, and onboarding; provision of data that are useful for management to identify process efficiencies, improvement opportunities, and reduce data entry work; and reduce the time spent and reliance on formal learning. We discovered two common challenges across the data: inconsistent understanding of workflow learning and performance support and the requirement of intentional support for effective implementation. We offer a new definition and recommendations for adoption of workflow learning and performance support.</p>

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Empowering Organizational Learning: Technology-Driven Performance Support for Real-Time Skill Building and Workflow Efficiency

  • 期刊论文

  • 发表日期：

    2025年7月5日

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  • Roshan Bharwaney,
  • Seth-Aaron Martinez,
  • Brian Simko,
  • Jeffrey Dalto,
  • Tyler Bangs,
  • Nolan Lovett

摘要

This paper examines how organizational learning leaders define and use workplace performance support and learning in the flow of work, including the strengths and challenges of these approaches and tools. We surveyed 84 individuals working across a variety of roles and industries and interviewed 21 individuals representing various learning and development functions across 21 different organizations. Our findings provide a contemporary understanding of how workflow learning is evolving and describe changes in how performance support is developed and utilized by individuals and organizations, particularly around Artificial Intelligence technologies and data capabilities. We found three common themes for perceived strengths of performance support and workflow learning: just-in-time support for work, skill building, and onboarding; provision of data that are useful for management to identify process efficiencies, improvement opportunities, and reduce data entry work; and reduce the time spent and reliance on formal learning. We discovered two common challenges across the data: inconsistent understanding of workflow learning and performance support and the requirement of intentional support for effective implementation. We offer a new definition and recommendations for adoption of workflow learning and performance support.