Do or Die: The 10 MASSIVE Mistakes Practitioners and Professionals Make When Preparing for L&D Disruption and the Future of Work (and what to do about them)


Trishuhl leaning left high res preview
Founder, Owl's Ledge LLC
Webinar Recording Details


This session explores MAJOR mistakes talent, training, learning & development practitioners and professionals make when preparing for L&D disruption and the future of work - and shows you what to do about them. 

We'll cover mistakes in the following: learning technology investments; human expertise and machine intelligence; training delivery strategies; learning experience design; instructional and informational interventions; training measurement, metrics and learning analytics; centers of control and learning in workflow; outside competitors and new L&D business models; cognitive and affective domains; and L&D skills, capabilities and career development. And we'll cover how to address and fix these mistakes.

Participants will learn the 10 MASSIVE mistakes in: 
  1. learning technology investments 
  2. human expertise and machine intelligence
  3. training delivery strategies
  4. learning experience design 
  5. instructional and informational interventions 
  6. training measurement, metrics and learning analytics 
  7. centers of control and learning in workflow
  8. outside competitors and new L&D business models
  9. cognitive and affective domains 
  10. L&D skills, capabilities and career development

About Trish Uhl, PMP, CPLP

Trish Uhl, creator of the Learning Systems Engineering Framework™, engineers learning solutions and leads project teams in design and development of data-enabled, results-driven learning experiences. As founder of the Talent & Learning Analytics Leadership Forum, Trish works with heads of Talent & Learning Development globally on setting and executing strategy for learning transformation and data-enablement projects. In addition, Trish works with talent and learning leaders on the professional development of their L&D teams, expanding the team’s focus from instructional products, to engineering dynamic learning systems leveraging data science, AI & machine learning, advanced analytics and predictive modelling to promote positive people impact and drive organizational outcomes.

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