Upskilling and reskilling employees are complicated challenges. It involves understanding where employees are skill-wise, knowing where they need to be, and bridging the gap with learning. Taxonomies offer enterprises an understanding of these needs by providing a structured and dynamic list of abilities. By making skill requirements explicit, taxonomies can make workforce planning intentional, match employers with job candidates, and even reduce systematic bias. However, the taxonomy needs to connect to learning to be meaningful.
In the domain of hard skills, Learning and Development has progressed by connecting granular learning objectives to learning content and assessment items. This becomes more challenging with soft skills and deep capability building as it is difficult to design and deliver learning experiences at scale, let alone report on them.
Learning platforms can address this problem head-on with “skills tagging” type features that explicitly connect learning to the underlying skills that this learning develops. As a result, learning leaders create experiences that are premium, high quality, rich in human connection, and scalable, measurable, and enterprise-grade.
This development lays the foundation for measurement and feedback-rich activity as the tagging helps learners receive quantitative and qualitative feedback on how well skills were demonstrated. Besides, rich, real-time feedback energizes the learner, neutralizes the negative impact of criticism through specificity, and keeps the learner in the flow of practice for continuous development.
For the program administrator, this granular data at the skills level means more capacity to zoom in and out, review patterns across a cohort, stage interventions, and improve the content and instructional design in real-time based on engagement and performance data.
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