Skills made simple

Skillsoft has introduced several platform enhancements to help organizations transition to skills-based talent strategies.

  • Thursday, 26th September 2024 Posted 10 months ago in by Phil Alsop

These enhancements, which are being showcased at Skillsoft Perspectives 2024, the company's annual customer conference, span the Skillsoft learning platform and benefit all users — from Chief People Officers and human resources teams to individual learners.

"Forward-thinking organizations recognize the transformative impact that skills-based talent strategies can have on workforce planning, productivity, and satisfaction. They also understand that this transition is a process that requires a solid framework for success,” said Ciara Harrington, Chief People Officer, Skillsoft. “We’re providing a structured approach for organizations to define and map skills, deliver role-specific learning experiences, and track progress in closing competency gaps. As Skillsoft implements these strategies and continues our own skills-based transformation, we are excited to guide our customers in making skills the foundation of all talent decisions.”

Streamline Talent Management with a Functional Skills Taxonomy

A common roadblock in adopting a skills-based approach to talent transformation is defining and reaching a consensus on the specific skills needed for jobs. To help eliminate this confusion, Skillsoft has built and integrated an AI-generated skills taxonomy into its learning platform. Providing a standardized central framework, or "dictionary," Skillsoft's taxonomy aligns skills to several categories ranging from "universal skills" such as personal productivity and digital proficiency to "role-specific skills" across functions including technology, sales, marketing, and finance. With skills automatically mapped to Skillsoft's learning curriculum and integrated into reporting and analytics dashboards, talent management teams can easily assess their workforce, identify competency gaps, and deliver upskilling programs tailored to the specific needs of employees.

Deliver Personalized, Job-Specific Learning Experiences with Role Advisor

Research from the Society for Human Resource Management (SHRM) showed 55% of employees saying they need training to perform in their job more effectively, and 38% wanting training more relevant to their role. Skillsoft is meeting this need with Role Advisor, a new, AI-powered tool that aligns specific learning experiences with learners' current jobs and career aspirations.

Drawing from Skillsoft's skills taxonomy, Role Advisor enables learners to choose from a defined list of more than 200 job roles — ranging from Chief Human Resource Officer to Artificial Intelligence Architect — each tagged with 10 to 20 skills deemed most critical for success and recommended learning experiences. Skillsoft customers using Role Advisor in early access observed that learners who selected a job role were 14% more likely to make learning a recurring habit compared to those without a selected role.

Additional features of Role Advisor include the ability for organizations to automatically match custom job architectures with Skillsoft’s skills taxonomy to deliver even more personalized skilling programs, as well as an Aspirational Role function that allows learners to identify a future job they hope to achieve, compare their skillset to what is required, and receive personalized learning recommendations to guide their transition.

Identify and Address Talent Development Trends with Skill Reports

Effective metrics, paired with robust reporting tools, allow talent managers to identify trends in skill development and cater their training approaches accordingly. Through new, detailed skill reports, organizations can easily export learning data from Skillsoft's platform and bring it into their talent management system. With the ability to filter and tag learning activity by skill, organizations can drive more strategic and effective efforts around workforce planning, talent development, and performance management.  

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