Employers have never had so much data to inform, innovate and optimize their talent strategies. However, understanding and extracting value from this data is something many organizations are still struggling with.
So how should employers be thinking about data, implementing data-driven talent strategies, and planning for a future of data-based decision-making?
My guest this week is Grant Telfer, Business Development Director at Textkernel. Textkernel has long specialized in bringing machine learning, AI, and data-driven intelligence to talent acquisition, and Grant has some great advice, use cases, and future insights to share.
In the interview, we discuss:
The current state of talent markets
Magnified skill shortages
Extracting value from data
What are the most important data sets employers have access to
Skills taxonomies and internal mobility
Upskilling and succession planning
Data & APIs
The dangers of not using data to its full potential
The role of AI
Example use cases and outcomes
What does the future look like, and how should we plan for it
This episode is supported by Textkernel:
Textkernel is a global leader in AI-powered recruitment solutions, delivering multilingual parsing, semantic search and match, and labor market intelligence solutions to over 2,500 corporate and staffing organizations worldwide. Our innovative technologies help companies better connect people and jobs.
See how you can connect people and jobs better, request a demo: https://hubs.ly/Q01VLGr40
Visit our website to learn more about our solutions: https://hubs.ly/Q01VLFnW0
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