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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