Session Leaders: Sharna Wiblen and Elizabeth Heichler

Thursday, May 29, 2025
8am PT | 11am ET | 4pm BST (1 hour duration)

Commercial Digitalized Talent Management (DTM) systems promise to streamline talent decisions by providing best-practice frameworks for objectively identifying talent. But when we rely too heavily on these systems, we risk outsourcing critical strategic decisions to algorithms that don’t account for the nuances of your culture or strategic goals.

So, how can executives effectively design fit-for-purpose talent systems and decisions?

Join the Center for Effective Organizations at the USC Marshall School of Business for an interactive webinar with renowned talent strategy expert Dr. Sharna Wiblen and Elizabeth Heichler, Editorial Director at MIT Sloan Management Review. Together, they’ll discuss how organizations can design talent and technology systems that serve—not hinder—their business strategy.

What You’ll Gain from This Webinar

• A strategic-first approach. Learn how to establish talent decisions that place your unique strategy front and center.
• Custom-fit talent definitions. Understand why defining talent on your terms is essential for executing your strategy.
• Hidden pitfalls of digital tools. Understand the unintended risks of relying on commercial algorithms and frameworks—and how to avoid them.
• Design fit-for-purpose systems. Creating digital frameworks that intentionally include, rather than seek to exclude, human judgment.
• A new decision-making mindset. Learn the mindset shift to help you embrace the salience of everyday talent decisions.

Join us for this insightful conversation and learn how to effectively synergize talent systems with human judgment to position your organisation as a talent management leader

SPEAKERS

University’s Notice of Non-Discrimination

This program is open to all eligible individuals. The Center for Effective Organizations operates all of its programs and activities consistent with the University’s Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.