What is this meeting about?
Connecting Rewards, Strategic Workforce Planning, and Organizational Design
Join us for an insightful webinar featuring Erzsebet Malzenicky, Global Head of Workforce Planning at Experian.
Erzsebet will share her experience of building a global job architecture and career framework from a strategic workforce planning perspective. She will walk through the design choices that result from starting with workforce questions rather than pay questions, the lessons learned along the way, and how that architecture enabled organizational design and workforce planning.
Stream:
Key take-aways:
Job architecture was presented not as a compensation framework but as essential workforce infrastructure that enables strategic workforce planning, career transparency, skills visibility, organization design, and workforce analytics. The discussion highlighted how a shared definition of work creates alignment across HR disciplines while supporting business transformation, standardization, and future workforce decisions.
A recurring theme was that architecture should be designed around future work, capabilities, and strategy rather than existing titles. Participants also explored governance, shared stewardship, AI-driven workforce change, and the need for ongoing maintenance to keep workforce structures relevant and trusted.
Key Takeaways
- Job architecture should serve the entire enterprise, not only Reward, providing a shared foundation for workforce planning, careers, learning, mobility, and analytics.
- Future work matters more than historical titles, making strategy, technology, and operating model discussions critical inputs into architecture design.
- Reward involvement is essential from the beginning to support grades, market alignment, pay transparency, and employee mapping.
- Shared stewardship creates sustainability, combining business ownership with HR governance and specialist expertise.
- AI analysis should focus on activities and workflows, helping organizations redesign, augment, and reskill work rather than simply predicting job replacement.
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