Turning HR into Analytics Translators: A Step-by-Step Guide

Exploring the success of ING's People Analytics Academy
Céline Ingenegeren Maria Rosaria Bonifacio
Céline Ingenegeren, ING
Maria Rosaria Bonifacio, Nokia

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Nokia's Rosaria Bonifacio talks with ING's Céline Ingenegeren about the People Analytics Academy – a peer-led programme that equips HR to translate data into action. Learn how executive nomination created early momentum, translators authored and delivered the curriculum, and cohorts produced a reusable insights deck for their leaders. Hear candid lessons on segmenting beginners and advanced learners, sizing groups for engagement, and anchoring every module to live business problems. The discussion also covers ING's cautious, governance-first approach to GenAI, practical Copilot demos, and how global standards balance local needs. Expect a replicable model with clear measures, alumni community design, and tips to sustain adoption.

Digital skills shortages already cost the UK economy £63 billion annually, while 78% of global enterprises are rolling out AI in at least one function. HR faces urgent pressure to close the data-fluency gap, comply with the EU AI Act’s “high-risk” rules for talent analytics and prove ROI amid 2025 cost constraints – making practical up-skilling frameworks mission-critical.

This session will explore:

  • Executive sponsorship and nomination: embedding capability building into team KPIs and selecting the first cohort for momentum.
  • Peer-led design: analytics translators create and facilitate modules, blending hands-on practice with real ING use cases.
  • Curriculum architecture: differentiated tracks, pre-work baselines, and breakout challenges for beginner and advanced profiles.
  • Outputs that travel: the weekly skeleton insights deck that participants complete and present to their leaders.
  • GenAI integration with controls: ING's governance-first approach, targeted use cases, Copilot demos, and prompt-writing basics.
  • Global–local balance: common data definitions and platforms, with room for local requirements (e.g. pay-gap reporting variants).
  • Adoption and sustainment: measuring competencies, NPS and attendance; alumni ambassadors, events and continuing up-skilling.

Learning outcomes:

  • Design a minimum-viable translator academy, including cohort size, nomination and peer-led delivery.
  • Segment learning paths so beginners and advanced practitioners both progress without losing engagement.
  • Embed AI governance, model validation and practical prompting into HR curricula safely.
  • Create reusable insight artifacts that land with leaders and inform action.
  • Balance global standards with local needs using clear definitions, tooling and escalation paths.
  • Track behaviour change and business value through competency shifts, adoption signals and impact on productivity, retention and cost-to-serve.