People Analytics World Podcast

Synthetic workforce data is reshaping how HR leaders approach change management. In this episode, HubSpot’s Matthew Corritore explains how his team uses predictive analytics to anticipate employee reactions to new policies – and why this matters for leaders navigating complex transformations.Matthew shares how his People Analytics team developed a change management tool powered by synthetic data, what lessons they learnt in rolling it out, and how it’s evolving into a full end-to-end platform.The conversation covers: – Anticipating workforce reactions with synthetic data – Applying predictive analytics to HR policy rollouts – Designing tools that augment, not replace, change leaders – Building responsibly with privacy and bias in mind – Creating an end-to-end AI-powered change management platform – Lessons from HubSpot’s agile development approach00:00 – Introduction and guest background 01:33 – Why HR should explore synthetic workforce data 03:12 – Predictive analytics explained in plain terms 05:33 – Data privacy and responsible use 09:16 – Building the workforce twin at HubSpot 11:45 – Case study: job levelling rollout 13:35 – Inside the chatbot tool (V1) 16:49 – Data selection and employee reactions 19:56 – Adoption and augmentation, not replacement 21:38 – Towards a full end-to-end change management platform (V2) 24:46 – Handling complex rollouts and stakeholder mapping 27:12 – Segmentation of employees and leaders 29:12 – Addressing bias, fairness and regional differences 31:18 – Balancing simulation with employee voice 33:56 – Starting small and building responsibly 35:35 – HubSpot’s internal AI agent platform 37:15 – Reception among leadership and HR teams 39:50 – Extending to other HR use cases 40:43 – Lessons learnt: focus on solving real problems 43:11 – Future uses of synthetic data in HR 44:52 – Key surprises and closing reflectionsGuest: Matthew Corritore – Senior Manager, People Data Science, HubSpotResources & links: People Analytics World 2025 New York – pawld.com/nyc

How did S&P Global turn a two-person HR team into a force that reshaped financial strategy? Alan Susi reveals the workforce-planning breakthrough that won over the CFO and delivered millions in measurable impact.Vice President for Organisational Planning and Analytics at S&P Global, Alan Susi, explains how he built workforce planning from scratch, translated models into Finance language, and scaled credibility through quick wins and stakeholder trust.Chapters:00:00 – Introduction and career background02:15 – From people partner to workforce planning pioneer05:30 – First prototype failure and lessons with Finance10:05 – Speaking Finance language and shifting cadence14:20 – Building minimum viable workforce planning models18:45 – Vendor choices and keeping planning simple23:10 – Key metrics and breakthrough data points27:35 – Signs the approach was working32:20 – Scaling challenges and system redesign37:55 – Rapid-fire myth busters45:10 – The 90-day workforce planning experiment49:30 – Looking ahead: AI and the future of planning53:20 – Closing reflectionsTopics:– Translating HR insights into Finance-friendly metrics– Using minimum viable products to prove value fast– Partnering with CFOs and legal teams for credibility– Evaluating vendors while avoiding over-engineering– Identifying breakthrough metrics such as revenue per employee– Scaling workforce planning through people partners– Preparing for AI’s impact on capacity modelsPAWorld Podcast, episode 13Host: Rosaria Bonifacio – VP HR, NokiaGuest: Alan Susi – Vice President, Organisational Planning and Analytics, S&P Global

Skills‑first leadership without the buzzwords Chief Talent Officer Jig Ramji shares how to build outcome‑based models, win Finance with evidence, and use AI responsibly in people decisions. From tailored leadership attributes to a data‑led acceleration case in APAC, Jig offers concrete pitfalls, dashboards and governance lessons for HR, Finance and People Analytics leaders. Topics:Tailoring leadership models to strategy, culture and ambition – not off‑the‑shelf. Replacing competency checklists with outcome‑based success predictors (e.g., followership; developing talent). Winning sceptical Finance with discrete pilots; APAC leadership acceleration with 65% progressing within 12 months. Using generative AI in assessment – validity, reliability and human judgement remain central; cautious use for promotions/succession. Governance dilemma – don’t abdicate leadership to AI; use it to augment human‑centred work. Designing people analytics for HRBPs – make insights simple, contextual and usable. Skills gap vs leadership constraints – prioritise strategic workforce planning and skills adjacencies. Guest(s):Jig Ramji – Chief Talent Officer.Hosted by Rosaria Bonifacio – follow and subscribe for future episodes.

How do you actually become a skills‑led organisation? In Episode 9, Francesca Caroleo – CHRO at Citi Luxembourg, formerly at Allianz and Bank International of Luxembourg – lays out a pragmatic, manager‑friendly path from headcount to skills. Hosted by Rosaria Bonifacio (VP HR at Nokia), this conversation turns buzzwords into actions: define the job, pick the few core skills, prototype before you scale, and build a growth culture. It also shows where AI strengthens – not replaces – your competency model. Chapters: Definition of a skills‑led organisationHeadcount vs skills planning100‑day plan (assess, prototype, avoid heavy governance)Spider‑chart insightsMiddle‑manager engagementAI and competency models2030 KPIs and mobility. Topics:– Defining a skills‑led organisation and the traps of bloated skills inventories– Moving from headcount models to skills‑based planning when talent is scarce– Building a simple backbone: job mission, three core skills, and key attributes– 100‑day playbook: assess business ambition, talk to middle managers, prototype before scale– Visualising capability gaps with spider charts and balancing values vs business drivers– Fixing communication mistakes by engaging middle managers through workshops– Using AI to solidify skills data while keeping competency models as the compassConnect with Francesca on Linkedin: https://www.linkedin.com/in/francesca-caroleo-shrm-scp-icf-acc-89908831/ Subscribe to the People Analytics World Podcast for more conversations on workforce, skills, and people analytics.

A candid interview on shifting from next-day manpower planning to a skills-based, long-term workforce strategy. Learn how to align with the business, blend people and financial data, reskill at scale, manage vendors, and build a learning culture that sustains change.This interview explores how to rebalance an operation optimised for short-term delivery towards a skills-based, long-term workforce strategy. We cover aligning HR with the business on a shared vision, moving from headcount to capability, and coping with location-based constraints.Practical examples include transparent reskilling deals, an AI-driven skills platform using a single external framework, an open internal talent marketplace, and new roles such as learning architects and skills experts. We discuss integrating HR, finance and sales data to become predictive, how to structure vendor relationships and best-of-breed choices, and the culture shift required – from ambassadors and inspiration days to metrics that prove impact.The conversation explores:Balancing day-to-day manpower planning with long-term workforce strategy.Building a shared vision with the business – governance, projections, and accountability.From headcount to capabilities – designing a single external skills framework.AI-driven skills profiling, calibration, matching and an open internal talent market.Reskilling at scale – learning architects, skills experts, curation and delivery mix.Integrating HR, finance and sales data to predict demand and strengthen hiring.Vendor strategy – early adoption, best-of-breed, contracts, and cost control.Learn more and watch the full video on PAWorld365Contact Anette on LinkedInContact Nick on LinkedIn

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. This session explores: 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. Contact Céline on LinkedInContact Rosaria on LinkedIn

This interview explores how a multinational people analytics function is operationalising CSRD and the EU Pay Transparency Directive – not as a tick-box exercise, but as a durable pay-equity capability. It covers defining pay beyond base, bonus and LTI by including taxable and in-kind benefits; why deep partnership with Payroll and Comp & Ben matters; and how a robust global job architecture enables apples-to-apples comparisons across countries. We also address transparency and privacy, methods for measuring and remediating gaps, and where AI can accelerate work with the right guardrails. Take away a practical blueprint – data, processes and governance – to meet mandates and strengthen trust.Topics covered:CSRD versus EU Pay Transparency – complementary purpose, scope and depth; organisation lens versus associate lens; a layered analytics approach that serves both.Defining the pay universe – cash, bonus, equity and in-kind or taxable benefits; methods to monetise benefits for analysis and reporting.Data sources and quality – joining HRIS with payroll; field-level definitions, taxability codes, controls and stewardship to create a complete pay dataset.Global comparability – using job architecture as the backbone; normalising for local market factors; handling small populations and exceptions.Transparency, privacy and process – pay ranges, candidate and employee communications; PII safeguards; case management, escalation and audit readiness.Analytical workflow – segmentation, matched comparisons and control variables; identifying gaps, setting remediation logic and reporting to leaders.AI enablement – human-in-the-loop guardrails, assessing bias versus accuracy, evaluation metrics (e.g. confusion matrices), documentation and monitoring.Outcomes:Separate and align CSRD and EU Pay Transparency requirements while designing one integrated fair-pay capability.Identify the critical fields, sources and quality checks to build a complete pay dataset, including benefits and taxability, across countries.Apply a robust job architecture to ensure apples-to-apples comparisons and fair remediation globally.Design transparency and privacy controls that build trust without exposing personally identifiable information.Run a defensible pay-gap analysis and convert findings into remediation plans and board-ready reporting.Use AI safely as decision support – establish human oversight, bias checks and clear model documentation.Set a 2028 roadmap that turns compliance momentum into a lasting fair-pay programme with cross-functional ownership.Connect with Ashish PantConnect with Dan RileyFind more sessions on driving business outcomes with people data on PAWorld365.

Hiring volumes are rising, admin budgets are flat and candidates expect rapid, personalised feedback. The EU AI Act and GDPR tighten the rules on data handling, while GenAI promises huge efficiency gains. Organisations that can safely embed AI into talent workflows will secure scarce skills sooner and at lower cost.Worldline's early‑careers recruitment team needed to speed up hiring without compromising candidate experience or GDPR compliance. Rather than buying off‑the‑shelf software, they created proprietary GenAI agents that transcribe and summarise interviews, draft role profiles and automate follow‑up notes. The project began as a weekend experiment, grew through peer adoption and is now a blueprint for AI‑enabled productivity across HR. This session unpacks the practical build‑versus‑buy rationale, the low‑code platform choices, the guardrails that satisfied legal and data‑protection teams, and the change approach that turned hesitant recruiters into enthusiastic advocates.This session will explore:Why Worldline chose to build, not buy, GenAI tools for recruitment.The architecture: secure in‑house sandbox, open‑source framework and corporate LLM licences.Interview transcript summariser – saving 30–45 minutes per candidate and improving eye contact.Governance tactics: anonymisation, permission requests, and training to satisfy GDPR and the EU AI Act.Bottom‑up adoption: peer pilots, iterative prompt engineering and a cross‑HR think‑tank.Next horizons – extending GenAI to learning, onboarding and workforce planning.Learning outcomes:Calculate a realistic build‑versus‑buy case for AI in recruitment.Design a low‑code GenAI workflow that keeps all candidate data on‑premise.Write guardrails and user prompts that balance productivity with compliance.Run a grassroots pilot that converts sceptics into champions.Identify further HR processes where GenAI can unlock measurable value.Connect with Jonathan de KrygerConnect with Dan RileyGet in touch to discuss this episode, or anything else related to People Analytics World.