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Workforce Intelligence and HR Analytics Master Class



HR measurement is growing quickly both in importance and also in the number of new insights into how to do it. These include the creation of new standards, new analytical tools and approaches, and the opportunities, as well as the challenges, provided by big data. While it is very useful to have these inputs, their sheer number means that HR practitioners increasingly find it difficult to know where to start. In this cutting-edge master class, we will showcase the best way to cut through the noise to focus ever more clearly on what drives organizational success,


This intensive three-day course will teach you how to properly align human capital analytics with business and HR strategies and leverage the data you have to build and deliver workforce and HR metrics that will improve results. Using a provided framework and roadmap, HR professionals will take in the value of evidence-based measurement and decision-making. Learn how to use human capital analytics to support your organization’s strategic and operational goals and provide decision-makers with greater insight into workforce-related considerations.


Section 1 

  • Introduction – HR Metrics Scope & Basics
  • The Human Capital Framework
  • Linking Strategy to Performance Through Analytics
  • Linking Human Capital to the Business Through Analytics
  • Aligning HR Metrics to Strategic and Business Objectives
  • The Challenge of Measuring Human Capital
  • The Most Important Metrics for Human Capital
  • HR Competencies & Analytics
  • HR Transformation & Organizational Analysis
  • Metrics for M&A, Reorganisation, & Downsizing
  • Total Cost of Workforce – Controlling cost to impact bottom-line
  • Management Span of Control (MSC) – Optimizing Organisational Structure for Results
  • Compliance & Risk Analysis Reporting
  • Case Study: Building out Analytics to guide Enterprise Change
  • Case Study: HP – Inventing the future workforce
  • Integrated Talent Management
  • Integrated vs. Best-in-class Talent Management
  • Using Analytics to Manage Talent Management
  • The Case for Data-Driven Talent Management
  • Building & Managing the Talent Management Index (TMI)
  • Talent Intelligence (TI) – Moving from Analytics to Decisions
  • Case Study: Ingram – Using TI to manage Turnover hidden cost

Section Two

  • Leveraging Analytics to Build & Maintain Performance Management
  • The Corporate Scorecard
  • The HR Department Scorecard
  • The Workforce Scorecard
  • Using Analytics to Optimize the Workforce Scorecard
  • Tool & Exercise: Building & Managing the Workforce
  • Evidence-Based Decision Making
  • Using Analytics to Identify Critical roles & skills to Execute Strategy
  • Analytics Maturity Progression
  • Aggregating & Analysing Data
  • Workforce Intelligence Services
  • Linking Workforce Planning
  • HR Linkage Framework
  • Case Study: PG & E – The Role of Analytics in Workforce Planning
  • Developing the Workforce Analytics & Scorecard Guide
  • Conclusion
  • Takeaways
  • Localizing the Experience
  • Action Planning



  • Why what we measure in HR is so disconnected from what adds value
  • Why a human capital scorecard provides the best basis for measuring what we do in HR
  • Different forms of HR scorecard and why this needs to be based on a strategy map
  • Different starting points and types of measures in the strategy map depending upon the level of value involved
  • Calculating and discussing ROI based upon the strategy map and scorecard
  • Using the strategy map and scorecard to underpin analytical approaches
  • Align workforce metrics with business strategy, goals, and objectives.
  • Align HR metrics with critical HR objectives and initiatives.
  • Determine the right data to collect.
  • Build and execute your implementation plan.
  • Obtain management and stakeholder support and involvement


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Course Curriculum

Workforce Intelligence & HR Analytics
HR Analytics1 Details 00:00:00
HR Analytics 2 Details 00:00:00

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  • 89,250.00 10,000.00
  • 180 Days
  • Course Certificate

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