Data Analytics in Human Capital Management

Program Overview

Organisations using data analytics in their Human Capital Management (HCM) activities are realising significant benefits and tilting the playing field in their favour. McKinsey & Co, a leading management consultancy cites an example where a company has reduced its retention bonuses by $20 million and its attrition rate by 50%, by using predictive behavioural analytics.
In this program delegates will study how Data Analytics can increase the productivity and effectiveness of Human Capital Management (HCM) function, discuss and review use cases of using Data Analytics in employee retention, succession planning and employee performance management, learn where to find Data Analytics sources relevant to HCM and perform exercises using Data Analytics to identify major workforce trends and their impact.

Learning Outcomes

Upon completion of this program, participants will:

  • Comprehend the business rationale for using Data Analytics in Human Capital Management (HCM)
  • Recognise various data sources and the mechanisms to access them
  • Evaluate the relevance of various technologies used in Data Analytics
  • Design and run different types of analyses and visualisations
  • Understand the success factors and potential roadblocks in Data Analytics initiatives
  • Provide a roadmap for the development of Data Analytics culture in HCM Teams
  • Create a business case for Data Analytics projects, including costings and expertise requirements

Intended Audience

This program has been designed for HCM Professionals requiring the skills and expertise to establish an HCM analytics and reporting framework enabling data-driven foundation in strategic, tactical and operational decision-making. The program would benefit HCM Professionals and Managers, business analysts, business partners and would also suit Payroll Professionals.

Program Level and Pre-requisites for Attending

Foundation level, no pre-requisites

Program Duration

2 days

Number of Attendees

Maximum 17 attendees

Training Methodology

A distinguishing feature of this program is its practical aspect. At the end of each module there is a practical exercise designed to reinforce the concepts of the module and to give participants a chance to “get their hands dirty”. The exercises are either scenarios where participants work in groups or individual tasks executed within a specially prepared software environment.

A specific module of the program is devoted to creating a Data Analytics project, which the participants will be able to use as a blueprint in their teams for a real-life Data Analytics initiatives.

Program Outline

Day 1

  • Registration, Introductions and Housekeeping
  • Data Analytics in the Organisation
  • Data vs Information vs Actionable Insights
  • Data Analytics in HCM – The Business Value
  • Overview
  • Benefits and Limitations
  • Potential areas of deployment
    • Talent Retention
    • Risk Management (see Appendix A for a real-life example)
    • Performance Management
    • Recruitment and Staffing
    • Training and Development
  • Use Case Review and Group Exercise
  • Data Sources and Locations
  • Enterprise Systems in the Organisation
  • External Sources of Information
  • Data Source Access
    • Issues, Limitations and Practical Advice
  • Group Scenario Exercise
  • Data Analytics in HCM – Design and Execution
  • Overview
  • Tools for Data Analytics
  • Data Analytics in HCM – Use Cases
  • Use Case Review and Group Discussion

Day 2

  • Data Analytics in HCM - Design and Execution (cont.)
  • Analytics Design Process
    • Overview
    • The 7-Step Approach
  • Practical Work
  • Visualization and Reporting
  • Introduction to Data Storytelling
  • Essentials of Impactful Visualizations
    • Overview
    • Main Principles
    • Tools
  • Reporting and Presentation of Results
  • Practical Work
  • Building a Data Analytics Culture - The Roadmap
  • Overview and Steps Involved
  • Practical Suggestions
  • Group Exercise
  • Success Factors and Stumbling Blocks
  • Required Skillsets
  • Legal and Privacy Considerations
  • Delivery Approach and Stages of Experts’ Involvement
  • Future Trends in Data Analytics
  • Big Data
  • Artificial Intelligence
  • Group Workshop: Running a Data Analytics Initiative
  • Defining the Business Need
  • Discovering Necessary Data-sources
  • Establishing Required Resources/Expertise
  • Costing
  • Program Review, Q&A, Comments

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