Introduction

In today’s data-driven business environment, organizations are increasingly relying on analytics to improve HR operations and enhance overall workforce management. HR operational analytics focuses on applying data-driven insights to HR functions such as recruitment, employee performance, training, retention, and productivity. This course is designed to equip HR professionals with the knowledge and practical skills required to analyze and interpret operational HR data effectively. Participants will learn how to leverage HR analytics tools and techniques to make informed decisions, optimize HR processes, and drive better organizational outcomes.

Objectives

By the end of this 5-day course, participants will:

1. Understand the role of HR analytics in operational decision-making and its impact on business outcomes.
2. Learn how to collect, clean, and analyze HR data from various sources.
3. Gain proficiency in using HR analytics tools and platforms to drive insights from operational data.
4. Understand key HR metrics and KPIs, and how to use them to optimize HR practices.
5. Learn how to present HR data in a compelling way to stakeholders and support data-driven decision-making.
6. Develop strategies for applying HR analytics to improve talent management, employee engagement, and workforce productivity.

Who Should Attend?

• HR managers, analysts, and professionals responsible for HR data collection, analysis, and reporting.
• HR directors and executives seeking to integrate analytics into HR strategy and decision-making.
• Data analysts and IT professionals supporting HR systems and data analytics platforms.
• HR business partners who need to understand how operational data can be leveraged for organizational performance.
• HR professionals interested in enhancing their analytical skills and moving toward data-driven HR practices.

5-Day Course Outline

Day 1: Introduction to HR Operational Analytics

• What is HR Operational Analytics?
  • Defining HR operational analytics: the role of data in HR decision-making.
  • Differences between HR operational analytics and strategic analytics.
  • Key goals and benefits of HR operational analytics: improving efficiency, reducing costs, and enhancing performance.
• The Role of Data in HR Operations
  • Identifying the key HR operations areas that benefit from analytics: recruitment, performance, retention, and training.
  • Understanding the data sources: HRMS, ATS, payroll systems, employee surveys, performance management tools.
  • The HR data lifecycle: from data collection to data analysis and reporting.
• Introduction to Key HR Metrics and KPIs
  • Defining common HR metrics: time-to-hire, cost-per-hire, turnover rate, employee satisfaction, and more.
  • How KPIs link to business objectives and drive operational performance.
  • Selecting and prioritizing metrics for HR analytics projects.
• Workshop: Identifying key HR operational challenges in your organization and mapping them to potential analytics solutions.

Day 2: Data Collection, Cleaning, and Preparation for HR Analytics

• Data Collection Methods
  • Overview of primary HR data sources: employee records, performance reviews, surveys, exit interviews.
  • Automating data collection processes: integrating HR systems with data analytics tools.
  • Ensuring data consistency, quality, and accuracy: the foundation for reliable analytics.
• Data Cleaning and Preparation
  • The importance of data cleaning: handling missing data, correcting errors, and dealing with inconsistencies.
  • Data normalization and transformation: preparing data for analysis.
  • Data privacy and ethical considerations in HR data collection and analysis.
• Data Governance and Security
  • Ensuring compliance with data protection laws (GDPR, CCPA, etc.).
  • Best practices for data security and protecting sensitive employee information.
  • Roles and responsibilities for data governance in HR analytics.
• Workshop: Cleaning and preparing sample HR data for analysis (e.g., employee turnover data).

Day 3: Tools and Techniques for HR Data Analysis

• Introduction to HR Analytics Tools
  • Overview of popular HR analytics software: Tableau, Power BI, Excel, SAP SuccessFactors, and others.
  • Understanding the capabilities of HR analytics tools: reporting, visualization, predictive analytics.
  • Choosing the right tool for your organization’s needs: scalability, ease of use, integration.
• Analyzing HR Data
  • Descriptive analytics: summarizing historical data to understand trends and patterns.
  • Diagnostic analytics: identifying the causes of HR-related issues (e.g., high turnover rates).
  • Predictive analytics: using historical data to forecast future trends and make proactive decisions.
  • Prescriptive analytics: recommending actions based on predictive insights (e.g., recruitment strategies to reduce turnover).
• Data Visualization for HR
  • Best practices for presenting HR data visually: charts, graphs, and dashboards.
  • How to create compelling data visualizations for different audiences (HR teams, executives, managers).
  • Using data visualization to highlight key HR insights and drive action.
• Workshop: Analyzing a sample HR dataset using a selected analytics tool and presenting insights through a dashboard.

Day 4: Applying HR Analytics to Operational Areas

• Recruitment Analytics
  • Analyzing time-to-hire, cost-per-hire, and candidate quality metrics.
  • Predicting future hiring needs and optimizing recruitment channels.
  • Identifying trends in candidate selection to improve the hiring process.
• Performance Management Analytics
  • Using data to evaluate employee performance: productivity, engagement, and development.
  • Identifying high performers and underperformers for targeted interventions.
  • How to use analytics to enhance performance reviews and feedback processes.
• Employee Retention and Turnover Analytics
  • Identifying factors contributing to employee turnover: culture, management practices, compensation.
  • Predicting turnover risk and taking preventive actions (e.g., retention programs).
  • Using analytics to improve employee engagement and satisfaction.
• Training and Development Analytics
  • Analyzing training effectiveness: ROI, completion rates, and employee performance post-training.
  • Identifying skill gaps and aligning training programs with organizational needs.
  • Tracking employee development and career progression using HR data.
• Workshop: Conducting a deep dive into one of the operational areas (e.g., recruitment or performance) using HR analytics.

Day 5: Communicating Insights and Driving Action with HR Analytics

• Building HR Analytics Reports and Dashboards
  • Designing effective HR reports and dashboards: choosing the right metrics and visuals.
  • Creating executive-level reports to align HR insights with business strategy.
  • Sharing insights with non-technical stakeholders: how to communicate complex data clearly.
• Driving Decision-Making with Data
  • Using HR analytics to inform strategic decisions: workforce planning, compensation, benefits.
  • How to influence stakeholders to act on data-driven insights.
  • Balancing data insights with qualitative factors (e.g., employee feedback, culture).
• The Future of HR Analytics
  • Emerging trends in HR analytics: AI, machine learning, and automation in HR operations.
  • Preparing for the future of work: the role of HR analytics in remote work, gig economy, and workforce flexibility.
  • Building a culture of continuous improvement through HR data.
• Workshop: Presenting HR analytics insights to stakeholders in a simulation, demonstrating how to drive action based on data.

Final Assessment and Certification

• Assessment: A comprehensive exam covering all aspects of HR operational analytics, including data collection, analysis, application, and communication.
• Certification.