The content of this page is currently only accessible to administrators. Please log in with your administrator account to view the content. Training: HR Analytics Show Progress Topic 1 – Introduction Topic 1 – Introduction Topic 2 – Frameworks Topic 2 – Frameworks Training: HR Analytics Welcome to this training on HR Analytics. This module will guide you through the key concepts of data-driven human resource management — from understanding why data matters in organizations to applying analytical frameworks that drive strategic decisions. The training is divided into two topics. In the first topic, you will explore why HR Analytics matters and how data differs from traditional decision-making. In the second topic, you will learn about the analytical frameworks — including the LAMP model and the HR Analytics Value Chain — that help organizations move from data to action. After completing each topic’s slides, you will be asked to answer a few questions to reinforce what you’ve learned. Next Topic 1 – Introduction Please navigate through the slides, take the time to understand the content, and internalize it to the greatest extent possible. Once you have completed the content, please proceed to the question section by clicking on “Exercises” below. You may refer to this introduction at any time. Formal vs. Real Organizations Organizational charts show us the formal structure of a company — who reports to whom, how departments are divided. However, the actual way an organization works is often very different from what the chart suggests. Informal networks, cross-departmental relationships, and actual communication patterns shape day-to-day reality. Data gives us the tools to understand this real organizational landscape, beyond the formal structure. This insight is the foundation of HR Analytics: by systematically analyzing people-related data, we can make better business decisions that reflect how the organization actually works — not just how it is supposed to work on paper. Digital Disruption: Data as the New Asset In the digital economy, data has become more valuable than physical assets. Consider the most influential companies of our time: Uber — largest taxi company, owns no taxis Airbnb — largest accommodation provider, owns no real estate Facebook — most popular media owner, creates no content Alibaba — most valuable retailer, holds no inventory Netflix — largest movie house, owns no cinemas These companies succeed because they harness data about people’s behavior to make smarter decisions. The main aim of HR Analytics: Making better business decisions by systematically analyzing people (human capital), who are key drivers of business outcomes. Source: “Strategic HR Analytics course”, Dr. Jan de Leede & Luuk Collou MSc. University of Twente (NL) Querying vs. Data Mining Querying means searching for answers to questions you already have. You define what you want to know and retrieve the answer. It is limited to your existing assumptions. Data Mining is different — it discovers patterns and relationships in data that you did not know to look for. Instead of asking a specific question, you let the data surface unexpected insights. This distinction is critical: querying confirms what you already suspect, while data mining can reveal entirely new knowledge. In HR Analytics, data mining allows organizations to discover hidden drivers of performance, turnover, and engagement. Source: “Strategic HR Analytics course”, Dr. Jan de Leede & Luuk Collou MSc. University of Twente (NL) The Beer and Diapers Story A famous example from Walmart illustrates the power of data mining: analysts discovered that young American men buying diapers on Friday afternoons also frequently buy beer — a correlation that no one would have discovered through traditional queries. The insight was not obvious. There was no prior hypothesis that linked beer and diapers. Only by mining large transaction datasets did this pattern emerge. The business response: Walmart relocated beer near the diapers section, resulting in a measurable increase in sales for both products. This story shows that the most valuable insights in data are often the ones you didn’t know to ask about. Source: “Strategic HR Analytics course”, Dr. Jan de Leede & Luuk Collou MSc. University of Twente (NL) Big Data Requires Big Theories (Huselid, 2016) More data does not automatically mean better decisions. According to Mark Huselid, three principles are essential: More data is not always better. Without a clear purpose, more data creates noise, not insight. Behavioral science theory matters. Moving from raw data to actionable knowledge requires understanding how and why people behave as they do. The biggest challenge is not data infrastructure. Knowing what to measure and how to measure it is harder — and more important — than building the data pipeline itself. This means HR Analytics is not primarily a technology challenge. It is a thinking challenge: before collecting data, you must have a clear theory about what drives the outcomes you care about. Source: “Strategic HR Analytics course”, Dr. Jan de Leede & Luuk Collou MSc. University of Twente (NL) Don’t Start with the Data One of the most common mistakes in HR Analytics is beginning with whatever data is available and asking “What can we find?” This approach rarely produces actionable insights. Mark Huselid’s principle is clear: “Don’t start with the data — start with the question!” The right order is: Define the business question clearly. Identify what information would answer that question. Collect and analyze the relevant data. Develop cause-effect understanding before thinking about statistics. Analytics does not always mean statistics. The key is conceptual clarity about what drives organizational outcomes — data and statistics are tools to test that understanding. Source: “Strategic HR Analytics course”, Dr. Jan de Leede & Luuk Collou MSc. University of Twente (NL) Please select a slide below to begin Use the numbers below to navigate between slides (1 = first, 6 = last). Click Exercises when you are ready to test your knowledge. 1 2 3 4 5 6 Back Exercises Please select a slide above to begin Exercises – Topic 1: Introduction Exercise 1: The Goal of HR Analytics What is the main goal of HR analytics?