Data Analytics Guide

• HR Analytics Lifecycle: A five-step process encompassing question identification, data gathering, data cleansing, data analysis, and conclusion/improvement. • Question Identification: The first step in the HR analytics lifecycle, involving asking the right questions to understand issues impacting business strategy. • Data Gathering: The second step in the HR analytics lifecycle, involving collecting and selecting data from various sources (HR, business, external) to support research design. • Data Cleansing: The third step in the HR analytics lifecycle, focused on validating data to improve quality and optimize usability by making it integratable and interrogable. • Data Analysis: The fourth step in the HR analytics lifecycle, involving understanding and interpreting data through suitable statistical solutions and business acumen. • Conclusion: The final step in the HR analytics lifecycle, involving translating insights into tangible actions and improvements. • Justification (Phase): The basic, foundational, and reactive first maturity phase of HR analytics, with distributed data collection and rudimentary reporting. • Measurement (Phase): The proactive second maturity phase of HR analytics, utilizing advanced reporting capabilities such as metrics, scorecards, and dashboards. • Effectiveness (Phase): The third maturity phase of HR analytics, characterized by the use of sophisticated tools like strategic analytics and KPIs, with cohesive efforts for process improvements. • Value Creation (Phase): The fourth maturity phase of HR analytics, focusing on predictive models for genuine insights that produce cultural shifts and data-driven decisions. • Impact (Phase): The fifth and highest maturity phase of HR analytics, where HR provides insights that significantly impact business operations and achieve the true purpose of analytics.