HR analytics entails evidence based decision making about people issues in an organization. The increasing use of technology in organizations generates a huge amount of data about people, processes, business and context. This should, ideally, enable a detailed analysis of HR policies, practices, procedures of the organization and help ascertain whether it aligns with the organizational strategy and purpose.
The areas covered under HR analytics include, but are not restricted to, descriptive analysis (for example, analysing the attrition data to derive insights about retention strategies) and predictive analysis (for example, analysing performance data to predict the future performance of a newcomer). The programme indeed sets the way for assessing, designing and transforming HR systems and processes based on solid evidence and data, thus, enhancing the alignment between HR and strategy.
For more information or any questions, contact Suman Verma: suman-exed@iima.ac.in | +91 92277 93191
22 August 2022 to 24 August 2022
In Person
IIMA Campus
85,000
Pay Now
A mix of senior, middle and junior managers involved in HR systems design and implementation in organizations and having key decision making responsibilities.
It is widely recognised that people-related decisions are crucial in shaping the organization’s performance. When organizations increase their investment in IT systems, it helps collect detailed data, enabling them to take evidence-based, informed decisions on people issues. The importance of HR analytics, however, extends much beyond data analysis and the application of statistical tools. With their domain expertise and understanding of the linkages between HR systems and organization strategy, HR professionals are in the right place to harness the potential of HR analytics for making strategic decisions.
The programme aims at developing the capabilities of the participants to understand and employ HR analytics for various people-related decisions in organizations.
• HR systems and data based decision making • Data collection-The role of Qualitative and Quantitative data • Posing the right questions and understanding the approach to the solution • Understanding analytical tools and their application • Linking the data insights to the domain expertise • Data visualisation and communication with stakeholders
