People analytics
In an ever-changing workplace and a context of intense competition to attract and retain talent, organizations need to improve how they manage talent. As a result, collecting and analyzing employee data has become a priority for key market players.
People analytics
The demand for new, more personalized experiences in the workplace requires more precise, individual-centric management, adding to the complexity of talent management. New challenges such as diversity, inclusion and employee well-being also need to be addressed.
Organizations are responding to these challenges by investing in the development of advanced people analytics capabilities.
People analytics development focuses on providing solutions for different HR areas, such as recruitment, talent and culture. Some of these solutions are:
- Data visualization for decision making, dashboards or reporting for specific purposes such as skills mapping or pay equity.
- Solutions to automate HR processes, such as the collection and standardization of resumes or the development of LLMs for employee management.
- Advanced analytical models to improve decision making across different employee groups, such as identifying specific profiles to enrich the talent map or managing high-value employee churn.
- Capturing and leveraging the voice of the employee to identify behaviors and anticipate mitigating actions.
Over the past few years, Management Solutions has evolved its People Strategy practice, developing new capabilities in response to market needs and addressing three main types of projects:
- Design and configuration of the People Analytics function, which includes defining the scope of the function and adapting it to the organizational model, resolving issues such as the framework for action and consequently deciding whether the model should be centralized or decentralized, and developing reskilling plans to build internal capabilities within the HR functions themselves.
- Building an “Employee 360-degree View” by creating information repositories that consolidate all employee data from various structured and unstructured sources.
- Design and implementation of use cases to develop solutions of different types and complexity including reskilling effort measurement; a training recommender; predicting employee success in new obs, e2e recruitment automation; identifying employee attrition risk, etc.