As we have already mentioned in this space in other articles, the application of advanced analytical solutions has been used in many professional and academic areas with significant advances in productivity and assertiveness in the decision-making process. One of the areas that is beginning to explore this technology more effectively is the Human Resources (HR) department of companies.
Regardless of the context in which it operates, the HR departments of most companies face several challenges to maintain a motivated and productive team, including:
- Improving individual and collective performance levels of employees;
- Reducing risks in personnel allocation for critical company projects;
- Greater assertiveness in promotion processes;
- More precisely identifying opportunities for improvement through training or other HR actions; and
- Increasing trust in leadership.
As in other areas, people management is in permanent search of insights and evidence that can be useful and relevant to answer questions necessary to overcome these challenges. This process, known as data discovery, aims to improve the quality and assertiveness of decision-making processes at all organizational levels through:
- Analytical models for predictive analysis and machine learning
- Automation of processes involving data extraction, integration, and enrichment
- Spatial analysis
- Data visualization
The data discovery process is based on the idea of self-service and empowerment for managers, not only in HR but in all areas of the organization. In this sense, it is necessary to use appropriate tools and methods for each of the objectives listed above. The next post in this series on this blog will cover in more detail the components of the framework that can be applied in predictive analytics projects for HR.