Industry: Government

Data-driven People Analytics leading to significant savings in operational cost and improved efficiency at AFIP

Benefits & Results

Reduction in overtime; Enhanced Human Resource Management; Compliance with labor legislation; Operational efficiency and cost reduction; Strengthened data culture; Continuous improvement and innovation; Data security and reliability

Significant savings in operational costs; Improved employee productivity and satisfaction

Background

AFIP is a renowned private nonprofit and philanthropic institution in the medical diagnostics sector. They faced significant challenges in managing employee data, dealing with excessive overtime, high turnover, absenteeism, medical leaves, workplace accidents, hiring of Persons with Disabilities (PCDs), and compliance with labor laws. The volume of data due to their core business added complexity to data management and analysis.

Challenges

Issue Identification: AFIP faced significant challenges in managing employee data. The main issues included: 1. Excessive overtime; 2. High employee turnover rate; 3. Frequent employee absences; 4. Managing absences due to health reasons; 5. Frequent workplace accidents; 6. Challenges in hiring individuals with disabilities; 7. Compliance with labor laws (CLT regime); Issue Impact: These challenges led to high operational costs, low productivity and efficiency, impact on employee satisfaction and retention, risk of non-compliance with labor regulations, and limitations on organizational growth

Solution

NowVertical's Role: NowVertical implemented a unified data platform collecting data from various source systems capturing employee information. This involved transforming data into different metrics and KPIs, generating actionable insights for the Human Resource team to improve productivity and efficiency. They developed dashboard visualizations to facilitate decision-making processes for the HR team and implemented data science models to predict overtime propensity, allowing the HR team to take preemptive actions

Implementation

Implemented a Snowflake data platform integrating all data sources capturing transactional and behavioral attributes of employees; Enabled cloud modernization to ensure scalability and security in the data infrastructure; Developed data science models in Python for predictive analysis

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