The leading automotive manufacturing company Continental wants to reduce the attrition-ratio in Mexico. Together, we set up an analytics project to create transparency on attrition drivers, define target groups of attrition, and derive tailored, location-specific measures to reduce attrition.
„With the analytics of HRForecast, we were able to define location-specific measures tailored to our different employee clusters to achieve our attrition targets. Data Analytics is the future.“
Marco Galluzzi, HR Country Head Mexico
Questions to be clarified:
1. Validation of available data
In a data workshop, we identified relevant data sources. The key sources of interest are primary data and unstructured information derived from exit interviews with leavers. Then, we set up a data model to integrate the data.
2. Build attrition model
Machine-learning algorithms enable the extraction of attrition drivers from the unstructured exit interviews. Analytics algorithms are then applied to bring transparency into the data set and derive location-specific insights on the questions.
3. Measures workshop
In a joint on-premise workshop with HR leaders across the country, suitable measures for each target group are discussed and allocated to the locations. Then we defined attrition targets follow-up activities for each site.
Key insights & value-adds for the client
- Used the analytics results to derive location-specific measures tailored for the attrition clusters.
- created action-plans for follow-up activities
- turned unstructured exit interviews into valuable insights
- was able to simplify the understanding of different types of employees