Staff Churn Prediction System

Mid-sized company with a large workforce

Project overview

The client faced a high staff churn rate, causing disruptions to operations and negatively impacting the company's bottom line. They sought a system that could predict which employees were most likely to leave the company and take proactive measures to retain

Project process

The challenge was to reduce staff turnover and retain valuable employees using a system that could predict staff churn.


Our team developed a staff churn prediction system that analyzed employee data from SAP and used machine learning models to identify patterns and predict which employees were most likely to leave.

Microsoft Azure, Data Factory, ADLS, Databricks, WebApp, and ServiceBus, Scikit-Learn, TensorFlow
6 people


The average employee turnover decreased by 10% in 2020 and a further 38% reduction in 2021, specifically among critical and key personnel. There was also a 5% decrease in overall turnover, resulting in significant cost savings for the company.

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