Forecasting Future Staffing Needs
Problem
Accurately predicting the future staffing requirements is challenging due to varied demands across skill sets and geographic locations.
Consequences of inability to anticipate precise staffing requirements are:
Solution Overview
Accurately predicting the future staffing requirements is challenging due to varied demands across skill sets and geographic locations.
Derive Seasonality, Historical Demand, Economic Indicators, Business Trends, Population demographics, local events.
Time Series (ARIMA, Prophet) | Machine Learning (GBM, RF)
Split data into training and validation sets. Validate the models using appropriate performance metrics such as RMSE, Accuracy, etc.
Deployment for future predictions. Continuously monitor model performance and retrain periodically with updated data to improve accuracy.