An American discount department store chain enhances its labor forecasting and operational efficiency with an AI Time Series Machine Learning (ML) Model.
SITUATION
Our client struggled to optimize staff allocation without infringing on union-driven shift regulations in one of their largest distribution centers. Scheduling was handled manually by managers using a basic Excel spreadsheet. Their goal was to enhance labor forecasting methods, mitigating costs associated with excessive overtime and insufficient voluntary time off. They chose to leverage Everforth Apex System’s expertise in data analytics and workforce management to develop a predictive forecasting model. Through this strategic initiative, the client would gain detailed staffing thresholds, enabling informed and cost-efficient scheduling decisions. This approach would not only decrease unwarranted financial expenses but also set the stage for the client to achieve sustained operational success and economic efficiency.
Labor Forecasting Period Extended From 4-5 Weeks to 26 Weeks
Everforth Apex began developing a comprehensive Time Series ML Model to enhance forecasting and operational efficiency within the client’s distribution centers. Our specialized project team, bringing together expertise in data science and engagement management, utilized a combination of past and current data analysis. This approach allowed us to understand the factors driving demand during a particular shift, leading to the creation of a tailored approach for planning staffing needs based on the predicted demand of that individual shift. Our methodology is meticulously designed, incorporating a broad array of data points—from environmental variables to workforce performance metrics—integrated through advanced machine learning models. The outcome is a precise prediction of the staffing levels required to ensure customer satisfaction and operational quality. We then provided recommendations on next steps to scale and incorporate this into further distribution centers.
RESULTS
The Everforth Apex solution significantly enhanced labor forecasting accuracy, culminating in considerable reductions in overtime and overstaffing expenses, estimated to save 14 unnecessary overtime shifts weekly. We also extended the forecast period from 4-5 weeks ahead to a substantial 26 weeks, augmenting our client’s financial planning capabilities. This solution was robust and also streamlined operations by removing the manual transfer of data. Our refined forecasting model not only addressed understaffing and overstaffing and left our client union-compliant, but also halved the mean absolute percentage of errors made in scheduling to approximately 5%, directly benefiting our client’s bottom line.
