A leading IoT based real-time location systems (RTLS) software and service provider for healthcare organizations wanted to improve their demand forecasting capabilities by analyzing medical and hospital equipment stocking levels. The aim was to leverage historical information across categories, such as clean storage, patient rooms, and other locations to deliver accurate forecasting.

Daitrix analyzed and understood high-level trends with IoT input data to arrive at the overall stock trend. We applied layered time-series analysis, breaking the data down into trend, seasonality, and other key components. Our solution also helped the client to drill down across categories to refine results by segments for trend analysis to accommodate different patterns. We also generated Periodic Automatic Replacement (PAR) level prediction appropriate to prevent overstocking or understocking.