Palantir Forecasting
Cutting-edge forecasting solutions with traditional & AI methodologies to determine the best forecasting model per stock keeping unit.
AI Forecasting
Our cutting-edge forecasting solutions employ a blend of traditional methodologies and artificial intelligence techniques to determine the most optimal forecasting model for each stock keeping unit (SKU). Our algorithms analyse individual SKU demand patterns and employ a range of forecasting models, encompassing ARIMA and advanced artificial intelligence time series analysis (AITSA) algorithms to identify the most suitable solution per SKU. Typically, our approach yields improvements ranging from 5% to 25% compared to traditional forecasting methods like ARIMA.
Intelligent Adjustment
When sufficient data is available – commonly the case with fast-moving items – our AI models excel in accurately forecasting seasonal and trend patterns. External occurrences, such as lock-downs, are seamlessly integrated into the models, enabling intelligent adjustment of demand patterns based on these known anomalies. Forecast accuracy can be further enhanced by incorporating internal and external regressors – variables that exert influence on demand.
Improved Efficiency
Improved forecasting accuracy empowers our clients to improve customer service levels through better inventory availability, while optimising their working capital investment in inventory by minimising buffer inventory levels – reduced uncertainty in demand leads to lower buffer stock, thereby improving efficiency and resource utilisation.