Good afternoon everyone. I’m currently reviewing how we handle demand forecasting in our distribution network, and it’s been eye-opening. During the holiday season last year, our forecasts were completely off — we underestimated demand for fast-moving items and overestimated niche products. It caused delays and extra storage costs. I recently read this piece that breaks down modern approaches to forecasting and how companies combine historical data with predictive analytics: https://www.trinetix.com/insights/demand-forecasting-in-supply-chain. It made me question whether our current tools are too rigid. Has anyone here shifted from traditional forecasting models to something more adaptive? Did it actually improve accuracy?