Accurate measurement of how much the customers will buy is ‘Step Zero’ for ensuring optimal demand fulfillment via replenishment. Explore the critical role accurate demand forecasting plays in replenishment optimization
Reduced
Out-of-Stock Events
Stock—outs account for USD 15—20 billion per year in lost sales in the US food industry alone.
Accurate forecasts anticipate demand fluctuations, ensuring the right amount of stocks at all times and efficiently mitigating customer needs.
Minimized Overstock
and Wastage
Annually, $163 billion worth of inventory is discarded due to oversupply and damage.
ML-based forecasting is highly accurate across all levels, categories, locations, SKUS, etc, and eliminates over-ordering, minimizes storage costs, and reduces the risk Of expired products.
Improved Profitability
Inaccurate demand forecasting can inflate inventory holding costs by up to 30%, eroding profit margins.
AI-based demand forecasting accounts for supply chain disruptions and demand fluctuations to suggest optimal inventory levels, thereby boosting profitability.
Data-Driven
Replenishment
Decisions
A whopping 70-90% Of stockouts are caused by poor stock replenishment.
AI/ML—based forecasting facilitates data-driven replenishment decisions in real time by factoring in external as well as internal factors.
Enhanced
Supply Chain
Efficiency
AI-powered forecasting can reduce supply chain errors by 30 to 50%, shrinking lost sales by 65% and warehousing costs by 10 to 40%.
Intelligent dernand forecasting solutions streamline supplier communication and collaboration, leading to smoother order fulfillment and reduced lead times.