PRODUCTAutonomous Forecasting and Replenishment
Retail, MRO, Spare Parts supply chains need to be highly responsive.
Availability and product variety on shelf matters more than the cost of holding the inventory. The value of the inventory does not matter. Ordering costs are high. Imagine creating a purchase requisition of 55 lines items of MRO items or creating a replenishment order of 200 lines items for Retail.
You need a different approach to understand consumption/goods issue and replenishment.
Why pretend to forecast when you cannot? Because there is no ‘model’ to predict it in theory.
Spare parts, MRO Supplies or for that matter any product with intermittent and sporadic demand can’t be predicted with any known model. Not even with the modern machine learning models.
The solution? Do not forecast, just replenish based on ‘confidence bands and ‘Bayesian’ conditions.
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