Point-of-sale (POS) information fails to measure actual demand most likely because data about lost sales cannot be captured due to:
Incomplete Data: POS data reflects only the sales that were actually made, not the sales that were lost due to stockouts or other issues. This leads to an underestimation of true customer demand.
Stockouts: When products are out of stock, potential sales are lost. Since POS systems do not record these lost sales, they cannot provide a complete picture of actual demand.
Customer Behavior: Customers may go to competitors or defer their purchases when items are not available, further obscuring true demand from the POS data.
Demand Estimation: Accurate demand forecasting requires an understanding of both actual sales and potential lost sales. Without data on lost sales, companies might misjudge the demand and make suboptimal inventory decisions.
Holidays (Option A) can disrupt typical sales patterns but are accounted for in demand planning. Inaccurate inventory levels (Option B) can cause stockouts but do not directly explain why POS data fails to measure demand. Lag time (Option C) affects the timeliness of data but not its completeness in capturing lost sales.
References
"Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain" by Robert A. Davis.
"Inventory Management and Production Planning and Scheduling" by Edward A. Silver, David F. Pyke, and Rein Peterson.
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