Demand forecasting and reordering requires operations teams to manually export sales data, calculate moving averages, and cross-reference supplier lead times across multiple spreadsheets. This repetitive, calculation-heavy work consumes 2+ hours per cycle and delays reorder decisions by days.
Automation analyzes historical sales patterns, applies seasonal adjustments, and generates purchase orders automatically. The operations team reviews and approves recommendations in minutes instead of hours, reducing stockouts and excess inventory.
The full workflow, from trigger to completion.
The automation runs on a weekly schedule or is triggered when new sales data is available. It pulls the past 7 to 14 days of sales by product variant.
The automation queries API to retrieve sales transactions and current inventory levels for all SKUs. Data is normalized and stored for analysis.
The automation analyzes historical sales patterns, applies moving averages and seasonal factors, and calculates recommended reorder quantities and timing based on supplier lead times.
The automation checks if any SKU has fallen below its reorder point or if demand forecast suggests imminent stockout. If yes, proceed to create PO. If no, log the forecast and wait for next cycle.
For SKUs flagged for reorder, the automation generates a purchase order with quantities, supplier, and expected delivery date.
The purchase order is sent to the supplier via email using a pre-configured template. A copy is logged in the reorder tracking system.
The operations team receives a notification summarizing the forecast, reorder quantities, and expected delivery dates for visibility and approval.
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