Inventory Exception Agent Workflow
Consolidate Shopify/order exports, supplier sheets, warehouse counts, refund logs, and sales velocity to flag low-stock and oversell risks, generate reorder suggestions, draft supplier emails, and provide a pre-PO verification checklist.
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Key Benefits
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Unified, timely inventory visibility
By ingesting and normalizing Shopify exports, order history, warehouse counts, refund logs, BOMs, and open POs (Steps 2–4), the agent creates a single unified inventory table with ATP, on-hand, damaged/held, inbound, and per-location details. This consolidated view surfaces true availability and depletion dates (Step 5), so operators quickly learn which SKUs and locations require attention instead of hunting across spreadsheets and storefront exports.
Data-driven reorder recommendations that respect supplier constraints
The agent computes sales velocity, reorder points, target stock, and suggested reorder quantities using configurable lookback windows, safety days, review periods, and lead times (Step 5). It then applies MOQs, case packs, and supplier lead-time rules (Step 5–7) to produce realistic, costed reorder suggestions and estimated days-of-cover. Users learn not only which items need replenishment but why and how much—accounting for seasonality, bundles/BOMs, and inbound quantities—reducing guesswork and over/under-ordering.
Fast, accurate supplier communication and cost summaries
For each supplier the agent groups reorder lines, calculates cost extensions and subtotals (Step 7), and drafts ready-to-send email templates with requested quantities, target ship dates, and confirmation requests (Step 8). Deliverables include per-supplier markdown drafts and CSV attachments (Step 9). This accelerates procurement workflows and teaches operators how consolidated calculations translate into purchase requests and supplier negotiation points.
Risk reduction through data-quality flags and a pre-PO verification checklist
The agent flags data issues (missing lead times, SKU mismatches, currency problems) and identifies low-stock and oversell risks with reason codes (Step 6). It generates a tailored verification checklist before issuing POs that walks operators through counts reconciliation, inbound verification, bundle checks, refund impacts, and capacity/budget review (Step 10). This enforces disciplined review, helps users learn common failure modes, and prevents costly automated mistakes.
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