Idle inventory is silent margin erosion. In stock-heavy Odoo deployments, working capital quietly gets trapped in items that haven't moved in months, warehouse bins fill with overstock ordered against optimistic forecasts, and lots creep toward expiry unnoticed. Odoo's native stock.quant, forecasted-availability screens and inventory valuation report tell you what you have and what it's worth today — but they don't age it, they don't flag what stopped selling, and they don't quantify the carrying cost of holding it. Finance asks "how much cash is stuck in dead stock?" and the honest answer requires exporting quants, joining them against stock.move history in a spreadsheet, and rebuilding the analysis every month by hand.

This is where a native Odoo install runs out of road, and where we build. Deadstock & Overstock Analytics is a purpose-built module (proper __manifest__.py, models.Model classes, ir.model.access.csv plus record rules for multi-company isolation) that computes movement velocity and aging directly from your stock.move / stock.move.line history and stock.quant positions. We classify every product-location (and, where you track it, every lot/serial) into bands — dead, slow-mover, healthy, overstock — using thresholds you set: days-since-last-outbound-move, rolling sales velocity, and stock-cover in days against consumption. Computed fields via @api.depends derive tied-up capital from standard or average cost, apply a configurable annual carrying-cost rate (storage, insurance, obsolescence, cost of capital) to estimate what the idle stock is costing you to keep, and compare on-hand quantity against a reorder/optimal level to size the overstock overhang. A liquidation view surfaces markdown and clearance candidates ranked by tied capital and age, so ops has a prioritized action list instead of a hunch.

Technically it ships as real Odoo, not a bolt-on. You get list/pivot/graph/search views (XML, with OWL where an interactive dashboard adds value) so users can slice aging by warehouse, product category, lot, or responsible buyer; a QWeb PDF "Deadstock & Tied-Capital" report for finance and management reviews; menu items and access groups wired through ir.model.access.csv; and optional ir.cron scheduled jobs plus automated actions that recompute the bands nightly and can flag or email when a product tips into the dead band. Everything is queryable over Odoo's XML-RPC / JSON-RPC API, so the same numbers can feed a BI tool or an external dashboard. It's built against Odoo 17.0, 18.0 or 19.0 for your exact edition — Community or Enterprise (on Enterprise we can surface the analysis alongside Inventory's own reporting and Studio-friendly models; on Community we deliver the full reporting stack natively without paid dependencies).

Because this is build-to-order, nothing ships blind. We start with a short scoping call to pin down your velocity windows, aging bands, costing basis and carrying-cost assumptions, then build the module against your data on a staging instance, run UAT with your finance and ops leads, and deploy behind a rollback plan. Typical delivery is one working week from confirmed scope depending on how many warehouses, lot-tracked products and edge cases (consignment, drop-ship, negative stock) are in play. You receive the installable source for your Odoo version, a git repository handover, technical and user documentation, a training session, and a post-go-live support window — so the analysis keeps running as your catalog and warehouses change.