Deadstock & Overstock Analytics for Odoo

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 2–4 weeks 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.