Odoo Data 101: The Tables Every Operator Should Know

The Essential Odoo Tables Every Operational Manager Should Know

Odoo is a powerhouse ERP — flexible, modular, and rich with operational data. But if you’ve ever opened the database behind the scenes, you know the truth: it’s massive. Hundreds of tables, thousands of fields, deeply interlinked. For analysts, it’s a playground. For operational managers who just need quick answers, it’s a maze.

The irony is simple: You have all the data you need to make strong, data-driven decisions — but it’s buried under schema complexity.

This guide breaks down the critical Odoo tables and fields that matter most for operations in supply chain, retail, logistics, manufacturing, and B2B commerce. No SQL expertise required. No noise. Just the essentials.

Let’s make Odoo usable for real-world decisions.

1. Customers & Partners: The Foundation of Every Workflow res_partner

If you manage orders, deliveries, suppliers, or customers, this is the first table you touch. res_partner is Odoo’s universal contact table — customers, vendors, drivers, franchisees, branches, everyone.

Key fields operational teams rely on:

id – the universal relationship key across the ERP

name – the customer/vendor name

customer_rank / supplier_rank – signals the role of the partner

street, city, zip, country_id – operationally critical for routing and delivery

phone / email – essential for support and coordination

active – flags churned or blocked customers

company_id – vital in multi-company setups

Why it matters: Everything ties back to res_partner. If data here is messy, nothing else downstream is clean — deliveries, invoices, orders, routing, segmentation… all suffer.

With an AI Odoo assistant like Treeo, users can simply ask: “Show me all active customers who haven't ordered in 30 days.” And get instant results without digging into joins.

2. Sales & Order Lifecycle: The Heartbeat of Operations sale_order & sale_order_line

These two tables track every commercial transaction and all product-level details inside each order.

sale_order (header-level data)

Important fields:

id

partner_id – link to the customer

date_order – order timestamp

state – draft, confirmed, delivered, cancelled

amount_total – financial value

This is your main table for revenue trends, order cadence, customer segmentation, and churn analysis.

sale_order_line (item-level data)

Important fields:

order_id – links to sale_order

product_id

product_uom_qty – quantity ordered

price_unit

price_subtotal

Why these matter: Operational managers need answers to daily questions like:

Which products are moving fastest?

Which customers are increasing or decreasing order size?

What’s the real reason behind churn?

Instead of running SQL, Treeo can answer natural-language questions instantly — a major upgrade in business intelligence workflows.

3. Inventory & Stock: The Reality Check on Operations

If sales is the “promise,” inventory is the “truth.” Stock issues cause delays, cancellations, customer churn, and operational firefighting.

The must-know tables:

stock_quant — Real-Time Physical Stock

Key fields:

product_id

location_id

quantity – available stock

reserved_quantity – allocated to open orders

company_id

This table is your live truth for availability.

stock_move — The Log of Stock Movement

Tracks every flow: receipts, internal transfers, deliveries, returns.

Key fields:

product_id

location_id → location_dest_id

state – draft, done, cancelled

reference – often ties back to sale orders or purchase orders

Operational impact: These tables explain:

Why a delivery failed

Why a SKU is unavailable

Whether a product is overstocked or understocked

Whether procurement is falling behind

Treeo's AI analytics engine can run instant stock breakdowns and even forecast impending stockouts.

4. Deliveries & Fulfillment: Where Operations Win or Lose stock_picking

If you are in logistics, retail fulfillment, or distribution, this table is your best friend.

It represents the delivery document.

Key fields:

id

partner_id – delivery customer

scheduled_date

date_done

state – waiting, assigned, done, cancelled

picking_type_id – delivery, receipt, internal

Operational managers use this to track:

SLA performance

Delays

Failed deliveries

Bottlenecks in warehouse workflows

stock_picking_type

Defines the picking category (delivery, receipt, internal transfer). Useful for filtering performance by operation type.

Why fulfillment tables matter: Most customer complaints originate here. If sales is upstream and inventory is the middle, fulfilment is the moment of truth.

Treeo can automatically analyze this data to surface:

Routes with the highest delay rate

Drivers or locations correlated with SLA breaches

Weekly operational performance trends

That’s real-time analytics applied to operations.

5. Products: The Operational DNA of Your Business product_product & product_template

In Odoo, product data is split into two layers:

product_template (shared properties)

Key fields:

name

categ_id

type – storable, consumable, service

uom_id

product_product (variant-specific properties)

Key fields:

barcode

default_code

active

tracking

Why it matters: Accurate product data is essential for procurement, demand planning, price updates, promotions, and warehouse operations.

With an AI analytics assistant, operators can ask:

“Which category is causing the most cancellations?”

“Show me top products by margin last 14 days.”

— without navigating Odoo’s schema.

Final Thoughts: Odoo Data Doesn’t Have to Be Hard

Most operational leaders don’t struggle because Odoo lacks data. They struggle because Odoo has too much data — and it’s hard to know where to look.

By focusing on these core tables:

res_partner

sale_order / sale_order_line

stock_quant / stock_move

stock_picking

product_product / product_template

…you unlock 80% of the insights needed to run day-to-day operations confidently.

And with a tool like Treeo — built on top of AI Odoo, AI analytics, and instant business intelligence — you remove the technical barrier completely.

Operational managers no longer need SQL. No more waiting for analysts. Just quick, reliable answers that drive real, data-driven decisions.

Want to turn Odoo into a decision engine?

Try Treeo — the AI analytics assistant that lets anyone chat with Odoo data, automate insights, and make smarter decisions in seconds.

Book a demo and make your Odoo data finally work for you.