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Rental Workflow Implementation-Case Study

This case study explains how we helped a rental business fix their daily operational problems, including delays in delivery, confusion in kit components, late invoicing, and messy return tracking. We redesigned their entire rental process in Odoo so their workflow became smooth, accurate and fast.

Project Overview

This project was for a company that runs a large rental operation. They rent out scaffolding, construction components, and kit-based materials. Their team already had a basic beta software, but nothing worked end-to-end. Every department had its own way of doing things, and operations were constantly getting stuck between sales, warehouse, planning, and accounts.

They asked us for one thing:

“Make the entire rental workflow run smoothly from lead to closure.”

This turned into one of the most detailed functional projects I’ve handled.

What Was Going Wrong

When we first looked at their process, it was functioning, but heavily manual and error-prone.

A few real issues:

  • Delivery challans were created late or with wrong components

  • Kit products were inconsistent; half the time items were missing

  • No automation for transporter assignment or e-way bill preparation

  • Customers received material, but branches updated the system late

  • Rental invoicing was completely dependent on manual updates

  • Return requests, damaged material, missing components — all tracked on paper

  • No clarity on who did what and when

  • Warehouse teams worked differently in each region

  • Planning team had no real-time tracking

  • Stock depletion was happening at the wrong time

  • Capital purchases and inter-branch movements had no common structure

  • Managers had to intervene daily just to keep the workflow alive

In short, operations were happening because of people, not processes.

What We Did:

We didn’t try to “force-fit” Odoo first.

We sat down with each team to understand how they actually worked.

1. CRM & Opportunity Flow

We mapped the entire lead → opportunity → conversion cycle.

Sales wanted something simple.

So we kept the CRM clean, and made sure once a deal was confirmed, it flowed straight into an actionable rental order.

2. Rental Order → Component Planning

This was the most complex area.

Kit products contain multiple parts.

Not every kit was available in the same warehouse.

Planning had to add/remove components based on availability.

So we redesigned:

  • Delivery creation logic

  • Component substitution rules

  • Inter-warehouse planning

  • Future fulfillment dates for unavailable items

  • Automatic and manual allocation options

This gave planners real control.

3. Dispatch & Warehouse Execution

This was chaotic earlier, with manual errors everywhere.

What we built:

  • A clear picking workflow

  • Quality check recording

  • Packing logic

  • Transporter assignment with auto-filled details

  • Auto-prepared e-way bill form

  • Status color coding (Green, Orange, Red) based on delivery date

  • Timestamp logging for every action

Warehouse staff finally had a single process to follow.

4. Customer Receipt & Digital Acknowledgement

Previously, acknowledgement came back on paper after 1–3 days.

We built an update flow where the branch team uploaded the signed challan, and filled receipt details in the system immediately.

This triggered the next phase automatically.

5. Rental Invoicing Automation

This was the backbone of the business.

Invoicing needed to start the moment customer officially received material.

We structured:

  • Start of rental billing

  • Monthly invoice cycle

  • Auto-continuation until returns were 100% complete

  • Stop-invoicing logic with timestamp and user tracking

  • Pending material value estimation (one-click check)

Accounts finally got predictable invoicing.

6. Return Management

Returns were the biggest mess because items came back in parts.

We created a controlled return workflow:

  • Return request approval by Sales/AR

  • Return challan creation for all components

  • Scheduling pickup in multiples of kit quantities

  • Warehouse verification of OK / Missing / Damaged / Excess

  • Automatic rental continuation for pending items

Every return became traceable.

7. Damage / Loss Handling

Earlier the customer blamed warehouse, and warehouse blamed customer.

No documented proof existed.

Now we built:

  • Damage recording

  • Excess items recording

  • Missing quantity calculation

  • Component-wise price visibility

  • Automatic invoice generation only for missing/damaged items

This removed arguments and stabilized cash recovery.

8. Transport Management

Transport invoices were being processed manually.

We mapped:

  • Transport challan upload

  • Multi-challan bill creation

  • Bill verification

  • Final booking and payment

  • Manager-level approvals

This connected operations with accounts smoothly.

9. Inter-Branch Transfers & Damage Sales Orders

We introduced approval-based internal transfers so no wrong movement happened between regions.

Also built a simplified damage sale order flow for items needing disposal or write-off.

10. Inventory Controls

We established stock audit approval workflow from task creation → verification → final posting.

This gave visibility and control at every step.

The Final Outcome

After Implementation, Here’s What Changed:

✔ Delivery delays reduced because color-coded statuses kept planners alert

✔ Stock depletion became accurate and traceable

✔ Transport and billing workflows became predictable

✔ Rental invoices were generated on time every month

✔ Lost/damaged item billing improved significantly

✔ No more paper-based tracking

✔ Every action had timestamp + user record

✔ Warehouse and planning teams stopped arguing

✔ Region heads finally got visibility without daily calls

✔ Customer disputes reduced because data and acknowledgements were clean

Most importantly, the company experienced process reliability for the first time.

The project didn’t just automate the rental cycle—it eliminated ambiguity, brought discipline, and made operations scalable.


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