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Automation of Order Management

Learn how a global manufacturing organization streamlined order management with AI-driven automation, reducing manual effort by up to 75% while improving accuracy and cycle times.

January 19, 2026
5 minute read
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Overview

The client processes 25,000+ orders per month across regions through emails, portals, and EDI. Orders require validation, pricing checks, credit approvals, and delivery-date commitments before the data is updated on multiple ERP systems. This was resulting  struggles with operational inefficiencies in its Order Management (OM) function.

Business Challenge

The Order Management process was highly manual and fragmented:

  • Manual PO validation and ERP entry led to errors, duplicates, and incomplete orders
  • Delivery-date mismatches due to lack of real-time coordination
  • Heavy reliance on email-based communication across siloed teams
  • Limited visibility into order status, impacting customer experience and responsiveness

The Solution

An AI-driven order processing framework was implemented to streamline and modernize the OM function.

Key elements of the solution included:

  • Automated PO extraction and validation
  • Autonomous ERP order creation in multiple ERPs.
  • Intelligent workflows for inventory availability and credit checks
  • GenAI-powered communication for automated acknowledgements and proactive customer updates

This approach demonstrates how Intelligent Automation  and AI & Data Engineering can be applied to streamline complex order management workflows and improve operational efficiency at scale.

Business Outcomes

  • 60–75% reduction in manual effort
  • ~40% faster order cycle time
  • 98%+ order accuracy and faster credit/contract checks
  • 50–60% reduction in internal email loops
  • Automated acknowledgements and proactive updates

Summary

The organization addressed highly manual, error-prone order management operations through a domain-led transition, strong governance, and AI-driven automation. This reduced manual effort, improved accuracy, strengthened cross-functional alignment, and enabled faster, more responsive customer interactions.

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