/ Case Studies / Removing Manual Touchpoints from Order Processing Case Studies Removing Manual Touchpoints from Order Processing How a Metals Distribution Company Expanded AI-Powered Order Automation Across North America Critical Issue Order processing is one of the most critical operational functions within manufacturing and distribution organizations. As order volumes increase and customers use multiple submission methods, manual review requirements can create inefficiencies, increase processing costs, and limit scalability. A large metals and industrial products distributor had already begun automating portions of its order-entry process but wanted to continue improving automation accuracy and expand automation capabilities across additional business units and regions. The organization sought to reduce manual intervention, process a wider range of order types, and extend automation capabilities into its Canadian operations while maintaining business continuity. The company needed a practical path toward greater straight-through processing while accounting for the realities of complex order management, multiple warehouse environments, cross-border operations, and bilingual business processes. Customer Profile A North American metals distribution and industrial products organization with complex order management requirements across multiple business units and geographic regions. The company relies on Microsoft Dynamics 365 and related business systems to manage customer orders, fulfillment, and operational workflows. Key Problem The organization wanted to improve the accuracy and effectiveness of an existing order automation solution while expanding automation coverage across additional order types and regions. In particular, leadership sought to reduce manual order handling, automate orders submitted without attached purchase orders, and extend automation capabilities into Canadian operations. Achieving these objectives required a combination of artificial intelligence, business process automation, data validation, and operational alignment across multiple teams and systems. BUSINESS CHALLENGES Order Automation Accuracy Limitations While the organization had already implemented automated order processing capabilities, certain order scenarios continued to require manual review. The business wanted to improve automation accuracy and move closer to a “human out of the loop” model for a larger percentage of inbound orders. Expanding Automation to New Order Types Some customer orders arrived in email messages without attached purchase orders, creating an additional layer of complexity that existing automation processes were not designed to address. The organization needed a way to capture and process information directly from email content while maintaining accuracy and reliability. Scaling Across Geographic Operations Expanding automation into Canadian operations introduced additional complexity, including regional business processes, warehouse management considerations, bilingual documentation requirements, and cross-border operational differences. The organization needed a scalable approach that could support both U.S. and Canadian order workflows. Outcomes Greater Straight-Through Processing Potential The planned enhancements are designed to increase order automation accuracy and reduce the number of orders requiring manual intervention. By focusing on recurring exceptions and process improvements, the organization is positioning itself to automate a larger percentage of inbound order activity and improve operational efficiency. Expanded Order Automation Coverage The initiative establishes a path for processing additional order types, including orders submitted directly within email messages without attached purchase orders. Broadening the range of orders eligible for automation increases the overall value and scalability of the solution. Foundation for North American Automation Expansion By extending automation capabilities into Canadian operations and supporting region-specific business requirements, the organization is creating a framework for more consistent order processing across multiple business units and geographies. The approach provides a foundation for future process automation initiatives throughout the enterprise. our solution Concurrency partnered with the organization to expand and enhance its existing order automation platform through a phased approach focused on accuracy improvements, expanded use cases, and regional scalability. Automation Optimization Evaluated recurring exception scenarios impacting automated order processing. Implemented enhancements focused on improving processing accuracy. Supported the organization’s goal of reducing manual order review activities. Addressed operational feedback from customer service teams. Intelligent Order Processing Designed capabilities to process orders submitted directly within email messages. Expanded automation beyond traditional purchase order attachment workflows. Created a reusable approach capable of supporting additional order submission methods. Enhanced the solution’s ability to interpret and process customer order information. Canadian Operations Enablement Extended automation capabilities to support Canadian packaging operations. Incorporated Canadian business rules and operational requirements. Planned support for French-language order extraction scenarios. Addressed regional workflow and fulfillment considerations. Enterprise Integration & Governance Maintained alignment with Microsoft Dynamics 365 business processes. Leveraged existing integration and operational infrastructure. Incorporated validation, user acceptance testing, and production rollout planning. Established requirements for ongoing measurement and performance tracking. Lessons Learned & Next Steps Data Quality Drives Automation Success Advanced automation solutions depend on accurate, representative business data. Sample orders, business rules, exception tracking, and validation processes play a critical role in ensuring that automation improvements deliver reliable results. Organizations pursuing AI-driven process automation should prioritize data readiness as part of their implementation strategy. Expansion Requires Operational Alignment Extending automation across business units, regions, and languages involves more than technology changes alone. Success depends on coordinating business stakeholders, process owners, operational teams, and technical resources to ensure workflows are consistently implemented and measured. The organization is positioned to continue refining automated order processing capabilities, expand coverage across additional business scenarios, and identify future opportunities to reduce manual effort while maintaining operational accuracy and control. Conclusion As organizations look to improve operational efficiency, order automation continues to represent one of the most impactful opportunities to reduce manual effort and improve scalability. For this distribution organization, the next phase of automation focuses on increasing processing accuracy, expanding automation coverage, and supporting operations across North America. By partnering with Concurrency, the company established a structured approach to enhancing existing automation investments while addressing new business requirements. The initiative creates a path toward broader straight-through processing, improved operational consistency, and continued digital transformation across order management processes. Order Automation & AI Processing FAQs How can organizations reduce manual order entry without disrupting existing operations? Organizations can reduce manual order entry by incrementally expanding automation capabilities around existing business processes rather than replacing them entirely. This engagement focused on improving processing accuracy, expanding automation coverage, and supporting additional order scenarios while continuing to leverage established operational workflows and systems. What types of orders can be automated with AI-powered order processing? AI-powered order processing can support a variety of order formats, including structured purchase orders, email-based submissions, and other customer order communications. The specific level of automation depends on data quality, business rules, document consistency, and the complexity of exception scenarios. Why is data quality important for order automation initiatives? Order automation relies on representative sample data, clearly defined business rules, and accurate operational tracking. Organizations that invest in data readiness and validation processes are typically better positioned to improve accuracy, reduce exceptions, and achieve higher levels of automation. How can manufacturers and distributors scale automation across multiple regions? Successful regional expansion requires a combination of technical scalability and operational alignment. Business rules, language requirements, fulfillment processes, warehouse operations, and customer expectations must all be considered when extending automation across geographic regions. What should organizations consider before expanding an existing automation solution? Organizations should evaluate current automation accuracy, exception volumes, data quality, business process consistency, and stakeholder readiness before scaling automation initiatives. A phased approach allows teams to validate results, manage risk, and identify opportunities for continuous improvement while maintaining business continuity.
