Element / Manufacturing - IDP
Invoice Digitization
Problem :
Manufacturing companies routinely deal with a high volume of vendor invoices across a diverse supply chain. These invoices often arrive in multiple unstructured formats-such as scanned PDFs, emails, or printed forms-making manual data entry into ERP or financial systems a time-consuming and error-prone process. Teams spend hours verifying line items, cross-referencing POs, and reconciling mismatched data. The lack of automation leads to delayed payments, missed early-payment discounts, incorrect entries, and poor vendor experiences. As invoice volumes scale, so does the operational burden, creating a bottleneck in the accounts payable process and introducing financial and compliance risks.
Solution :
Element’s Intelligent Document Processing (IDP) solution automates the extraction, validation, and integration of invoice data. Using AI-powered OCR and machine learning, the system captures key fields such as vendor name, invoice number, amount, tax, due date, and line-item details. It then cross-validates the extracted data with purchase orders, delivery receipts, and master vendor records to detect duplicates, mismatches, or policy violations. Once validated, the structured data is automatically routed into the company’s ERP or payment processing system, with exception handling workflows for flagged invoices.
Outcome :
The invoice digitization solution significantly improves operational efficiency and accuracy within the accounts payable function. Manufacturers report up to 80% reduction in manual entry, faster invoice approval cycles, and improved visibility into liabilities and cash flow. Vendor relationships are strengthened through timely payments and fewer disputes, while finance teams are freed from transactional tasks to focus on analytics and strategy. By closing the loop between procurement, finance, and operations, the solution helps drive end-to-end financial process optimization and ensures greater compliance with internal controls.
2. Sales Order (SO) Automation
Problem :
In a fast-paced manufacturing environment, customer sales orders are received through numerous channels-email attachments, PDFs, scanned forms, and online portals-each with varying formats and information quality. Sales operations teams are forced to manually enter this information into ERP systems, leading to a high risk of data entry errors, missed fields, and inconsistent processing timelines. These delays in order intake ripple downstream, affecting production scheduling, inventory planning, and on-time delivery. The manual nature of the process limits order throughput, reduces responsiveness to customer demand, and constrains scalability during peak seasons.
Solution :
Element’s IDP-enabled Sales Order Automation solution streamlines the capture and processing of incoming sales orders. The system leverages AI and natural language processing to identify and extract key order information, such as customer ID, product SKUs, quantities, requested delivery dates, and pricing details, from a variety of document formats. It applies configurable business rules to validate the information, detect missing or invalid entries, and prepare the data for ingestion into the order management or ERP platform. The automation also creates an audit trail and enables exception workflows to handle complex or incomplete orders.
Outcome :
By transforming the sales order entry process into an automated, high-throughput workflow, manufacturers can dramatically shorten the order-to-cash cycle. Order accuracy increases, fulfillment timelines improve, and operations gain real-time visibility into order pipelines. Customers benefit from faster confirmations and consistent service, leading to higher satisfaction and repeat business. Internally, sales and supply chain teams are able to collaborate more effectively with fewer manual interventions, improving agility and resilience in demand planning. As a result, the organization can scale its order processing capacity without adding headcount, enabling growth with reduced overhead.
3. Warehouse Management – Inventory Forecasting & Cooler Box Tracking
Problem :
Warehouse operations-particularly those involving specialized inventory like cold chain cooler boxes-face challenges in maintaining accurate visibility over inbound and outbound stock flows. At Johnson & Johnson’s Kentucky Distribution Center (KDC), inventory tracking was hampered by unscheduled vendor deliveries, incomplete documentation, and manual, Excel-based forecasting. Returned or damaged items were not consistently documented, leading to gaps in accountability and inaccurate inventory balances. These inefficiencies not only disrupted daily operations but also made it difficult to forecast future demand or plan replenishment with confidence, exposing the facility to both stockouts and overstocking risks.
Solution :
Element implemented an AI- and IDP-driven inventory management solution tailored to KDC’s cold chain environment. The solution uses IDP to extract structured data from inbound shipment documents such as Bills of Lading (BOLs), and integrates with a centralized dashboard to track inventory categorized by box size and type. The system also monitors damaged or expiring items, provides predictive analytics for demand forecasting, and generates alerts for anomalies or inventory imbalances. Built with Power BI and role-based access, the solution delivers real-time visibility across stakeholders while maintaining strict access controls and scalability for future integration.
Outcome :
The warehouse achieved greater control and transparency over cooler box inventory. Automated data capture reduced the manual workload and minimized data entry errors, while real-time dashboards enabled more agile and data-driven decision-making. Predictive insights allowed the team to align stock levels with expected demand, reducing waste and improving service levels. The solution also improved vendor accountability for damaged returns and supported future readiness through modular architecture and integration potential with ERP systems. Overall, the implementation set the foundation for a modernized, intelligent warehouse operation with enhanced operational efficiency, cost control, and risk management.