Published on January 26, 2026 • 22 min read
By CLEARomni Editorial Team
The landscape of order fulfillment has undergone a fundamental transformation in recent years, driven by evolving consumer expectations, the proliferation of sales channels, and the imperative for businesses to optimize inventory utilization across distributed networks. At the heart of this transformation lies Distributed Order Management (DOM)—a specialized approach to order orchestration that enables businesses to fulfill customer orders from the optimal location within their network, balancing factors such as delivery speed, shipping costs, inventory positions, and operational capacity.
As we navigate through 2026, Distributed Order Management has evolved from a nice-to-have capability to an essential infrastructure component for businesses pursuing omnichannel excellence. The DOM market has reached $681.2 million in 2026 and is projected to expand to $1.49 billion by 2035, representing a robust 9% compound annual growth rate. This growth trajectory reflects the accelerating adoption of distributed fulfillment models, with 73% of global enterprises now operating across four or more fulfillment nodes. Understanding what DOM is, how it differs from traditional order management approaches, and how to successfully implement it has become critical knowledge for retail executives, operations leaders, and technology strategists seeking competitive advantage in increasingly demanding markets.
The Business Case for Distributed Order Management in 2026
To appreciate the strategic importance of Distributed Order Management in 2026, it is essential to understand the evolution of order management approaches and the specific challenges that DOM addresses. The progression from basic order processing to sophisticated distributed orchestration reflects the increasing complexity of modern retail operations and the growing demands of omnichannel consumers.
Order management has evolved through several distinct phases, each driven by changes in technology capabilities, consumer expectations, and retail complexity. In the earliest days of ecommerce, businesses operated with relatively simple fulfillment models—orders received through a single website channel were fulfilled from a central warehouse or distribution center using basic inventory management systems. The focus was on accurate order processing and timely shipment rather than sophisticated optimization.
As ecommerce expanded and competition intensified, businesses began pursuing multi-channel strategies, selling through marketplaces like Amazon, eBay, and regional platforms alongside their own websites. This expansion created new challenges—orders flowing from multiple sources needed to be consolidated, inventory needed to be synchronized across channels, and fulfillment needed to be coordinated with multiple partners. Traditional order management systems, designed for single-channel operations, struggled to handle this complexity, leading to inventory discrepancies, fulfillment delays, and customer satisfaction issues.
The rise of omnichannel retail marked the next significant evolution. Consumers began expecting flexible fulfillment options—buying online and picking up in-store, ordering for home delivery with precise delivery windows, returning purchases through any channel. Meeting these expectations required businesses to view their entire fulfillment network as a unified system, with inventory flowing dynamically between locations based on demand patterns and fulfillment requirements. This is the challenge that Distributed Order Management was designed to address.
The global ecommerce market, now approaching $8.1 trillion in 2026, has made efficient order management not just an operational necessity but a critical competitive differentiator. Organizations that struggle with order management face significant financial consequences—the average cost per order error ranges from $25 to $150, and manual processing introduces errors in 8-15% of orders. These error rates directly impact customer satisfaction, return rates, and ultimately revenue and profitability, making investment in sophisticated order management capabilities a strategic imperative.
The term "distributed" in Distributed Order Management refers to the fundamental architectural characteristic of having inventory and fulfillment capabilities spread across multiple locations rather than concentrated in a single facility. A distributed fulfillment network typically includes multiple fulfillment centers or warehouses positioned strategically across geographic regions, retail stores that can serve as fulfillment points for online orders, third-party logistics providers offering additional capacity and geographic reach, and supplier facilities capable of direct shipment to customers.
This distribution creates both opportunities and challenges. The opportunity lies in the ability to fulfill orders from the location closest to the customer, reducing shipping costs and delivery times while improving inventory utilization by positioning stock where demand exists. The challenge is the complexity of managing inventory across all these locations, ensuring accurate visibility into what is available at each point, and making optimal routing decisions that balance multiple competing factors.
Traditional order management systems assume centralized inventory and process orders through a single or limited number of fulfillment centers. They are not designed to handle the dynamic nature of distributed fulfillment—the constant movement of inventory between locations, the real-time changes in availability at each point, and the complex routing decisions required when inventory exists in multiple places. DOM systems are purpose-built for this environment, providing the visibility, intelligence, and orchestration capabilities that distributed fulfillment requires.
The scale of distributed fulfillment has grown substantially in recent years. Research indicates that 73% of global enterprises now operate across four or more fulfillment nodes, and this number continues to grow as businesses expand their fulfillment networks to meet customer expectations for faster delivery and flexible fulfillment options. This proliferation of fulfillment locations has made DOM capabilities essential rather than optional for businesses seeking to compete effectively in omnichannel retail.
Several converging trends have elevated Distributed Order Management from a tactical capability to a strategic imperative in 2026. Consumer expectations for fulfillment speed and flexibility have escalated dramatically, with shoppers now expecting options including same-day delivery, precise delivery windows, buy online pickup in-store, and seamless returns across channels. Meeting these expectations requires sophisticated order orchestration capabilities that traditional systems simply cannot provide.
The economics of fulfillment have also changed, with shipping costs representing an increasingly significant portion of order economics. Businesses must optimize every fulfillment decision to balance shipping costs against delivery speed, inventory carrying costs against stockout risks, and operational efficiency against customer satisfaction. This optimization requires real-time analysis of multiple factors across the entire fulfillment network—exactly what DOM systems are designed to do.
The market response reflects this strategic importance. The DOM market has grown from $681.2 million in 2026 toward a projected $1.49 billion by 2035, representing 9% CAGR. Investment activity has increased 37% from 2023 to 2025, with 58% of investments specifically targeting AI-based orchestration capabilities. These trends underscore the recognition among retail executives that distributed order management capabilities are essential infrastructure for competitive omnichannel operations.
Modern Distributed Order Management systems provide comprehensive capabilities that address the unique challenges of distributed fulfillment networks. Understanding these capabilities is essential for evaluating DOM solutions and planning implementations that deliver maximum business value.
The foundation of effective distributed order management is accurate, real-time visibility into inventory positions across all fulfillment locations. Modern DOM systems provide this visibility through continuous synchronization with warehouse management systems, store inventory systems, and supplier inventory data. This visibility extends beyond simple quantities to include inventory status, reservations, in-transit quantities, and expected replenishments.
Effective inventory visibility addresses one of the most persistent challenges in distributed fulfillment—the risk of overselling when inventory exists but is not visible to the order management system, or conversely, stockouts when inventory is committed to orders at multiple locations simultaneously. DOM systems maintain a unified view of inventory across all locations, applying reservations and allocations in real-time to ensure that available-to-promise calculations reflect the true state of inventory across the network.
Research indicates that organizations without proper DOM capabilities report inventory inaccuracies above 15%, leading to overselling, stockouts, and customer dissatisfaction. After DOM implementation, inventory accuracy typically improves from 78% to 94%, representing a fundamental improvement in the reliability of inventory data that supports not only order fulfillment but also demand planning, replenishment, and merchandising decisions.
At the heart of DOM capability is intelligent order routing—the ability to determine the optimal fulfillment location for each order based on multiple factors evaluated in real-time. Unlike traditional systems that apply static rules or route all orders to the nearest warehouse, DOM routing considers a comprehensive set of factors to identify the best fulfillment option for each individual order.
Key routing factors include customer location and proximity to fulfillment nodes, inventory availability across the network, shipping costs from each potential location, delivery time commitments and customer expectations, current operational capacity and performance at each location, carrier availability and rates, and order characteristics such as size, weight, and special handling requirements. DOM systems evaluate these factors simultaneously, applying business rules and optimization algorithms to identify the fulfillment option that best balances competing objectives.
The impact of intelligent routing is substantial. Organizations implementing DOM typically achieve 32% improvement in order routing accuracy, meaning orders are more likely to be fulfilled from the optimal location. This translates to reduced shipping costs, faster delivery times, improved inventory utilization, and higher customer satisfaction. Advanced DOM systems continuously learn from routing outcomes, refining their algorithms to improve performance over time.
One of the most valuable capabilities in distributed order management is the ability to split orders across multiple fulfillment locations when inventory is not available at a single location. When a customer orders multiple items and no single location has complete inventory, traditional systems face a difficult choice—delay the entire order until all items are available at one location, or split the order with different items shipping separately. Neither option is optimal from a customer experience or cost perspective.
DOM systems handle split orders intelligently, evaluating the tradeoffs between fulfillment speed, shipping costs, and customer convenience. They can consolidate items at intermediate locations for combined delivery, ship items from different locations to arrive simultaneously, or prioritize splitting that minimizes total shipping cost while meeting delivery time commitments. The system manages all aspects of split order fulfillment including tracking, customer communication, and returns handling.
Split order orchestration is particularly valuable for businesses with large product catalogs or those sourcing from multiple suppliers. It enables fulfillment of orders that would otherwise be delayed or cancelled due to inventory fragmentation, improving order conversion rates and customer satisfaction while optimizing the overall efficiency of the fulfillment network.
Modern consumers expect flexible fulfillment options that seamlessly blend online and offline shopping experiences. DOM systems provide native support for the full range of omnichannel fulfillment models including Buy Online Pick Up In-Store (BOPIS), Reserve Online and Try In-Store, Ship From Store for direct customer delivery, Ship To Store for customer pickup at retail locations, and Same-Day and Next-Day Delivery using stores as fulfillment points.
Research indicates that 61% of retailers deploy DOM specifically to enable ship-from-store and click-and-collect capabilities, reflecting the strategic importance of these fulfillment options in meeting customer expectations. DOM systems handle the complexity of these fulfillment models, managing inventory allocation, reservation systems, customer notifications, pickup window management, and the operational workflows required at store locations.
The integration between online and offline fulfillment extends beyond order placement to include returns. DOM systems support omnichannel returns, enabling customers to return online purchases through any channel including physical stores. This flexibility is essential for customer satisfaction—research shows that flexible return options significantly influence purchase decisions, with customers more likely to buy when they know returns are convenient.
Same-day delivery has achieved 46% penetration in the U.S. market, reflecting consumer appetite for immediate fulfillment. DOM systems enable same-day delivery by optimizing the use of store inventory and partnering with last-mile delivery services to offer rapid fulfillment options. This capability requires real-time inventory visibility, intelligent routing, and tight integration with delivery platforms—capabilities that DOM systems are specifically designed to provide.
Every business has unique requirements for how orders should be fulfilled, reflecting product characteristics, customer relationships, operational constraints, and strategic priorities. Modern DOM systems provide sophisticated rule management capabilities that enable businesses to configure these requirements without custom development.
Configurable rules address routing priorities such as preferred fulfillment locations or carriers, inventory allocation strategies including how inventory is reserved and allocated across channels, carrier selection based on cost, speed, and service quality requirements, handling requirements for special products like perishables, hazmat, or oversized items, and customer-specific fulfillment preferences for high-value or loyal customers. Rules can be defined at multiple levels—global policies, location-specific configurations, customer segment requirements, and product category guidelines—providing flexibility while maintaining consistency.
Effective rule management enables DOM systems to reflect business requirements accurately while automating routine decisions. As business needs evolve, rules can be updated without system changes, enabling agility in responding to market conditions, seasonal patterns, and strategic initiatives.
Effective management of distributed fulfillment requires comprehensive visibility into performance across the network. Modern DOM systems provide performance analytics capabilities that track key metrics at multiple levels—individual orders, fulfillment locations, channels, and the overall network.
Key performance indicators tracked by DOM systems include order routing accuracy measuring how often orders are fulfilled from the optimal location, fulfillment cycle time tracking the duration from order placement to shipment, on-time delivery rates monitoring commitments to customers, inventory accuracy assessing the correlation between system records and physical stock, shipping cost efficiency analyzing costs per order and per shipment, and split order performance measuring the effectiveness of distributed fulfillment. Dashboards and reporting capabilities enable operations teams to monitor performance in real-time, identify issues, and track improvement initiatives. Advanced analytics support deeper analysis including pattern identification, root cause analysis, and predictive insights.
The performance visibility provided by DOM systems supports continuous improvement in fulfillment operations. By identifying underperforming locations, routing rule issues, or capacity constraints, businesses can take targeted actions to improve overall network performance. This analytical capability is essential for achieving and sustaining the operational excellence required for competitive omnichannel fulfillment.
| Capability | Description | Business Impact |
|---|---|---|
| Multi-Location Visibility | Real-time inventory synchronization across all fulfillment nodes | Inventory accuracy improves from 78% to 94% |
| Intelligent Routing | Dynamic optimization based on proximity, cost, and capacity | 32% improvement in routing accuracy |
| Split Order Handling | Orchestration of orders fulfilled from multiple locations | Improved order conversion and fulfillment speed |
| Omnichannel Support | BOPIS, ship-from-store, same-day delivery capabilities | 61% of retailers deploy DOM for omnichannel |
| Rule Management | Configurable business rules for routing and allocation | Operational agility and requirement alignment |
| Performance Analytics | Comprehensive visibility into fulfillment performance | Continuous improvement and issue identification |
Artificial intelligence has fundamentally transformed Distributed Order Management capabilities in 2026, moving from experimental features to essential functionality that defines competitive advantage in increasingly demanding fulfillment environments. AI now functions as a real-time operational control layer on top of warehouse management systems and order management platforms, continuously ingesting and analyzing signals from across the fulfillment network.
One of the most impactful applications of AI in DOM is predictive demand forecasting. Traditional forecasting methods, based on historical averages and seasonal patterns, typically achieve 65-75% accuracy. AI-powered forecasting, by contrast, achieves 92-97% accuracy by analyzing a much broader set of factors including real-time demand signals, weather patterns, promotional calendars, social media trends, economic indicators, and competitive activity.
The accuracy improvement in demand forecasting has profound implications for distributed order management. With more accurate forecasts, businesses can optimize inventory positioning across their network, ensuring that inventory is available where demand is expected while minimizing excess stock at locations with lower expected demand. This proactive approach to inventory positioning reduces shipping costs, improves delivery times, and reduces both stockouts and excess inventory.
AI forecasting also enables more effective promotion and seasonal planning. By analyzing the relationship between marketing activities and demand patterns, AI systems can predict the impact of upcoming promotions, enabling businesses to pre-position inventory and scale operations to meet expected demand surges. This capability is particularly valuable for managing peak periods like holiday shopping seasons when demand patterns are both high volume and unpredictable.
Traditional order management systems operate on batch processing cycles, with routing decisions made periodically based on inventory states at fixed intervals. AI-powered DOM systems, by contrast, operate in real-time, continuously ingesting signals from across the fulfillment network and adjusting decisions accordingly.
The AI transformation enables continuous re-optimization across all fulfillment operations. Pick paths are continuously adjusted based on order batching and picker location. Wave releases are optimized based on carrier cut-off times and labor availability. Labor allocation is dynamically adjusted based on order volume and capacity constraints. This continuous optimization ensures that fulfillment operations are always operating at peak efficiency, adapting instantly to changing conditions rather than waiting for the next batch cycle.
AI systems also continuously learn from outcomes, refining their algorithms based on actual performance. When routing decisions result in delivery delays or excess shipping costs, the system analyzes the contributing factors and adjusts its decision-making to avoid similar outcomes in the future. This continuous learning means that AI-powered DOM systems improve over time, becoming increasingly accurate and effective as they accumulate operational experience.
The business impact of AI-powered optimization is substantial. Organizations implementing AI order management achieve processing cost reductions of 35-50%, order accuracy improvements to 99.5%+, error rate reductions of 80-95%, and fulfillment time improvements of 40-60%. AI-driven order routing adoption has increased by 41%, with 58% of DOM investments now targeting AI-based orchestration capabilities.
AI Transformation Impact on Distributed Order Management
AI enables a new level of autonomous decision-making in order management. Rather than escalating exceptions to human operators for resolution, AI-powered DOM systems can analyze situations, evaluate options, and take action within defined parameters. This autonomous operation is particularly valuable for handling routine exceptions that would otherwise consume significant operator time.
Examples of autonomous decision-making in AI-powered DOM include rerouting orders when delivery delays are predicted based on weather or traffic conditions, automatically adjusting inventory reservations when orders are delayed in fulfillment, selecting alternative carriers when primary options are unavailable or delayed, managing backorder situations by identifying the fastest path to fulfillment, and handling customer service inquiries by providing accurate delivery status and resolution options. Autonomous decision-making reduces operational overhead while improving response times to exceptions. Operators are freed from routine exception handling to focus on strategic initiatives and complex issues that require human judgment.
The result of AI transformation is fulfillment operations that adapt dynamically to changing conditions rather than relying on static routing rules. Organizations like Amazon have demonstrated the potential of AI-powered fulfillment, decreasing fulfillment costs from 15% of revenue in 2015 to under 12% in 2025 while handling 5x more volume. These achievements illustrate the transformative potential of AI in distributed order management.
Successful DOM implementation requires a structured approach that addresses technology, processes, organizational change, and continuous optimization. Understanding the implementation journey is essential for organizations considering DOM investment.
The implementation journey begins with a comprehensive assessment of current fulfillment operations and definition of future-state requirements. This phase involves analyzing the current fulfillment network including locations, capacity, and performance; documenting order volume, channel mix, and fulfillment patterns; identifying pain points including inventory discrepancies, routing inefficiencies, and customer service issues; defining success metrics including target improvements in routing accuracy, cycle time, inventory accuracy, and costs; and gathering requirements from stakeholders across operations, IT, customer service, and finance.
The assessment phase produces a clear understanding of the current state, a vision for the future state, and specific, measurable objectives for the DOM implementation. This foundation is essential for successful technology selection, implementation planning, and success measurement.
Organizations should also assess their readiness for DOM implementation during this phase. Key readiness factors include data quality and systems integration capabilities, organizational change management capacity, executive sponsorship and stakeholder alignment, and available resources for implementation and ongoing operation. Identifying readiness gaps early enables proactive planning to address them.
Selecting the right DOM platform is critical to implementation success. The market includes solutions ranging from specialized DOM vendors to components of larger commerce platforms. Key evaluation criteria include functional capabilities matching identified requirements, integration architecture and compatibility with existing systems, AI and automation capabilities for future-state optimization, scalability to support business growth and network expansion, vendor viability and market presence, implementation support and professional services, and total cost of ownership including licensing, implementation, and ongoing costs.
Organizations should request detailed reference customers, particularly those with similar network complexity and operational requirements. Proof-of-concept demonstrations with actual data provide valuable insight into how candidate platforms perform with real-world scenarios. Clear ROI projections, validated by reference customers, are essential for securing investment approval and setting appropriate expectations.
The market concentration—where top five vendors control 57% of the market—provides vendor stability but may limit differentiation. Organizations should evaluate both market leaders and specialized vendors to identify the best fit for their specific requirements and strategic direction.
DOM systems must integrate with multiple enterprise systems to function effectively. The integration architecture typically includes connections to ERP systems for order receipt and financial integration, warehouse management systems for inventory and fulfillment execution, ecommerce platforms for order capture and customer data, marketplace integrations for order synchronization, carrier management systems for shipping optimization, and business intelligence tools for performance reporting.
Integration architecture decisions should consider real-time versus batch synchronization requirements, error handling and exception management, data transformation and standardization, and security and access controls. Cloud-native DOM platforms, now representing 68% of deployments, offer integration advantages including pre-built connectors, API-first architectures, and reduced infrastructure burden.
Data preparation is equally critical. DOM systems require accurate, standardized data to function effectively. Key data preparation activities include inventory data cleansing and standardization, location hierarchy definition, product attribute configuration, customer data quality assessment, and historical data migration. Organizations with strong data governance practices will find DOM implementation smoother, while those with data quality issues should plan for significant data remediation effort.
Business rules configuration is a key activity during this phase. Routing priorities, allocation strategies, carrier selection rules, and customer preferences must be translated into DOM system configurations. This configuration work requires close collaboration between business users who understand requirements and technical teams who understand system capabilities.
Most organizations benefit from a phased implementation approach, starting with core capabilities and expanding scope over time. A typical phased approach includes a pilot phase with limited scope, expanded deployment, full optimization, and continuous improvement. The pilot phase focuses on validating core functionality with a subset of locations and channels. Pilot scope should be sufficient to test key scenarios while limiting risk—typically one or two fulfillment centers and major sales channels.
The pilot phase validates routing logic, tests integration flows, and refines business rules based on actual performance. Key activities include monitoring routing accuracy and identifying optimization opportunities, testing exception handling and escalation processes, gathering user feedback and addressing usability issues, and validating performance against defined success metrics. Pilot learnings inform refinements before broader rollout.
Expanded deployment extends DOM capabilities to additional locations and channels. This phase typically follows a geographic or channel-by-channel expansion pattern. Key considerations include change management to ensure user adoption, integration validation for each new system connection, performance monitoring to identify scale-related issues, and knowledge transfer to build internal capabilities. The expanded deployment phase may take 3-6 months depending on network complexity.
Full optimization leverages AI capabilities and performance analytics to continuously improve DOM performance. This phase focuses on refining routing algorithms based on accumulated data, expanding automation of routine decisions, developing custom reports and dashboards, and establishing ongoing optimization processes. Full optimization may take 6-12 months to achieve target performance levels.
Organizations should expect implementation timelines of 3-6 months for core capabilities and 6-12 months for full optimization. ROI is typically achieved within 14-18 months for 63% of implementations. Success factors include executive sponsorship, cross-functional alignment, and focus on change management to ensure adoption across the organization.
Effective Distributed Order Management requires continuous measurement and optimization. CLEARomni provides comprehensive analytics that enable businesses to track the metrics that matter most for DOM success. The following KPIs provide a framework for measuring DOM performance and identifying improvement opportunities.
| Metric | Definition | 2026 Target |
|---|---|---|
| Order Routing Accuracy | Percentage of orders routed to optimal fulfillment locations | 95%+ |
| Inventory Accuracy | Percentage of inventory records matching physical stock | 94%+ |
| Order Cycle Time | Average time from order placement to shipment | 27% reduction from baseline |
| Fulfillment Cost per Order | Total cost per order fulfilled including shipping | 26% reduction from baseline |
| Order Accuracy | Percentage of orders fulfilled completely and correctly | 99.5%+ |
| On-Time Delivery Rate | Percentage of orders delivered by promised date | 98%+ |
| Split Order Rate | Percentage of orders fulfilled from multiple locations | Optimized for cost and speed |
| BOPIS Fulfillment Time | Average time from order ready to customer pickup | Under 4 hours |
CLEARomni's Distributed Order Management solution provides the intelligent orchestration capabilities that modern retail operations require to compete effectively in increasingly demanding omnichannel environments. Our platform delivers measurable improvements that translate directly to competitive advantage and sustainable growth.
The CLEARomni DOM Advantage
Organizations that implement CLEARomni's DOM solution consistently achieve transformative results: 32% improvement in order routing accuracy, 27% reduction in order cycle time, inventory accuracy improvements from 78% to 94%, and 26% reduction in fulfillment costs. AI-powered implementations deliver additional benefits including 37% accuracy improvements and 21% cost reductions compared to non-AI alternatives. These outcomes enable sustainable competitive advantage in increasingly demanding markets where customers expect flexible fulfillment options, accurate inventory information, and fast delivery.
The complexity of managing distributed order fulfillment across multiple channels, locations, and customer expectations becomes manageable with CLEARomni as your technology partner. As the DOM market continues its strong growth trajectory toward $1.49 billion by 2035, organizations with comprehensive distributed order management capabilities position themselves to capture the substantial opportunities in omnichannel retail while meeting escalating customer expectations for speed, accuracy, and flexibility.
The 73% of global enterprises operating across four or more fulfillment nodes require sophisticated DOM capabilities to effectively coordinate distributed operations. Organizations that invest in DOM position themselves to meet these requirements while optimizing costs and enhancing customer satisfaction. The strategic importance of distributed order management will only increase as consumer expectations continue to evolve and competition for fulfillment excellence intensifies.
Don't let fragmented order management limit your omnichannel potential or cost you customers through inaccurate inventory, slow fulfillment, or limited fulfillment options. CLEARomni's advanced DOM solutions empower businesses to optimize inventory across their distributed network, reduce operational costs, and deliver exceptional customer experiences that drive loyalty and growth. With comprehensive capabilities spanning multi-location visibility, intelligent routing, omnichannel support, and AI-powered optimization, CLEARomni provides the foundation for world-class distributed order management.
Ready to transform your distributed order management? Book a demo with CLEARomni today and discover how our DOM solutions can elevate your fulfillment operations, reduce costs, and prepare your business for omnichannel success in 2026 and beyond.
About CLEARomni
CLEARomni is a leading provider of omnichannel commerce solutions, including Distributed Order Management (DOM), Product Information Management (PIM), and Order Management Systems (OMS) powered by artificial intelligence. Our mission is to help businesses deliver exceptional customer experiences while streamlining operations and driving sustainable growth through intelligent automation and data-driven insights. With comprehensive capabilities for order orchestration, inventory optimization, and seamless omnichannel fulfillment, CLEARomni enables organizations to scale their operations efficiently while meeting the speed, accuracy, and flexibility that modern customers demand.