In the world of B2B commerce, having an efficient order management process is a baseline capability. Especially when large order loads are involved, the ability to achieve a high percentage of orders shipped complete drives significant transportation savings, as split shipments eat away at margins.
There are several factors that drive an increased reliance on split shipments for large order loads, sometimes acting in combination to exacerbate the issue. These include how inventory is distributed in a network, the pressure on stock levels from large orders, and the operational strain it can cause. That’s why order management precision and efficiency is at such a high premium, especially when disruptions like a major port strike throw a wrench in the works.
This article examines split shipments and the issues they cause within the supply chain and distribution and explores some best practices to avoid them. The aim is to help reduce operating expenses, improve product availability, and increase customer satisfaction.
Definition and Causes of Split Shipments
A split shipment happens when an order is divided into multiple shipments due to low stock levels, logistical constraints, or both. Often, businesses feel forced to ship what’s available immediately and send the rest later, hoping that customers can get by on the partial order in the meantime.
Some common causes of split shipments on large B2B orders include the following:
- Multiple suppliers: Variations in supplier lead times or stock availability can cause parts of the order to arrive at different times.
- Order complexity: Large orders often involve diverse products with different handling, storage, or shipping requirements. For instance, temperature-sensitive or hazardous goods requiring specialized transportation often lead to separate shipments.
- Order prioritization: High-priority, in-demand products are time-sensitive, which can lead to shipping what’s on hand separately while waiting for replenishment to send the rest.
- Warehouse fulfillment: Large orders can tax the resources of warehouse operations. SKUs stored in different locations or those requiring a different picking process can cause delays, leading to split shipments.
- Backorders and lead time variation: Some items have significantly different supplier lead times, forcing businesses to ship only a portion of their available inventory and put the balance on backorder.
- Inefficient systems: Without an advanced order management system (OMS), businesses lack real-time inventory visibility across multiple locations. This leads to fragmented fulfillment decisions and more split shipments.
The High Cost of Split Shipments
While some split shipments are inevitable or unavoidable due to external factors, costs go up along with higher frequency. Transportation is clearly the highest direct cost, as it’s generally the second highest expense as a percentage after labor, and more trips are required. There’s also the added complexity of scheduling additional pickups with transporters.
Speaking of labor, split shipments also hit this cost center, as they lead to more man-hours spent preparing orders through picking and packing.
Indirect costs include damage to customer relationships and reputation and the potential loss of future business. B2B customers rely on complete orders to meet production schedules or product demand. As a result, many retailers have implemented on-time in-full (OTIF) requirements. The idea is to enforce greater supply chain optimization by tight collaboration among retailers, brands, transporters, and logistics service providers.
Failure to meet OTIF requirements results in fines and penalties. A McKinsey study found that many retailers in North America are tightening OTIF requirements by narrowing delivery windows and increasing fines while revising the definition of in-full delivery.
A higher incidence of split shipments can reflect deeper issues of poor inventory management, such as stock imbalances or inefficient replenishment processes. Finally, they contribute to higher carbon emissions from the additional truck trips required.
Other Split Shipment Headaches in B2B
Split shipments introduce complexities that impact multiple areas of operations, including order tracking, invoicing, and customer communication. Each contributes to inefficiencies, often leading to higher costs, increased labor, and a decline in service quality.
Tracking Complexity
When shipments are split, tracking the order status becomes more complicated because different segments move independently through the supply chain. Logistics teams have to track each portion of the order separately, from inbound inventory to fulfillment and delivery. This involves monitoring multiple tracking numbers, the status of transporters, and estimated delivery times.
Managing Multiple Invoices
Split shipments often lead to multiple invoices, complicating accounts payable for both the shipper and customer, including reconciliation of multiple invoices against the original order. Each invoice might include different shipping costs, taxes, and fees, adding to administrative overhead. In some cases, customers might withhold payment until the entire order is delivered, adding more complexity and delaying closing the transaction.
Customer Communications
In B2B transactions, logistics and delivery impact a customer’s production schedules, inventory levels, and downstream operations. Shippers need to manage expectations around timing, coordination, and delivery schedules. Customers often rely on complete shipments to avoid production downtime, which causes frustration and the pain of adjusting internal processes.
Split shipments also require customers to coordinate with receiving teams across multiple deliveries. Additional labor and resources are needed to accept, inspect, and verify each portion of the order upon arrival.
Leveraging Technology to Optimize B2B Order Management
Advances in technology for supply chain and logistics have made it easier for businesses to optimize their inventory and order management processes in order to reduce the incidence of split shipments. Here are some examples.
WMS
A warehouse management system (WMS) provides real-time updates on inventory levels, enabling better decision-making and reducing stock-outs that lead to split shipments. Most systems can also automate inventory replenishment to ensure that items in high demand remain in stock, reducing the need for split shipments.
OMS
An order management system (OMS) integrates order data from various sources (e-commerce platform, ERP, CRM, WMS, etc.), providing visibility into inventory availability. This helps drive a higher percentage of “order complete” confirmations before shipment. An OMS also has consolidation logic for prioritizing full order fulfillment vs. partial shipments.
Tramm, a developer of a leading unified supply chain management platform, combines a powerful OMS within its transportation management system (TMS) suite. This integrated approach provides end-to-end visibility and control over order fulfillment and shipping processes. Tramm’s Order Management Module ensures that orders are fully consolidated before being released for shipment, while the TMS manages transportation in the most efficient, cost-effective manner.
Using real-time data synchronization, Tramm’s integrated approach ensures that any changes in order status, inventory levels, or shipping schedules are immediately reflected across both systems. This allows the OMS to quickly adjust fulfillment strategies if stock availability or transporter issues arise, reducing the need to rely on split shipments.
Predictive Analytics and Demand Forecasting
Predictive analytics tools tap the power of AI to enable proactive inventory management. By more accurately forecasting demand and optimizing inventory levels, both stockouts and split shipments are reduced. This technology enables users to foresee potential supply chain disruptions and adjust fulfillment strategies accordingly.
Automated Fulfillment and Transporter Routing
Fulfillment automation reduces errors in picking/packing, allowing a higher percentage of full orders to be processed and minimizing the need for split shipments.
Smart routing automatically directs orders to the most appropriate warehouse or fulfillment center, optimizing shipments and reducing transportation costs. Tramm’s Planning & Optimization Module uses advanced algorithms and visualization tools to drive better, faster load and routing decisions. The result is operational cost savings, including reduced split shipments and highly responsive planning capabilities.
Supplier Collaboration and Data Sharing
Collaborative planning includes sharing inventory and demand data with suppliers, improving stock replenishment, and reducing the likelihood of split shipments. By employing Vendor-Managed Inventory (VMI), suppliers manage stock levels, helping ensure that products are consistently available. This minimizes the need for split shipments due to out-of-stocks.
Best Practices to Minimize Split Shipments in B2B Order Management
Companies can take several steps to improve their order management processes, increase efficiency, and increase the percentage of “shipped complete” orders.
Centralized Inventory Management
Centralized inventory involves keeping all stock in one primary location, such as a warehouse, fulfillment center, or other storage facility. This central hub typically manages not only inventory but also key logistics functions like order processing and fulfillment.
In a centralized inventory system, the majority of operations, including order management and distribution, are handled from this single location, even when there are multiple sales channels or retail outlets. This strategy reduces the need for split shipments due to inventory imbalances.
Order Consolidation Policies
Order consolidation involves combining multiple orders into a single shipment. This can be done by centralizing items from multiple orders into a single location or by combining multiple orders from different sales channels into a single system.
Order consolidation can benefit businesses in several ways. This includes lower transportation costs based on economies of scale, better management of stock levels due to fewer shipments, overall simplified logistics, and a better customer experience through more complete orders.
Smart Reordering Strategies
Smart reordering is a rules-based, automated process utilizing data analytics and AI to manage inventory levels and optimize replenishment. Unlike traditional reordering, which relies on manual tracking or fixed schedules, smart reordering uses real-time data (sales trends, demand forecasting, lead times, supplier performance, etc.) to predict when SKUs will need to be replenished.
This approach helps ensure that critical and/or high-demand products are always in stock, preventing backorders and reducing the need for split shipments.
Transparent Customer Communication
This seems like an obvious point, but too many organizations fail to keep customers updated on order status. This is especially important when unexpected drops in inventory levels or logistics snafus require a split shipment.
Always give customers the option of waiting for replenishment to send a complete order or receiving a partial shipment first. In some cases, the added expense of expedited transportation comes into play to make things right and keep to their schedule.
Continuous Monitoring and Adjustment
Regularly analyzing order data helps identify patterns that lead to increases in split shipments. By tracking trends in demand, stock levels, and fulfillment performance, you can proactively adjust inventory management, including redistributing stock across locations or improving order consolidation processes.
Leaning On Technology to Optimize Large Order Loads
Minimizing split shipments is important to maintain supply chain efficiency and reduce transportation costs. Software such as OMS, WMS, and predictive analytics tools can improve inventory management and streamline fulfillment processes. Best practices such as smart reordering, order consolidation, and continuous monitoring help reduce the incidence of split shipments.
Tramm integrates transporter management, route optimization, order management, customizable dashboards, and a control tower to optimize routing and order allocation. When shipments do need to be split, Tramm automates the process based on operational and resource requirements.
Tramm’s FleetVision Module gives users access to precise real-time data and insights. With a better understanding of fleet operations on a granular level, they can manage each load more effectively and implement performance improvement measures. The result is greater efficiency, reduced costs, and improved customer satisfaction.
To learn more about how Tramm can drive measurable improvement in your supply chain and logistics operations, request a demo today.
Related Resources
Synchronized Logistics: Leveraging An Integrated TMS for Real-Time Supply Chain Management
An integrated supply chain TMS helps make tight partner collaboration and data collection from multiple sources possible so goods flow smoothly, SLAs are hit, and production stays on track.
It’s also a key element in synchronized logistics, a process that businesses lean on to manage multiple complex systems. This involves pulling together and analyzing data from disparate sources, all of which touch the supply chain in some way: transportation management systems (TMS), warehouse management systems (WMS), enterprise resource planning (ERP), and even yard management systems (YMS). Using data analytics, synchronized logistics pulls together insights that can then be applied to various supply chain processes.
In this context, an integrated supply chain TMS can achieve synchronized logistics by enhancing business intelligence and optimizing all aspects of transportation. This, of course, has multiple benefits up and down the supply chain, such as faster inventory turns, better delivery metrics, and improved asset utilization, among others.
An integrated TMS uses advanced business intelligence to optimize logistics and transportation by analyzing large sets of real-time and historical data. It helps identify patterns and inefficiencies, predict delays, and recommend optimal routes. Using predictive analytics to forecast demand can optimize capacity utilization and automate decision-making, such as selecting the most cost-effective carriers or adjusting delivery schedules.
An integrated TMS enables more precise planning, cost control, and supply chain efficiency by incorporating data from ERP, WMSs, and other systems. This helps companies improve planning and execution, reduce delays, and respond quickly to disruptions. Using AI-powered data analytics, businesses can fine-tune their operations and keep costs in check.
As the need for real-time supply chain visibility grows, the role of an integrated supply chain TMS becomes even more critical. Its ability to synchronize logistics and provide actionable insights helps companies stay competitive in an increasingly dynamic market.
What is an Integrated TMS in the Supply Chain?
An integrated TMS is a comprehensive platform designed to streamline the core functions of supply chain management: planning, execution, and optimization of transportation activities. It helps businesses plan efficient routes, execute shipments, and optimize delivery schedules to reduce costs and improve performance.
It also helps meet heightened performance expectations by providing visibility and agility across the supply chain. Unlike a traditional TMS with limited connectivity, an integrated TMS hooks into multiple complementary software systems. Creating a cohesive information flow across the supply chain enables more informed decision-making and better cross-functional collaboration. Businesses benefit from real-time tracking, updates, and greater visibility into logistics operations.
The Importance of Real-Time Supply Chain Management
Customers in both B2B and B2C are demanding faster delivery times, more accurate ETAs, tight delivery windows, and real-time updates on order status. Call it the “Amazon effect,” driven by the higher service level expectations created by the mega e-commerce company turned logistics powerhouse. Especially in a tighter economy, there is little margin for error in terms of costs, the balance sheet, and customer churn.
Real-time supply chain management involves continuously monitoring and managing supply chain activities as they happen. This is where synchronized logistics comes into the picture. Real-time data from integrated systems provides immediate visibility into inventory, shipment status, and fulfillment operations. This allows businesses to make quick, informed decisions, optimize routes, and adjust to changing conditions. The result is increased efficiency, cost savings, and improved customer service.
Key benefits of real-time supply chain management include:
Quick response to disruptions: Real-time supply chain management enables businesses to respond swiftly to issues like traffic, port congestion, or weather delays. With immediate access to updated data, they can quickly adjust routes, reschedule shipments, and notify customers, minimizing delays and maintaining operational efficiency.
Optimized route planning: Real-time data from TMSs allows businesses to dynamically optimize routes based on current conditions such as traffic or road closures. This reduces transit times, improves fuel efficiency, and enhances on-time delivery rates, leading to cost savings and improved KPIs.
Improved customer satisfaction: Accurate real-time tracking ensures customers receive up-to-date information on shipment status, including greater accuracy in delivery estimates. This transparency and proactive communication build trust and loyalty by enhancing customer experience (CX), helping companies exceed delivery expectations, and improving customer satisfaction.
Core Features of an Integrated TMS That Supports Synchronized Logistics
An integrated supply chain TMS offers a wide array of features designed to improve supply chain management and logistics flow:
Real-Time Tracking and Visibility
A supply chain TMS allows you to monitor each shipment from order to delivery by providing continuous updates on shipment location, inventory status, and delivery progress. This level of transparency allows you to quickly address potential issues (delays, misrouting, breakdowns) before they escalate. The system’s ability to provide real-time views into supply chain flow improves accountability and efficiency.
Advanced Data Analytics
Integrated TMS platforms use predictive analytics to anticipate delays, optimize routes, and improve decision-making. Predictive and even prescriptive insights allow businesses to proactively avoid disruptions and refine logistics strategy.
Automation and Collaboration
Automation tools facilitate freight scheduling, real-time communication with carriers, and stakeholder collaboration. This reduces manual intervention and enables teams to focus on higher-value tasks.
Seamless Integration
An integrated TMS connects with other systems to synchronize supply chain operations. This ensures data flows smoothly between departments, teams, and partners, helping streamline processes and reduce delays.
Overcoming Common Supply Chain Challenges with Integrated TMS
An integrated TMS helps businesses address several common supply chain challenges:
Reducing delays and inefficiencies: Real-time updates allow companies to anticipate and avoid delays. With real-time visibility, businesses can reroute shipments or adjust schedules to minimize disruptions.
Improving demand forecasting and inventory management: Data generated by a TMS helps logistics planners maintain lean inventories while still meeting customer demand. With accurate, up-to-date information on shipment status and inventory levels, they can more closely align supply with demand, reducing the risk of stockouts or overstocking.
Adapting to market changes: Market volatility and changes in consumer behavior can disrupt supply chains. An integrated TMS helps businesses become agile through real-time adjustments to routes, carriers, or schedules in response to changing conditions.
The Role of Data in Synchronized Logistics
Data is the backbone of synchronized logistics. An integrated TMS collects, processes, and analyzes vast amounts of data to drive more informed decision-making.
A TMS provides real-time data, enabling better decision-making in procurement, route optimization, and warehouse management. Accurate, timely information helps businesses be more proactive and improve overall efficiency.
Many advanced TMS platforms incorporate AI and machine learning algorithms to predict risks, optimize freight rates, and automate repetitive tasks. These technologies enhance the system’s ability to make real-time adjustments, delivering improved operational efficiency and reduced costs.
By leveraging real-time data, businesses can provide more accurate information to customers about shipment status, improving transparency and loyalty. Data-driven synchronized logistics enhances CX by ensuring timely deliveries and proactive communication.
Choosing the Right Integrated TMS for Your Business
Some attributes of an integrated TMS include its intuitive UI, which makes it easy for nontechnical users to manage both owned and contracted transportation assets. This includes streamlining aspects of transportation management, such as contracts and payments.
Scalability is another important feature, as well as a cloud architecture and ease of integration with other systems through API connections. A supply chain TMS should also be customizable and rules-based, adaptable to prioritize the execution of last-mile delivery, international shipping, or retail replenishment. Mobile workflows, master data attributes, exception management, self-reporting, and business intelligence should all be easily configurable based on your business needs.
The importance of provider reliability cannot be overstated. Look for a company that offers robust customer support, ongoing training, and regular system updates to address evolving industry and business needs. This is a recipe for long-term success, giving you the ability to maximize system capabilities.
An Integrated TMS: Creating the Future of Supply Chain Efficiency
An integrated supply chain TMS plays a pivotal role in powering synchronized logistics so businesses can streamline operations and respond in real time to supply chain challenges. Consolidating data from multiple systems enhances visibility, optimizes routes, and minimizes disruptions. Companies can make informed decisions, improve delivery performance, and reduce costs through advanced analytics and automation. These next-generation systems ensure a more agile, efficient, and customer-centric supply chain.
Tramm TMS is the first SaaS platform using advanced technology to enable companies to easily manage all transportation assets, both owned and third-party, from the first mile to the last mile.
It is purpose-built to streamline supply chain operations, synching data to create a single source of truth. By eliminating data silos and tapping the power of AI-driven insights, Tramm streamlines processes and ensures a consistency of action across the supply chain.
With its modular, scalable architecture, Tramm’s solution set includes an order management system (OMS), a visibility and control tower module, a global transporter module, a dashboards module, and a driver app. Its platform marries flexibility with optimization, powering a customer-centric approach that delivers measurable results. To learn more about Tramm’s ability to power synchronized logistics and increase supply chain efficiency in your organization, request a demo today.
Predictive Analytics in Logistics: The Key to Effective Supply Chain Management
It’s hard to say “supply chain” without throwing in the word “complexity” as a qualifier. Supply chain management has grown more challenging for a number of reasons. Many businesses, both B2B and B2C, have become “omnichannel,” mixing online and offline, while geopolitical strains have disrupted shipping. The pandemic effect led to widespread supply chain redesign and rethinking, including diversifying sourcing, carriers, ports and lanes, etc., to guard against future shocks.
Predictive analytics has become a key capability across industries and business functions. Smart digital tools are used to analyze vast amounts of data, helping companies gain insights and plot strategies with a more forward-looking bent. In logistics and supply chain, predictive analytics has become an invaluable tool, leveraging historical and real-time data to more effectively set transportation, logistics, and warehousing strategies.
We will explore how predictive analytics is transforming supply chain management. It has become essential for everything from demand forecasting to shipping schedules and route optimization.
Supply Chain Analytics: Insights Made Actionable
Predictive analytics applies advanced algorithms and statistical models to identify patterns, trends, and correlations within the data to generate forecasts about future events or behaviors.
In the context of supply chain management, predictive analytics takes historical and transactional data to create models that identify patterns for risks and opportunities. This helps guide decision-making by anticipating specific future events.
For instance, predictive analytics can be used to help a company shift from a just-in-case to a just-in-time model for sourcing products and materials, or use analysis of next quarter’s freight rates to optimize carrier selection and contracting.
Effective Supply Chain Management Begins with Effective Analytics
The proactive approach enabled by predictive analytics helps businesses optimize key supply chain functions such as inventory management, transportation planning, and demand forecasting. It does this by making resource allocation more efficient while minimizing the impact of disruptions.
Common techniques in predictive analytics for supply chain management include regression analysis, time series forecasting, decision trees, and neural networks. Each has its unique strengths and application to specific areas, such as route planning and risk mitigation.
Ensuring compatibility between predictive analytics tools and existing IT infrastructure can be challenging. Balancing innovation with operational continuity is key to leveraging predictive insights effectively. And breaking down silos to enable seamless data flow across systems is critical but often difficult to achieve. This is why a smart option is to go with an end-to-end supply chain management platform approach, using an integrated suite of tools that comes pre-built with powerful analytics capabilities.
Three Ways Predictive Analytics Can Revolutionize Supply Chain Management
Let’s dive a little deeper into specific areas of supply chain management where predictive analytics can drive operational efficiency.
Enhancing Demand Forecasting and Inventory Management
Predictive analytics significantly enhances demand forecasting accuracy, enabling businesses to better align inventory levels with future demand. By analyzing historical sales data, market trends, and external factors, predictive models provide insights into upcoming demand patterns.
This leads to more precise inventory planning, reducing the risk of overstock and stockouts. Benefits include cost savings from reduced holding costs and waste, along with improved customer satisfaction due to consistent product availability.
Optimizing Transportation and Route Planning
Predictive analytics also plays a crucial role in optimizing transportation and route planning. By anticipating potential delays, disruptions, and inefficiencies (traffic congestion, weather conditions, etc.), predictive modeling drives more efficient route planning. This reduces transit times, lowers fuel costs, and minimizes carbon emissions, saving money while taking a more sustainable approach.
Tramm, the creator of a true supply chain TMS, has a Route Optimization Module that utilizes predictive analytics to adjust routes in real time based on a variety of factors, ensuring timely deliveries while maximizing efficiency. It also helps companies optimize cross-dock and multi-modal planning, including LTL, TL, and multi-fleet.
Proactive Risk Management and Issue Resolution
By identifying potential risks (supplier delays, transportation bottlenecks, port disruptions) before they materialize, businesses can get ahead of these risk factors. Early warning systems and scenario planning, powered by predictive analytics, help maintain supply chain resilience and continuity.
Tramm’s Control Tower Module uses the power of predictive analytics to monitor and manage potential disruptions. A dashboard view provides real-time vehicle tracking and status updates via third-party integration, GPS, or Tramm’s Mobile App. Customizable alerts notify managers about unplanned stops, deviations, and performance issues, minimizing the impact of unforeseen events.
Tapping the Power of Predictive Analytics for Supply Chain Optimization
Predictive analytics is transforming supply chain management by allowing companies to optimize demand forecasting and transportation, and proactively manage risk. These capabilities allow them to make data-driven decisions, improving efficiency and supply chain resilience. The efficiencies gained help reduce costs and improve competitiveness.
Tramm’s platform is built on a simple yet rarely implemented idea: a TMS can only be effective if every aspect of transportation management is modeled, integrated, and visible from order inception to final delivery. The power of Tramm comes from its ability to capture and leverage details in a user-friendly way. Users gain planning and route optimization, transporter management (Transact Module), real-time visibility (FleetVision Module), and impactful business insights (Dashboard Module). To learn more about how Tramm can transform your supply chain management, request a demo today.
Reducing Operational Complexity With a Unified Logistics Management System
Saying “logistics are complex” may be akin to saying “water is wet,” but the level only seems to be rising. Companies are expanding sales channels, trading partners, vendors, and markets as they seek new opportunities, and each step adds a layer of complexity. In the process, they often pursue a point solution approach, creating a patchwork of technologies that require a heavy IT lift in terms of integration and maintenance.
A logistics management system (LMS, not to be confused with a labor management system) is a technology solution that addresses this issue. It’s a software tool that helps companies manage the flow of goods from production to end customers.
An LMS can help improve efficiency, reduce costs, and provide a better customer experience. It does this by consolidating all logistics operations into one integrated platform. A truly unified LMS can help shippers reduce complexity and improve supply chain resiliency. By coordinating multiple logistics functions within a single system, an LMS eliminates silos and promotes real-time collaboration.
What is a Unified Logistics Management System?
A unified LMS integrates various logistics functions, such as inventory, transportation, and warehouse management. Key features include access to real-time data, automated processes, and end-to-end visibility. By consolidating logistics operations, a unified LMS removes inefficiencies that naturally arise from disparate technologies. The result is improved decision-making and better demand forecasting.
Unification is critical for managing complex, multi-node supply chains under pressure from heightened customer expectations, geopolitical and labor tensions, fluctuating markets, and global sourcing. A unified LMS provides the flexibility and scalability to adapt to new business challenges and opportunities, increasing responsiveness and competitiveness.
The Operational Complexity of Logistics
Managing the flow of goods from origin to customer involves many moving parts. Disparate systems and silos, as noted above, slow down operations and drive inefficiency. This often requires manual intervention to reconcile data across platforms, resulting in errors and delays.
Reliance on manual workflows adds to the operational burden, lowering productivity and increasing the risk of errors. Inventory management, shipping, tracking, and reporting are time-consuming and require coordination across departments, making it difficult to maintain accuracy and efficiency.
The sheer volume of data generated in logistics — customer orders, inventory updates, shipping schedules, etc. — can quickly overwhelm traditional systems. Handling this information load without the proper infrastructure increases complexity and response times, impacting overall supply chain performance.
A Unified LMS: Reducing Operational Complexity
Imagine a centralized platform where all logistics data is stored, providing real-time visibility across operations. This would remove the need to constantly reconcile data across multiple systems. Tracking orders, monitoring shipments, and accessing up-to-date inventory levels would become easier. Real-time data access would also allow logistics managers to make faster, more informed decisions that improve supply chain efficiency.
This type of consolidation reduces errors and eliminates delays caused by manual data entry. Teams no longer need to cross-check information across systems; all stakeholders can access the same accurate data. Greater visibility streamlines coordination among suppliers, warehouse managers, transporters, and customers, leading to faster response times and fewer disruptions.
Streamlining Communication and Collaboration
A unified LMS also enhances internal and external communication by eliminating data silos. This makes it easier to track orders, manage inventory, and resolve issues in real time.
With all logistics operations accessible on a single platform, teams can collaborate more effectively, reduce communication barriers, and increase alignment. This level of coordination improves performance, so every aspect of the logistics process runs smoothly and efficiently.
Workflow Automation
Automating orders, inventory updates, and shipment tracking reduces the need for manual intervention. Automated workflows also help eliminate errors and streamline administrative tasks, freeing up logistics teams to focus on more high-level, strategic activities.
For example, an automated system can trigger the creation of shipping labels, inventory adjustments, and confirmations upon order placement. This ensures that everything is processed rapidly without requiring additional input. Automation helps companies reduce lead times, improve accuracy, and reduce errors in orders and shipping.
Integrated Inventory and Transportation Management
A unified LMS combines inventory and transportation data, optimizing routing while making order fulfillment faster and more accurate. The system can automatically adjust shipments in real time by linking SKU-level inventory data with transportation schedules based on stock availability and order requirements.
Integrated data benefits transportation management. The LMS can track shipment progress, identify bottlenecks, and suggest alternate routes, minimizing delays and reducing fuel consumption. With end-to-end visibility and integrated tools, companies can better sync inventory and shipments, reducing the risk of overstocks or stockouts and lowering transportation costs.
Benefits of a Unified LMS
Centralizing and automating logistics processes leads to faster operations and minimizes disruptions. With a unified LMS, teams can quickly identify bottlenecks, proactively address issues, and optimize resources. This reduces downtime, speeds up deliveries, and improves service levels.
Lower Operational Costs
A unified LMS optimizes resources and improves planning by reducing errors and lowering operating costs. With automated workflows, consolidated data, and the elimination of redundant systems, companies can cut down on overhead and avoid unnecessary delays.
Better Decision-Making with Real-Time Data
One of the greatest advantages of a unified LMS is access to real-time data. With accurate, up-to-date information at their fingertips, managers can make faster, smarter decisions. From adjusting routes to reallocating inventory, real-time data delivers the insights needed to keep operations running smoothly and efficiently.
Improved Customer Satisfaction
With a unified LMS, companies can ensure they’re providing timely, reliable deliveries. Streamlined operations allow them to consistently meet deadlines and reduce transit times, raising CSAT scores. Companies can increase loyalty and sales through improved order fulfillment accuracy and reduced delays.
Overcoming Implementation Challenges
Integrating a unified LMS into an existing logistics environment can present challenges, particularly for companies overly reliant on embedded legacy systems. Connecting the LMS with a transportation management system (TMS), warehouse management system (WMS), enterprise resource planning (ERP), etc., requires careful planning and execution. A staged approach helps ease the transition, allowing teams to adapt while minimizing downtime and service disruptions.
Training and Change Management
The transition requires thorough training and change management so teams become comfortable with the new system. Effective training helps them understand how to use it efficiently, while change management eases the cultural transition to a data-driven approach.
Data Security and Compliance
As logistics increasingly goes digital, data security and regulatory compliance are huge priorities. For instance, a unified LMS helps companies doing business in Europe meet major data privacy regulations such as GDPR. Ensuring that all systems are secure and up to date helps protect sensitive customer and financial data while maintaining trust.
The Impact on Long-Term Business Growth
A unified LMS can scale and adapt to changes in demand, making it a key asset for companies during rapid market changes. As they expand into new markets or roll out product launches, it gives them the flexibility to meet new demands without compromising performance.
Fostering Innovation
A unified LMS reduces complexity, freeing up resources that can be reinvested into innovation. Companies can now pursue emerging technologies like AI-driven analytics, predictive forecasting, and automation, improving supply chain efficiency and creating a competitive advantage.
Competitive Advantage
A simplified, efficient logistics operation makes companies more nimble and responsive to market changes. Optimizing routes, reducing transit times, and improving inventory management all lead to better business outcomes and future positioning.
Playing the Long Game Through Unified Logistics
A unified LMS is essential for reducing operational complexity and increasing supply chain efficiency. By integrating key logistics functions into a single platform, companies can improve communication, streamline workflows, and make smarter, data-driven decisions. This helps foster cost savings, boost customer satisfaction, and improve competitiveness. It also allows them to keep pace with evolving demands in logistics and supply chains while ensuring greater resilience and scalability.
Tramm, an innovative supply chain software firm, has created the first SaaS platform that allows companies to easily manage all owned and third-party transportation assets. Tramm is purpose-built to streamline supply chain operations, acting as a unified LMS by synching data and creating a single source of truth. By eliminating silos and tapping the power of AI-driven insights, Tramm ensures consistency of action across the supply chain.
With its modular, scalable architecture, Tramm’s solution set includes an order management system (OMS), a visibility and control tower module, a global transporter module, a dashboards module, and a driver app. Its platform marries flexibility with optimization, powering a customer-centric approach that delivers measurable results. To learn more about Tramm’s ability to power synchronized logistics and increase supply chain efficiency, request a demo today.
The Importance of Detailed Order Data in Supply Chain Optimization
As supply chains become increasingly complex, the demand for efficiency and flexibility has never been greater as companies struggle to meet rising customer expectations and deal with global disruptions. Having detailed order data is one key ingredient in supply chain optimization, enabling better decision-making, improved efficiency, and reduced costs.
The ability to access and analyze clean, accurate data improves demand forecasting, inventory management, and fulfillment operations by providing greater visibility into SKU levels and order status. It also helps streamline transportation, reduce lead times, and optimize carrier selection.
Conversely, a lack of detailed order data leads to a variety of negative consequences. These include mismanaged inventory (more stockouts, overstocks), fulfillment delays, disrupted workflows, inaccurate demand forecasts (over or underproduction), strained customer relationships, and financial impacts.
This is why order data accuracy is critical in supply chain optimization. It improves decision-making, enhances efficiency, and reduces costs.
Understanding Order Data’s Role in Supply Chain Optimization
Order data includes information on products, quantities, prices, customer preferences, delivery schedules, and fulfillment status. Sources of order data include order management systems (OMS), enterprise resource planning (ERP, often the central hub), customer relationship management (CRM), procurement systems, and, if there’s a retail component, point-of-sale (POS) systems.
Detailed order data is the foundation for optimizing inventory management, transportation and delivery, warehousing, and fulfillment — in short, every operational aspect of the business.
An inability to control how orders are handled from inception contributes to poor decisions, and inaccurate data is often the culprit. The lack of a unified, efficient system for moving orders from planning to execution and doesn’t enable real-time visibility is a recipe for disaster. The result is a limited ability to represent actual order status in a meaningful way.
Enhancing Demand Forecasting and Inventory Management
A business’s success or failure is inextricably linked to its ability to accurately forecast demand and, from there, properly manage inventory levels. Detailed order data (current and historical), as well as factors like market trends and customer feedback, allow businesses to predict demand more accurately and optimize inventory levels.
Using manual processes to handle order data, even in small-to-medium businesses, is a system rife with errors and inaccuracies. The ability to access real-time order data informs smarter reordering and replenishment strategies. This helps reduce overstocks or out-of-stocks by leveraging actual demand patterns, maintaining cash flow, reducing carrying costs, and keeping customers happy.
Improving Order Fulfillment and Reducing Lead Times
Having detailed order data helps minimize fulfillment errors by optimizing picking, packing, and shipping processes. By accurately tracking customer demand, businesses can expedite order processing and optimize transportation routes to reduce lead times.
Order allocation can be fine-tuned based on stock availability and proximity to customers, enabling faster, more efficient fulfillment. This not only speeds up deliveries but also improves customer satisfaction.
Optimizing Transportation and Logistics
Another benefit of having detailed, accurate order data is on the logistics side. With it, businesses can optimize order routing, consolidate shipments, and reduce delivery costs. They can also choose the most cost-effective carriers and shipping methods based on order data.
Order consolidation involves centralizing items from multiple orders into a single location or by combining multiple orders from different sales channels into a single system. This helps lower transportation costs, improve inventory management, simplify logistics, and provide a better customer experience by reducing split shipments.
With the ability to access and analyze detailed order data, businesses can save by taking advantage of bulk shipping discounts, optimizing carrier selection, and avoiding last-minute changes in shipping schedules.
Supporting Customer Satisfaction and Personalization
Detailed order data allows businesses to track customer preferences, providing personalized offerings and recommendations. It also improves proactive communication, informing customers about order status, estimated delivery times, and potential delays.
This type of transparency enhances trust and helps companies to manage customer expectations. It contributes to a consistently excellent customer experience, boosting satisfaction scores, repeat business, and brand loyalty.
Without Detailed Order Data, Things Break Down
Detailed order data is critical for supply chain optimization, enabling better demand forecasting, more efficient inventory management, and faster fulfillment. It allows businesses to streamline transportation, optimize routing, and reduce delivery costs. Accurate order data also supports customer satisfaction by providing real-time order status and personalized offerings, reducing errors and improving efficiency. A lack of such data, for instance, due to manual processes or outdated software, leads to fulfillment delays, inventory mismanagement, and strained operations.
Tramm, a developer of a leading unified supply chain management platform, combines a powerful OMS within its transportation management system (TMS) suite. This integrated approach provides end-to-end visibility and control over order fulfillment and shipping processes. Tramm’s Order Management Module ensures that orders are fully consolidated before being released for shipment, while the TMS manages transportation in the most efficient, cost-effective manner.
The power of Tramm lies in its ability to optimize the entire process from order management through planning and route optimization, contract management, fleet management, and performance analytics. A versatile driver app provides workflow management, electronic proof of delivery, compliance tracking, and auditing.
Request a demo today to learn more about how Tramm can drive supply chain optimization through its cutting-edge tools and holistic approach.
