Today’s highly interconnected supply chains are, in effect, massive networks that rely on all the players to do their part. Despite this, inadequate communication often results in lackluster coordination and is a primary chokepoint, leading to any number of failures. That’s why implementing a true supply chain TMS (transportation management system) is a key success factor.
TMS software is one way organizations look to create unified communication among supply chain stakeholders. Unfortunately, most systems today fail to achieve this objective, as they’re cumbersome, inflexible, and out of sync with interdependent pieces of the tech stack.
A lack of integrated communication and collaboration among external and internal supply chain partners ultimately frustrates customers and leads them to jump ship. Throw in all-too-common disruptions — tight capacity, port backups, geopolitical conflicts — and companies with poor supply chain visibility can’t give customers the kind of transparency they’ve come to expect.
This is where Tramm comes in. Tramm is a comprehensive TMS that is purpose-built to streamline supply chain operations within a unified platform approach. By integrating communication, route optimization, order management, and a control tower for real-time visibility, Tramm ups efficiency, reduces costs, and helps improve CSAT scores. All of this addresses critical pain points felt today across logistics management.
In this article, we’ll explore the issues and limitations of TMS systems and how Tramm addresses them by enhancing communication across the supply chain. We’ll unpack how Tramm is built on a simple yet rarely implemented idea: a TMS can only be effective if every aspect of transport management is modeled, integrated, and visible from order inception to final delivery.
Communication: A Key Chokepoint for Complex Supply Chains
In logistics, every operational execution — whether store delivery, inbound DC shipment, or DTC order — touches multiple functional areas: transportation, order management, customer data, and warehouse management. Without a unified communication approach, things can break down quickly, as we’ll illustrate with this hypothetical scenario:
Jessica orders a dress for a friend’s wedding that's four days away, choosing the retailer’s two-day delivery. The OMS confirms her purchase, but an inventory system error shows it as in stock at a nearby store for e-commerce fulfillment when, in reality, it’s sold out. The next day, the same dress is located at a warehouse 500 miles away, and the order is re-routed, adding a day in transit.
Three days after the order was placed, it’s out for delivery, but the truck breaks down on the way. Due to poor fleet visibility, a delivery status update isn’t communicated to Jessica. On top of that, an address change she entered on the e-commerce website goes into the CRM, but this data isn’t synced with the TMS. So, a driver leaves the package at her old address. Jessica, anxiously trying to track her order, contacts customer service, but a lack of synchronization between systems leaves her without answers. The dress finally arrives — a day after the wedding — and a high-value customer is lost.
This unhappy ending demonstrates how vital seamless communication is, given the intricate nature of today's supply chains, where even a minor failure has financial repercussions. Think, for example, of the high cost of customer acquisition vs. retention.
We’ll now look at three specific challenges of supply chain communication faced by organizations today.
Fragmented Systems
Fragmented systems create significant barriers to effective communication. This disconnection leads to the creation of information silos across disparate systems, making it hard for each operations team to access accurate, consistent data. Poor integration hampers their ability to coordinate assets and tasks, increases the likelihood of errors, and reduces operational efficiency.
Inconsistent Data
Inconsistent data poses a major supply chain challenge, as variations in formats and sources lead to bad information and worse decisions. This undermines the reliability of communication, causing confusion and errors. Ultimately, it hampers your ability to coordinate effectively with other functional teams, limiting efficiency and dinging customer satisfaction.
Manual Processes
Manual processes increase the risk of errors and slow down the flow of crucial information. Depending on paper-based methods often causes delays and makes it difficult to maintain accurate, timely communication. This ultimately impacts decision-making and results in poor operational performance.
To quote Strother Martin to Paul Newman as the cruel prison captain in “Cool Hand Luke”: “What we’ve got here is … failure to communicate.” Updates from manual processes, sometimes using Excel sheets, is a recipe for disaster, especially considering the need for real-time data sharing between systems, internal teams, carriers, 3PLs, and customers.
Integrated Communications: Revolutionizing Coordination with Supply Chain TMS
Tramm has developed an innovative TMS solution that integrates supply chain communications in a single powerful, intuitive platform. It ties together order management, route optimization, planning and scheduling, carrier management, a control tower for shipment visibility, and a mobile app with customizable workflows and electronic proof of delivery (ePOD) for driver management.
A true supply chain TMS, Tramm offers broad optimization across many aspects of logistics operations, from order processing to delivery, carrier billing, returns, and exception management. The results are greater efficiency, reduced costs, improved performance (order accuracy, on-time delivery, etc.), and enhanced customer satisfaction.
Tramm’s configurable solution has many automation capabilities for a variety of supply chain functions, including alerts for off-plan events, automated reporting, driver debriefing, and communication via standard tools (WhatsApp, email, SMS) with customers, drivers, and managers.
Here are more details on different aspects of Tramm TMS and what sets it apart from traditional solutions.
Platform Unification
Tramm TMS addresses the problem of fragmented supply chain systems by integrating key functions into a unified, scalable platform. It centralizes data, ensuring consistency, accuracy, and integrated communication. The FleetVision control tower provides real-time visibility into vehicle location and ETAs, route adherence, and load status.
Transportation managers can set up customized, automated workflows to manage drivers and routes via the Tramm mobile app. For instance, it can include detailed instructions such as the level of signature required for each stop, when to scan a code, if a confirmation picture is required, etc.
Information from the app is fed back into the Tramm system for planning, reporting, and performance management purposes. For instance, location data from the driver’s device is compared to the onboard GPS to identify any errors or inconsistencies.
Seamless Data Integration
Tramm TMS centralizes all supply chain data in an accessible, intuitive platform with mobile access. This ensures data consistency and accuracy, eliminates discrepancies, and provides organizations with a single source of truth. Real-time updates and automated workflows further enhance data reliability, improving decision-making and overall supply chain efficiency.
Data usability and accessibility are some of the main benefits. Team members across supply chain functions get access to precise data and analytical insights for improved performance monitoring, planning, and reporting.
Tramm’s platform brings in data from internal as well as external partners (carriers, brokers, freight forwarders, 3PLs, etc.) via APIs. Drivers, managers, planners, and executives all get a unified view via the app to real-time tracking and status information, hours of service remaining, precise delivery locations and pickup requirements, KPIs, and much more.
Automated Supply Chain Accuracy
Tramm TMS alleviates cumbersome manual processes by automating key workflows to reduce reliance on manual data entry and paper-based methods. It streamlines operations with dynamic updates, integrated communication tools, and centralized data management.
Tramm’s rules-based order processing automates things like order splitting based on operational and resource requirements, as well as designated delivery days and windows for end customers, with the option of manual intervention where necessary. Tramm’s dashboard includes automated reporting, analytics, and business intelligence capabilities. This empowers decision-makers with a clear understanding of operations, performance, and growth opportunities.
Jessica’s Story, Reimagined
Now, let’s return to our earlier example of the fictional Jessica and her ill-fated dress order, with Tramm as the hero of the story.
Jessica orders her dress, and Tramm’s OMS confirms her purchase, pulling directly from the retailer’s inventory management system to confirm it’s in stock. Tramm also selects the optimal carrier and delivery window based on the customer’s location and the retailer’s requirements, handing this information off to the TMS for dispatch.
On the promised date, the driver, using the Tramm mobile app, notes Jessica’s delivery preference (side door). The ePOD function notifies the system of a successful dropoff for performance monitoring and reporting. Jessica, meanwhile, having received regular notifications of the order in transit at every scan, is thrilled with the experience (and the dress). She has a blast at the wedding, and the retailer gets a smiley rating from their happy customer.
Yesterday’s TMS Can’t Handle Today’s Exacting Supply Chain Communication Needs
How is it possible to have an optimized, efficient supply chain when internal and external data is siloed, and stakeholder communication sometimes feels like today’s equivalent of cans and strings? Answer: it’s not possible.
This leads to all kinds of negative downstream effects: missed opportunities, time-consuming manual processes to cover system gaps, inadequate reporting, and business intelligence insights, poor visibility into assets and deliveries, increased costs, and dissatisfied customers.
Tramm’s unified suite enables shippers, 3PLs, carriers, and their partners to accurately communicate the intricacies of day-to-day supply chain operations. Through our powerful app, control tower visibility, customizable dashboard, and precision planning capabilities, companies can increase efficiency and optimize execution. Analytics and reporting, including KPI-based internal and external scoring, lead to smarter decisions and better outcomes for customers and businesses.
To learn more about how Tramm can make a difference by unifying your supply chain communications, request a demo today.
Related Resources
Managing Large Order Loads to Reduce Split Shipments
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.
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.
Route Optimization: The Key to Effective Logistics Planning
Listen to any quarterly earnings call from major logistics services firms like UPS and FedEx, and you’re bound to hear a plethora of statistics that deal with delivery performance: average miles per delivery stop, stops per route, packages per driver hour, cost per package, on-time delivery rate, etc.
These figures matter a great deal because they help determine the company’s profitability (or loss) that quarter, as indicators of operating performance expressed in KPIs. They also have a great deal to do with the concept of route optimization, the art and science of executing deliveries as efficiently as possible.
Within the broader scope of logistics planning – coordinating the movement, storage, and flow of goods within a supply chain – route optimization plays a key role. Transportation managers put a great deal of effort into reducing total miles, eliminating delays, and improving route density metrics (number of stops, packages per stop, per driver, etc.). Performance goals include higher on-time rates, lower operating costs, and higher customer satisfaction, among other key business objectives.
We’ll take a closer look at route optimization, why it matters, how it’s achieved, and the technology behind it.
Aspects of Route Optimization
In logistics and transportation, whether truckloads from a plant to a distribution center or stepvans from a hub to a local run, route optimization involves finding the most efficient travel paths. Factors include the distance between points, traffic patterns, delivery windows, fuel costs, and vehicle capacity.
Determining the best fleet to use in each case is also an important success factor. Transportation managers must not only select between different vehicle types and sizes for each set of deliveries, but also the right number of each type based on fixed and variable costs. Fixed costs include driver salaries and wages, vehicle leasing or depreciation, insurance, licensing and permits, and administrative costs. Variable costs include fuel, driver overtime, maintenance and repairs, tolls, loading and unloading, and third-party fees when using a logistics provider.
In addition to vehicle type and size, other route optimization variables include product suitability and restrictions (i.e., refrigerated), road networks, customer time windows, backhaul opportunities, driver hours of service (HOS), efficient load building, and fuel/rest stop planning.
Balancing fixed and variable costs is important because it helps achieve route optimization by minimizing the total cost per delivery while maintaining efficiency and delivery schedules. By selecting the right number of vehicles, adjusting for stop density, and optimizing distances, businesses can achieve substantial savings and performance gains.
Why Route Optimization is Crucial
Through route optimization businesses can achieve greater cost efficiency, improve delivery performance, and foster sustainability. By identifying the most efficient travel routes, they can minimize fuel consumption, lower labor costs, and reduce vehicle wear and tear. This is particularly important in a competitive environment where even small cost savings can spell the difference between a division’s profit and loss.
Optimized routing helps ensure timely deliveries, improving service reliability and customer satisfaction. From an environmental perspective, it means reduced fuel usage and lower carbon emissions, supporting sustainability initiatives and regulatory compliance. This is also something that can resonate with customers who value greener transportation.
Route optimization also helps companies maximize resource utilization through increased efficiency of vehicle, driver, and asset usage. By balancing fleet capacity, stop density, and delivery schedules, transportation managers can reduce empty miles and truck idling. The result: more streamlined operations, better use of resources, and improved performance.
Logistics Challenges Affecting Route Optimization
It’s hard to believe given technological advances across logistics functions, but manual route planning is still widespread, especially among small to mid-sized businesses. Many companies continue to rely on a combination of spreadsheets, paper maps, or simple routing tools for delivery and route planning. These methods are often in use when delivery volume is manageable and the network is relatively small. But they are inefficient, lack scalability, increase costs and risk customer dissatisfaction.
As supply chains become more complex and expectations increase, the use of route optimization software is growing. Advanced tools like transportation management systems (TMS), GPS tools, and AI are becoming much more common. They all leverage real-time data, machine learning and predictive analytics to optimize routes based on factors such as traffic, weather, fuel costs, and delivery windows.
Larger enterprises – both logistics providers and shippers – rely heavily on advanced route optimization technology to manage vast delivery networks. As e-commerce growth and customer expectations rise, more companies are shifting toward automated solutions to stay competitive and improve operational efficiency.
The Role of Technology
Technology has revolutionized route optimization, enabling businesses to streamline logistics and reduce costs. Route optimization software integrates GPS, telematics, and algorithms, analyzing real-time and historical data to create the most efficient travel paths. These tools consider variables like traffic patterns, weather, delivery time windows, and vehicle capacity.
AI and machine learning enhance these capabilities with predictive analytics, looking at traffic trends, fuel costs, and customer demand to anticipate delays and proactively recommend adjustments. Machine learning models continuously refine routing strategies by analyzing historical data, improving accuracy and adaptability.
By integrating these technologies into logistics planning, companies can reduce total miles driven, minimize delays, and optimize resource use. This helps them achieve their key goals (cost savings, higher on-time delivery rates, improved customer satisfaction).
Key Features of Route Optimization Software
Route optimization software gives logistics managers an advanced tool for improving efficiency and reducing costs. A key feature is vehicle selection. When the optimal vehicle is chosen for each route based on capacity, cost, and suitability, it maximizes utilization and reduces costs. Dynamic route adjustments allow for real-time updates based on changing traffic, weather conditions, or unexpected delays, helping maintain on-time performance.
Multi-stop optimization efficiently sequences stops for deliveries, reducing total miles driven and improving route density. Beyond basic stop sequencing, route optimization software should be designed to handle the complexity, nuances and business rules of each company. This could include factoring things like load building based on relative item weight, customer delivery windows, and site restrictions, to optimize stop sequencing.
System integration ensures seamless communication with WMS, TMS, and fleet management systems (FMS), providing end-to-end visibility across functional areas. And driver behavior analytics enhance efficiency and safety by monitoring factors such as speed, braking patterns, and fuel consumption.
Best Practices for Implementation
Successfully implementing route optimization software requires a strategic approach. Start by defining clear objectives that align with your business goals. This includes identifying key metrics such as cost savings, delivery speed, or carbon emissions reduction in order to measure success effectively.
Invest in scalable technology that can grow with your business. As you expand or deal with demand spikes, the solution should be able to adapt to meet changing demands without disrupting workflows.
Provide thorough training in order to maximize the benefits of routing tools. A well-trained workforce leads to better decision-making and greater efficiency.
Prioritize continuous monitoring and adjustment. Real-time analytics can identify inefficiencies, respond to changing conditions, and fine-tune processes. Regular reviews ensure the system continues to deliver value over time and adapts to evolving challenges.
Partnering with the Right Technology Provider
Key characteristics to look for include proven expertise in logistics software and analytics, as well as an understanding of your industry's specific needs. Scalability is another important requirement, future-proofing the technology so it can grow with your business and adapt to changing needs. The ability to provide seamless integration via API or EDI with WMS, TMS, and FMS sets up real-time data sharing and better collaboration across the supply chain.
The right provider should be able to deliver a realistic implementation timeline that factors in data readiness, integration complexity, user training and any customization. For SMBs with fewer requirements, it can happen in a matter of weeks; in more complex enterprise scenarios it can take 3-6 months, often in a phased rollout.
Continuous updates ensure the technology stays on track with advances in AI, machine learning, and predictive analytics. The provider should also be able to deliver a tailored solution that addresses your unique requirements. This will help optimize performance, increase efficiency and cost savings, and improve delivery speed and accuracy, delighting customers and building loyalty.
A Tech-Driven Route To Greater Transport Efficiency
Route optimization has become a cornerstone of supply chain management, and a reliance on outdated manual processes falls woefully short of achieving its goals. Through advanced technology, businesses can become more efficient, save on costs, and improve customer satisfaction and sustainability.
Tramm, an innovator in supply chain technology, has developed a cloud-based end-to-end TMS platform that combines route planning and load building, transporter management, order management, a logistics control tower, and a mobile app. With this approach, Tramm has solved the problem of fragmented supply chain systems, integrating key functions into a unified, scalable system.
Tramm’s Planning and Optimization Module leverages powerful algorithms to handle complex routing environments, accounting for variables that accurately reflect on-the-ground transport operations. Its dynamic multi-day route planning handles scheduling for primary, secondary, and service-based fleets. Users can easily make real-time adjustments based on changing needs, including “what if” visualization and scenarios. A load builder/stackability app automatically plans loads that are tightly synced with capacity and route optimization.
To find out how Tramm’s unified approach can drive transportation efficiency and cost savings while helping you realize sustainability goals, 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.
