Logistics Optimisation: Complete Guide from Shipping to Final Delivery

Key Takeaways

• Logistics optimisation turns guesswork into a repeatable system: the right stock in the right warehouse, on the right carrier, at the lowest cost-to-serve.
• Logistics is no longer a footnote in the P&L: U.S. business logistics costs hit US$2.58 trillion in 2024, 8.8% of GDP, against a 7.4–7.8% pre-pandemic norm. [1]
• Last-mile delivery alone now swallows 53% of shipping spend, up from 41% in 2018, making it the single biggest lever for cutting cost-per-order. [2]
• Five moves do most of the work: distributed inventory, carrier diversification, order consolidation, dynamic routing, and tighter returns handling.
• The real unlock isn’t OMS or WMS alone: it’s the two working together, turning fulfilment from reactive firefighting into predictive planning.

Every extra warehouse, carrier, and market a business adds multiplies the ways an order can go wrong, and each failure point adds cost. For enterprises managing fulfilment across regions, that complexity is no longer a background risk: it shows up directly in the P&L.

Logistics costs remain well above pre-pandemic levels, and fragmented markets and inconsistent carrier networks push that pressure higher still. [1] The strain compounds for businesses selling across marketplaces such as Amazon, Shopee, Lazada, and TikTok Shop alongside branded webstores. Every sales platform enforces its own delivery-speed expectations, regional infrastructure varies by market, and regulatory requirements shift from country to country.

Additionally, unoptimised logistics erodes margin faster than almost any other line item in this environment. A single percentage point of avoidable cost-per-order compounds fast across a multi-million-order book, turning a small inefficiency into a material loss at scale.

This guide covers what logistics optimisation is, the core areas it addresses, the strategies that drive measurable efficiency gains, and how to evaluate logistics optimisation software that fits enterprise-scale operations. Understanding the distinction between logistics vs. supply chain management is a useful starting point for framing where optimisation efforts deliver the most value.

1. What Is Logistics Optimisation?

Logistics optimisation is the application of data, technology, and process design to minimise cost and maximise speed across the physical movement of goods. It covers warehouse operations, transportation routing, carrier selection, inventory positioning, and last-mile delivery.

Unlike general supply chain management, which encompasses procurement, demand planning, and supplier relationships, logistics optimisation focuses specifically on the execution layer: how product moves from storage to the customer as efficiently as possible.

In practice, logistics optimisation involves decisions at multiple levels. At the network level, it determines where inventory should be positioned relative to demand. At the operational level, it governs how orders are picked, packed, and routed. At the carrier level, it selects the most cost-effective shipping option for each order based on destination, weight, SLA requirements, and available capacity.

2. Why Logistics Optimisation is Important

Logistics optimisation is important because logistics now eats up a bigger share of operating costs than it used to, and that share keeps rising.
The Supply Chain Xchange report confirms U.S. logistics costs have stabilised at 8.8% of GDP, a full percentage point above the 7.4–7.8% pre-pandemic baseline. [1] For enterprises operating across multiple countries, that shift means logistics is no longer a cost that reverts to normal: it’s the new floor, and any added friction from customs delays, carrier gaps, or SLA penalties sits on top of an already elevated base.

Last-mile delivery is the single most expensive segment of the logistics chain. Statista data shows that last-mile costs now represent 53% of total shipping costs, up from 41% in 2018. [2] For high-volume, multi-channel enterprises, unoptimised last-mile routing adds up to a real, avoidable cost per order, sometimes enough to flip a fulfilment model from profitable to unprofitable.

Beyond cost, logistics performance directly affects marketplace compliance. Platforms such as Amazon, Shopee, and Lazada enforce strict SLAs on dispatch time, delivery speed, and cancellation rates. Failure to meet these benchmarks results in search ranking penalties, reduced visibility, and, in severe cases, account suspension.

3. Core Areas of Logistics Optimisation

Logistics optimisation spans five core operational areas, each of which contributes to total cost-to-serve and delivery performance.

• Warehouse operations: Optimising pick paths, packing workflows, and staging sequences reduces the time between order receipt and dispatch. For operations handling high daily order volumes, even small improvements in warehouse throughput translate to measurable gains in dispatch compliance.
• Transportation and carrier management: Matching each shipment to the right carrier on cost, speed, destination, and parcel characteristics keeps per-shipment costs down and delivery reliability high. Achieving that consistently means negotiating rates, consolidating shipments to cut per-unit costs, and balancing carrier allocation across peak and off-peak periods.
• Inventory positioning: Distributing stock across multiple warehouses and fulfilment nodes based on demand patterns, so that orders ship from the location closest to the customer. Effective logistics network optimisation reduces average shipping distance and transit time simultaneously.
• Last-mile delivery: The final leg from local hub to customer accounts is where the majority of shipping costs lie, making it the highest-leverage area for cost reduction. Optimisation here involves route planning, delivery window management, failed delivery reduction, and returns handling. Reverse logistics, the process of managing product returns efficiently, is a critical component of last-mile cost control.
• Cross-border logistics: For businesses selling across multiple markets, customs clearance, duties calculation, documentation compliance, and landed cost estimation add layers of complexity. Optimisation reduces clearance delays, avoids duty miscalculations, and ensures consistent delivery timelines across borders.

4. How Logistics Optimisation Works

Logistics optimisation works by replacing manual, rule-of-thumb decisions with data-driven logic at each stage of the fulfilment process.

• Data collection: The system set in place aggregates real-time data from warehouse management systems, carrier APIs, marketplace platforms, and inventory databases. This includes stock levels, order volumes, carrier rates, transit times, and delivery SLAs.
• Analysis and decision logic: Optimisation algorithms evaluate the available options for each order: which warehouse has stock, which carrier offers the best cost-to-speed ratio for the destination, whether orders can be consolidated, and whether split shipments should be avoided.
• Execution: Once the optimal path is determined, the system pushes instructions to the warehouse (pick, pack, label), the carrier (booking, manifest, tracking), and the customer (confirmation, estimated delivery, tracking link).
• Feedback and iteration: Post-delivery data (transit time, failed delivery rates, cost-per-order, SLA compliance) feeds back into the system to refine future routing and allocation decisions. Logistics planning that incorporates this feedback loop improves continuously rather than relying on static rules.

5. Logistics Optimisation Strategies That Improve Efficiency

Five strategies consistently deliver measurable improvements in logistics cost optimisation and delivery performance. Each addresses a different point of cost leakage, from where inventory sits to how the last mile gets routed.

a. Distributed inventory positioning

Placing stock in multiple locations based on historical demand data. It reduces average shipping distance, cuts transit time, and lowers last-mile costs. Distributed inventory also protects against bottlenecks. That means if one warehouse is at capacity during a campaign peak (Black Friday, Cyber Monday, 11.11), orders route to the next closest node.

b. Carrier diversification

Relying on a single carrier creates rate dependency and capacity risk. Maintaining relationships with multiple carriers, and using automated selection logic to choose the optimal carrier per shipment, improves both cost and reliability.

c. Order consolidation

Combining multiple items destined for the same customer or region into a single shipment reduces per-order shipping costs and minimises split shipment rates. This is especially important during high-volume campaign periods when fulfilment nodes are processing surge volumes.

d. Dynamic routing

Using real-time data (traffic, weather, carrier capacity, warehouse workload) to adjust routing decisions on the fly rather than following static rules. Dynamic routing is the foundation of e-commerce logistics optimisation at scale.

e. Returns optimisation

Returns represent a significant and growing cost centre. Optimising reverse logistics through automated return authorisation, regional return hubs, and rapid restocking workflows reduces the cost-per-return and accelerates inventory recovery.

6. Benefits of Logistics Optimisation

The benefits of logistics optimisation are measurable across cost reduction, delivery performance, and operational scalability.

Lower fulfilment costs: Optimised carrier selection, route planning, and order consolidation reduce cost-per-order. Given last-mile’s outsized share of total shipping costs, carrier and routing optimisation in the final leg delivers the highest cost impact.

Faster delivery time: Positioning inventory closer to demand centres and using dynamic routing reduces average transit time. For retailers and brands on marketplaces, faster delivery directly improves platform ranking and conversion rates.

Higher SLA compliance: Automated dispatch and carrier selection ensure that orders meet marketplace-mandated delivery windows. This protects seller ratings, search visibility, and access to promotional placements on marketplace platforms.

Scalability without proportional headcount growth: Automated logistics decision-making allows operations to handle volume surges (campaign peaks, flash sales, seasonal demand) without adding proportional manual labour for routing, carrier booking, and tracking.

Reduced environmental impact: Shorter delivery distances, consolidated shipments, and optimised routing reduce fuel consumption and carbon emissions per order. For enterprises with sustainability commitments or operating in markets with emissions reporting requirements, this is increasingly a compliance factor.

7. Common Challenges in Logistics Optimisation

The most common challenges in logistics optimisation stem from data fragmentation, infrastructure limitations, and the complexity of multi-market operations.

• Siloed systems: When warehouse management, order management, carrier systems, and marketplace platforms operate independently, there is no single view of inventory, orders, or logistics performance. Optimisation requires integrated data, and integration is often the first and most difficult step.
• Carrier API inconsistency: Different carriers provide different levels of API capability (rate queries, booking, tracking, proof of delivery). Normalising these integrations to enable automated carrier selection across a diverse carrier portfolio requires middleware or a platform with pre-built carrier connectors and the ability to aggregate required data.
• Multi-country complexity: Enterprises operating across multiple countries face different customs requirements, tax regimes, address formats, and carrier networks in each market. What works in one market does not automatically translate to the next, whether that is Germany to France or Malaysia to Indonesia. 3PL partners with regional expertise help bridge this gap, but the orchestration layer must still accommodate market-specific rules.
• Peak demand volatility: Campaign events (Black Friday, Cyber Monday, 11.11, Ramadan sales) create order volume spikes that stress warehouse capacity, carrier availability, and delivery SLAs simultaneously. Optimisation strategies must account for peak scenarios, not just steady-state operations.

8. Role of OMS and WMS Technology in Logistics Optimisation

An order management system (OMS) and warehouse management system (WMS) are the two systems that power logistics optimisation at scale. Together they form the operational backbone that connects order intelligence with warehouse execution.

Order management systems centralise order capture from all sales channels, apply routing logic to determine the optimal fulfilment path, manage carrier selection and booking, and provide end-to-end visibility from order placement to delivery confirmation. For enterprises selling across marketplaces and branded webstores, an OMS is the orchestration layer that ensures every order follows the most cost-effective and SLA-compliant path.

Warehouse management systems govern what happens inside the warehouse: inventory storage, pick path optimisation, packing workflows, labelling, and dispatch sequencing. WMS ensures that the instructions generated by the OMS are executed accurately and efficiently at the warehouse level.

The integration between OMS and WMS is where logistics optimisation software delivers its highest value. When both systems share real-time data (inventory levels, order priorities, dispatch status, carrier capacity), the operation moves from reactive to predictive. Logistics network optimisation at this level means routing decisions account for current warehouse workload, carrier availability shifts in response to real-time conditions, and stock rebalancing happens before shortages materialise rather than after.

9. Logistics Optimisation for Omnichannel E-commerce

E-commerce logistics optimisation for omnichannel operations requires treating every inventory location (warehouse, retail store, 3PL facility) as a potential fulfilment node.

In a single-channel model, logistics decisions are relatively linear: order comes in, warehouse ships it out. In omnichannel commerce, the same inventory must serve marketplace orders, webstore orders, B2B orders, and in-store customers. The challenge doesn’t necessarily have inventory. It is making inventory visible and allocable across every channel simultaneously.

Logistics optimisation for omnichannel addresses three specific problems. First, inventory fragmentation: stock sitting in a retail location while online orders show “out of stock” because the systems are not connected. Second, fulfilment cost inflation: shipping from a central warehouse to a customer when a closer retail store or regional 3PL had the stock available. Third, delivery speed inconsistency: marketplace orders demand next-day delivery, but click-and-collect and ship-from-store requests routed through the same store create conflicts the system can’t resolve on its own.

Anchanto’s order management platform enables real-time inventory visibility across all nodes and automated order routing that selects the optimal fulfilment location based on proximity, stock availability, SLA requirements, and cost.

10. Choosing the Right Logistics Optimisation Software

The right logistics optimisation software connects every channel, carrier, and fulfilment node into a single decision layer. Here is what to evaluate.
Multi-channel integration. The platform must connect to every sales channel you operate (marketplaces, webstores, B2B portals) and aggregate orders into a single management view. Evaluate the depth of marketplace-specific integrations for the platforms you sell on, such as Amazon, Shopee, Lazada, and TikTok Shop.

• Carrier connectivity. Assess how many carriers the platform supports natively and how quickly new carriers can be added. This includes local last-mile carriers, national postal services, and cross-border logistics providers in each market you operate in.
• Routing and allocation logic. The platform should support configurable rules for order routing: closest warehouse, lowest cost, fastest delivery, or a weighted combination. Static FIFO (first in, first out) allocation is insufficient for multi-node operations.
• Scalability under peak load. Evaluate whether the platform can handle volume surges during campaign events without degradation in processing speed or routing accuracy. Ask for specific benchmarks on orders-per-minute throughput during peak periods.
• Reporting and analytics. Logistics cost optimisation requires visibility into cost-per-order, carrier performance, SLA compliance rates, split shipment rates, and return rates. The platform should provide this data at the channel, warehouse, carrier, and SKU level.

11. What Logistics Optimisation Actually Requires

Logistics optimisation is what separates enterprises that scale profitably from those that scale into margin erosion. Every additional channel, warehouse, carrier, and market adds complexity that manual processes cannot absorb.

The operational priorities are clear: position inventory closer to demand, automate carrier selection and routing, integrate warehouse and order management systems, and measure performance at the cost-per-order level. For enterprises operating across multiple markets, these priorities are not optional. They are the baseline for meeting marketplace SLAs, managing campaign peaks, and maintaining delivery performance across borders.
Anchanto’s order management system provides the orchestration layer that connects inventory, orders, carriers, and warehouses into a unified system, enabling logistics optimisation at the speed and scale that enterprise commerce demands.

FAQs

1. What technologies are used for logistics optimisation?

The core technologies are order management systems (OMS), warehouse management systems (WMS), transportation management systems (TMS), route optimisation algorithms, and carrier API integrations. AI and machine learning are increasingly used for demand forecasting, dynamic routing, and predictive carrier selection.

2. Can logistics optimisation reduce shipping costs?

Yes. Optimised carrier selection, order consolidation, distributed inventory positioning, and route planning consistently reduce cost-per-order. Last-mile delivery represents the largest single share of total shipping costs, making it the highest-impact area for logistics cost optimisation. [2]

3. What KPIs should businesses track for logistics optimisation?

The most operationally relevant KPIs are: cost-per-order, on-time delivery rate, SLA compliance rate by channel, split shipment rate, average transit time, failed delivery rate, and return processing cost.

4. How can businesses improve logistics efficiency?

Start with data integration: connect order management, warehouse management, and carrier systems into a single platform. Then implement automated carrier selection, distributed inventory positioning, and dynamic routing. Measure results at the cost-per-order and SLA compliance level.

5. When should a business invest in logistics optimisation software?

The most common triggers are: order volumes exceeding manual processing capacity, expansion to new marketplaces or geographic markets, rising cost-per-order, SLA compliance failures on marketplace platforms, and operational bottlenecks during campaign peak periods.

6. How does AI help in logistics optimisation?

AI improves logistics optimisation through demand forecasting (predicting order volumes by location and time period), dynamic routing (adjusting carrier and route selection in real time based on conditions), anomaly detection (identifying delivery failures or cost spikes before they compound), and automated carrier rate optimisation.

References

[1] Thescxchange.com – “State of Logistics Report” highlights growing uncertainty after a year of relative stability

[2] Statista.com – Share of last-mile delivery costs out of total shipping costs in 2018 and 2023