Logistics decarbonization: 7 concrete levers your WMS can activate

A few years ago, decarbonization was a topic of communication. A page in the annual report, a green logo on the website, a tree planting.

Today, it is a subject of a call for tenders.

Ask any 3PL provider who responds to requests for proposals from major shippers: the rating grid now includes an environmental column. Sometimes it accounts for 10%, sometimes 20% of the final score. And this column is filled with kg of CO₂e per package shipped, fill rates, and quantified improvement plans.

The setting has completely changed, but what about your logistics?

When you talk to logistics directors, the same phrase comes up: "We want to decarbonize, but we don't know where to start, and we don't have the budget for an electric fleet."

Decarbonizing a warehouse doesn't begin with a hardware investment. It begins with a much more mundane question: how many unnecessary movements do you make each day?

A forklift operator who travels 12 km per shift instead of 8. A truck that leaves 68% full. An order prepared with an error, resulting in a return, reshipment, and a second check. An item stored in a cold storage area when it doesn't need to be.

Each of these micro-wastes is invisible individually. Multiplied by 250 working days and by 8,000 daily order lines, they become your main source of carbon emissions, and your main source of savings.

Perhaps you're wondering how to find out all this? Well, thanks to a tool you almost certainly already have: your Warehouse Management System. The only thing left is to make it work.

Why WMS is the tipping point for green logistics

Carbon in logistics: Where is it really?

Before taking action, you need to map things out. Too many sustainable supply chain initiatives fail because they focus on the most visible aspect rather than the most significant one.

To help you get a clearer picture, here is the typical breakdown of emissions in a downstream supply chain (warehouse + distribution):

Indicative distribution constructed from the orders of magnitude published by ADEMEand the GLEC Framework of the Smart Freight Centre.

The message is clear: transportation is everything. But it would be naive to conclude that the warehouse doesn't matter. Because it's in the warehouse that truck capacity and the quality of shipments are determined.

The warehouse is not the biggest emitter. It is the biggest decision-maker regarding emissions.

What your WMS already knows (and that you're not using)

Let's take stock of the dormant data in your WMS solution:

• The dimensions and weight of each SKU (if your item repository is correctly populated)
• Theexact location of each stock unit, at the cell level
• Therotation history of each item, day by day
• The picking path actually taken by each order picker
• The error rate per operator, per zone, per type of flow
• The volume and weight of each order before shipment
• The carrier involved, the mode of transport, the promised delivery time
• Reasons for return and their frequency

Each of these data points is a carbon sensor that is unaware of itself.

The transition from operational data to environmental data does not require a system overhaul. It requires configuring business rules and, often, standardizing the product repository.

That's exactly what we do for our clients: we don't sell a green module. We configure logistics flows so that the most efficient path becomes the default path.

Lever #1 — Load Optimization: Stop Transporting Air

Trucks often half empty

According to data from the Ministry of Ecological Transition, the empty journey rate for French heavy goods vehicles is around 20 to 25% of the kilometers traveled. And when trucks are loaded, they are rarely at full volumetric capacity.

At the European level, the European Environment Agency believes that improving load factors is among the most effective and least expensive levers for reducing road freight emissions.

In practical terms, for you as an operator, this means that every semi-trailer that leaves at 70% volumetric fill means 30% of diesel fuel is burned to transport air.

On a fleet of 15 daily rotations, this can represent the equivalent of 4 ghost trucks per day!

What WMS can actually do

A WMS software acts on loading at four levels:

1. Upstream palletization calculation

The WMS knows the unit dimensions, stacking capacities, fragility constraints, and product incompatibilities. It can therefore calculate the correct palletization plan even before the order picker begins.

The tangible result : fewer pallets for the same volume of goods. Saving one pallet out of ten means 10% less truck space.

2. The intelligent constitution of shipping units

Calculated packing allows for the automatic selection of the most suitable cardboard box from a defined range. Over-packaging is one of the most foolish carbon-inefficient aspects of logistics: cardboard is manufactured to transport empty space, then this empty space is transported, and then it is recycled.

According to several industry studies on e-commerce, the average empty space rate in shipped packages frequently reaches 57%. A well-configured WMS reduces this figure to significantly lower levels.

3. Order consolidation

Three orders for the same customer, shipped on the same day, in three separate packages? At this level, it's a configuration failure, not an inevitable occurrence.

The WMS can apply consolidation rules: short time delay, grouping by recipient, by route, by postal code.

4. Cross-docking

Cross -docking  is the most elegant decarbonization lever available: it simply eliminates the storage stage. Goods are received at the delivery dock, broken down, and then shipped out again the same day.

Less handling. Less space occupied. Fewer machines needed. And a shorter lead time. In short, what more could you ask for?.

The WMS, for its part, orchestrates the matching between the expected receipt of goods and the ongoing shipping needs.

Lever #2 — Choosing a low-carbon carrier: From intuition to informed decision-making

The regulation wall is arriving faster than expected

In France, the GES information system for transport services (derived from the Transport Code, articles L.1431-3 et seq.) already requires carriers to communicate the emissions of their services to their customers (Legifrance / ADEME, official methodology).

In practical terms, this means that the data exists. But the problem is its lack of integration into the decision-making process.

The moment of truth: The carrier assignment

In most warehouses, the allocation of the carrier is based on two criteria: price and delivery time.

A WMS connected to a logistics TMS (Transport Management System) can introduce a third criterion: the carbon intensity of the service provider on the route considered.

This multi-criteria selection logic changes everything. The question is no longer "which is the cheapest carrier?" but "which carrier has the lowest emissions among those that respect the customer's deadline and stay within my budget ?"

It's a trade-off, not a sacrifice.

Criteria to include in your selection matrix

Criteria related to the service provider:

• Fleet engine options (Euro VI, CNG/bioCNG, electric, hydrogen)
• Membership in recognized programs: ADEME's CO₂ Target charter and label , FRET21 for shippers
• Existence of a published and verified GHG inventory
• Reported average occupancy rate
• Eco-driving training policy

Route-related criteria:

• Available modes of transport (road / rail / river / combined)
• Actual distance, not theoretical distance
• Network density in the area (a dense carrier = fewer empty kilometers)
• Proposed solution for the last few kilometers (cargo bike, electric van, relay points)

The topic of the last few kilometers

The last mile  alone accounts for a very significant share of the cost and emissions of the urban distribution chain, while it represents only a fraction of the total distance.

To limit its impact, you can use several levers:

• Promote collection points by offering the option from the moment the order is placed (fewer delivery failures = fewer returns)
• Reduce delivery failures with clean address data and a reliable delivery window
• Group deliveries by geographical area using a route-based approach

A failed delivery means a doubled journey. This is the worst possible carbon scenario, and it is almost always due to faulty data or communication.

Lever #3 — Optimized Picking: Every step counts, every step costs

Over 50%: The figure every warehouse manager should keep in mind

In a typical warehouse, movement accounts for a major portion of order preparation time. Industry estimates consistently suggest that 50 to 60% of a picker's time is spent solely on movement.

Yes, yes, you read that right.

Half of the time your teams are paid for is not spent picking items. It's spent walking.

Walking takes time, and therefore costs money. But it also means, at a constant volume, more hours of building lighting, heating, ventilation, more equipment rotations, and more fatigue, therefore more errors.

Picking is the beating heart of the warehouse. It is also its main source of internal decarbonization.

The mechanics of optimizing the sampling path

Good warehouse management software has several tools at its disposal to shorten journeys:

Path optimization

The WMS does not simply sort lines by location number. It calculates a route taking into account the actual topology: direction of traffic, one-way streets, access constraints, congestion zones.

Batch picking

Instead of walking down aisle A once per order, the order picker walks down it once for every ten orders. The benefit is immediate, especially for e-commerce businesses with a low number of line items per order.

Picking by zone (zone picking)

Each order picker remains within their designated area. In this scenario, it's the orders that circulate, not the people. This approach reduces the number of people traveling and also allows for specialization by product type.

Goods-to-man and robotization

When the volume justifies it, the logic is reversed: it is no longer the man who goes to the product, but the product that comes to the man thanks to multiple systems: Mobile robots, AMR robots, AGV robots , goods-to-man systems, guided order picking carts

automation and mechanization are not purely about productivity. When properly designed, they eliminate kilometers, space, and hours.

However, be aware : A poorly managed automated system can consume more energy than it saves. The WMS remains the central control unit. Without it, the system runs on empty.

The direct link between picking error and carbon

Here is a sequence that every logistics professional knows, but that few quantify in terms of emissions:

1. Warehouse picking error
2. Package shipped
3. Dissatisfied customer → complaint
4. Return route of the package
5. Return processing, inspection, restocking
6. New order preparation
7. New expedition

A single error therefore generates two additional trips and two complete handling cycles.

This is why the zero-error approach is simultaneously a quality, economic and environmental approach.

Lever #4 — Sustainability-driven slotting: Installation becomes an environmental choice

Slotting, this neglected discipline

Ask a logistics manager when their warehouse layout was last revised. The answer is often: "when the site opened".

However, slotting, the allocation of references to locations, is probably the most structuring decision for your operation. It alone determines a major portion of the kilometers traveled daily.

The basic principle is well-known: The ABC method, or ABC classification, places high-turnover items as close as possible to shipping areas and at an ergonomic height. A-listed items typically represent 20% of the items but account for 80% of stock movements.

Classic, effective, but… Insufficient.

Durability slotting: a broader perspective

What we call sustainability slotting involves integrating environmental criteria into the allocation algorithm, in addition to the rotation criteria.

Specifically, four additional dimensions:

1. Thermal constraint

Not all products require the same temperature. How many items are stored in cold or temperate zones unnecessarily?

Refrigeration is the number one energy expense for warehouses that have it. Every cubic meter of unnecessary refrigeration is a pure expense.

The WMS can apply a simple rule: an item will only go into a constrained area if its product record requires it. Furthermore, it can detect existing layout anomalies.

2. Volumetric densification

A well-located warehouse stores more in fewer square meters. And every square meter is heated, lit, ventilated, insured, and depreciated.

The WMS can recommend storage bay changes based on actual volume changes per SKU. For example, a product whose volume has plummeted doesn't belong in a double-depth bay.

3. Expiration and markdown

Here is a point that many environmental initiatives forget: the destroyed product is the worst possible carbon scenario.

In the food, pharmaceutical, and cosmetics industries, managing expiration dates (use-by, best-before, and best-before dates) using FEFO (First Expired, First Out) is a business imperative. It is also a major lever for decarbonization.

Logistics traceability software, imposing FEFO at the location level and not at the reference level, mechanically reduces destruction.

4. Dynamic slotting

Product turnover is not constant. It varies according to seasons, promotions, and life cycles.

Dynamic slotting involves periodically recalculating the optimal layout based on actual data from recent weeks. Some WMS platforms incorporate predictive logic capable of anticipating increased demand.

Note : rearrangement also has an energy cost. Intelligent dynamic slotting weighs future gains against the cost of the movement. Moving 400 items every week makes no sense.

Slotting decision matrix

A field observation on product affinities

Affinity analysis (which references consistently appear together in orders) is one of the most profitable and least practiced analyses.

If two items are ordered together in 60% of cases and are located at opposite ends of the warehouse, you pay for this difference several thousand times a year, whether in time, euros and carbon.

The data is in your WMS. It's up to you to make it speak using a query.

Lever #5 — Zero errors and returns management: Avoided carbon is the best carbon

The return, a blind spot in decarbonization

In e-commerce, return rates reach considerable levels depending on the sector. Fashion and apparel are among the most affected. Each return triggers a complete chain: return shipping, receiving, quality control, possible repackaging, restocking, or destruction.

Reverse logistics is structurally more emissive than forward logistics because it is less massified, less predictable and more manual.

Two types of returns coexist:

• Involuntary returns (the customer changes their mind): we can reduce them, but not eliminate them
• Induced returns (preparation error, breakage, non-conforming item): these can be eliminated

It is the latter that should mobilize you as a priority, because they are 100% your responsibility.

How does a WMS eliminate forced returns?

Systematic scanning

The principle is simple: no item is added to a package without having been scanned and validated. The WMS rejects the line if the code does not match.

The error thus becomes impossible rather than detectable.

Weight control

The theoretical weight of the order is compared to the actual weight at the end of packing. If the difference exceeds the tolerance, the package is held. This technique detects omissions and duplicates, even for small items.

Quality control upon receipt

Many customer errors originate during the goods receiving process. An item that is incorrectly identified upon entry will be incorrectly prepared upon departure.

A WMS that enforces control of quantities, references, batches and expiration dates at the entry point secures the entire downstream chain.

Real-time traceability

Real-time traceability, via batch number and serial number, makes it possible to precisely target the units concerned in the event of an anomaly.

The product recall will affect a specific batch rather than an entire range. That's the difference between recalling 200 units and 20,000. In the food and pharmaceutical industries, the carbon (and financial) difference is clearly significant.

Structuring the management of incoming returns

For returns that you cannot avoid, the objective changes: maximize restocking, minimize destruction.

This implies:

• A rapid qualification process : the longer feedback is delayed, the more its value degrades.
• A clear decision grid : restocking / refurbishment / second-hand / destruction
• A statistically usable follow-up on the reasons for return
• A feedback loop to purchasing and marketing (if a product generates 30% returns, the problem is not logistical)

Lever #6 — Stock reliability and cycle counting: Don't produce what you already have

The phantom stockpile, a silent generator of emissions

An inventory discrepancy is not an accounting problem. It is a physical problem with very real consequences:

• Stock shown as available but not found → order cancelled or urgent restocking (often via express shipping, therefore a very high-emission method)
• Existing but unseen stock → overproduction or overbuying
• Stock tied up without need → space occupied, energy consumed, risk of expiration

Each of these scenarios triggers unnecessary physical flows.

Stock reliability is therefore, very directly, an environmental indicator.

Rolling inventory as the standard

The complete annual inventory is a historical legacy. It immobilizes the site, mobilizes dozens of people for an entire day (sometimes more), and provides a snapshot that is already outdated the next day.

Modern inventory management relies on cycle counting driven by the WMS:

• Split, daily counts, integrated into the normal flow
• Frequency differs according to class ABC (As counted very regularly, Cs more rarely)
• Automatic triggering on event: emptying of location, detected discrepancy, picking anomaly
• No interruption of activity

The environmental benefit is twofold : no downtime to compensate for with overtime, and continuous reliability that avoids emergency flows.

Towards a predictive logic

The most advanced WMS solutions integrate analytical layers: anomaly detection, load forecasting, replenishment recommendations.

Generative AI is currently being implemented primarily in user assistance and data analysis. Agentic AI , a system capable of making decisions and executing actions, remains, frankly, in its infancy in our field. However, this technology is already showing positive results and is very promising.

Digital warehouse twins, on the other hand, offer a very concrete promise: to simulate a relocation, a peak in activity or an investment in mechanization before moving a single pallet rack .

Simulation helps avoid costly mistakes. And avoiding a placement error saves hundreds of hours of equipment use.

Lever #7 — Energy management of the building based on actual activity

The warehouse that consumes when no one is working

How many warehouses light, heat, and ventilate areas where no activity takes place?

This is a totally avoidable waste, and the WMS holds information that the BMS (Building Management System) does not have: it knows where the activity will take place in the next few minutes.

WMS ↔ BMS coupling

The idea is simple and remarkably effective: the WMS emits the planned activity zones, the BMS controls the lighting and heating accordingly.

Practical applications :

• On-demand lighting by aisle, triggered by scheduled preparation waves
• Concentrating nighttime or weekend activity in a limited area rather than dispersing it throughout the site
• Anticipating the opening of the docks to limit heat loss in the cold zone
• Prioritizing traffic flow in thermally constrained areas to reduce door opening times

Optimizing the use of equipment

Yes, it is possible for the WMS to act on the handling equipment fleet via:

• Intelligent task allocation to prevent a forklift from crossing the site empty
• Monitoring equipment utilization rates: an oversized fleet is costly in terms of energy and depreciation.

The subject of surfaces

A warehouse at 65% volumetric fill rate consumes almost as much energy as a warehouse at 90%. Densification is therefore a direct energy lever.

Making better use of height, reducing oversized aisles, reviewing the sizing of cells: these decisions are made based on WMS data, not intuition.

Summary: the 7 levers at a glance

Where to begin?

If you were to remember only one sequence: start with lever 5 (zero error), which costs almost nothing and produces an immediate effect. Follow with lever 3 (picking) and lever 1 (loading), which offer the best gain/effort ratio. The rest will follow naturally.

What really makes the difference: Data and the ability to evolve it

Let's be clear on a point that is often overlooked in sales brochures.

None of these seven levers works without a proper data repository.

No palletization calculation without product dimensions. No intelligent slotting without reliable movement history. No credible carbon reporting without end-to-end traceability.

The prerequisite for any sustainable supply chain is, quite simply, a data quality project. It's less glamorous than a mobile robot, but it's infinitely more crucial.

The second point: your warehouse today will not look like it will in three years.

New customers for 3PL providers, new distribution channels, new regulatory constraints, new types of products.

That's why, when you interview publishers, you should ask them:

"How long, and at what cost, will it take for your solution to be able to do Y when I need it?"

This is generally where the difference between publishers lies.

The specific case of logistics providers: decarbonization as a selling point

A special word for 3PL providers, who are experiencing a unique situation.

You are not just decarbonizing for yourself. You are decarbonizing for your customers, of whom you are a part of Scope 3.

This changes the nature of the issue. Your environmental performance becomes a selling point, just like your service level or reliability.

The shippers who consult you must report their emissions themselves. If they cannot obtain reliable data from you, you become a blind spot in their reporting. And they don't want that blind spot.

Three specific 3PL recommendations:

1. Be able to produce carbon reporting per client, not just overall. That's what your clients expect, and that's what few service providers know how to do today.
2. Leverage shared resources. This is your structural advantage: a multi-client warehouse is inherently more efficient than a collection of dedicated warehouses. Quantify this.
3. Demand that your WMS offer autonomous configuration. A logistics provider never knows their next client. If every new flow requires intervention from your software provider, you'll lose bids, and more importantly, you won't be able to adapt your environmental rules on the fly.

Logistics decarbonization is primarily a matter of operation

Decarbonizing your supply chain won't begin with a spectacular investment. It will begin with a series of operational decisions, made thousands of times a day, that your Warehouse Management System can guide in the right direction.

These decisions can be grouped into seven levers of logistics performance. These reduce costs, improve service levels, enhance team safety, and alleviate the mental burden on operators.

It is no coincidence that they are also reducing emissions: in logistics, carbon waste and economic waste are the same thing seen from two different angles.

And now ?

If you recognize yourself in these situations, the first step is to diagnose your flows.

To achieve this, we propose three ways to move forward:

• A 30-minute consultation with one of our logistics consultants to define your challenges and identify your initial areas for optimization.
• An on-site flow audit to objectively assess your current waste and quantify potential savings
• A demonstration of the EGO solution applied to your own flow types, not a textbook case.

EGO: Warehouse management software, with over 580 satisfied customers already!

Discover how they optimized their logistics with the EGO WMS.

FAQ — Everything you need to know about logistics decarbonization

Does a WMS really help reduce CO₂ emissions from a warehouse?

Yes, but indirectly. WMS software is not a carbon calculation tool. It addresses the physical causes of emissions: kilometers traveled by order pickers, truck fill rates, number of packages shipped, volume of returns, surface area used, and fuel consumption of equipment.

By optimizing these parameters, it mechanically reduces the farm's footprint. The most significant gains generally come from optimizing loading and reducing preparation errors, as these two levers affect transport.

What levers should you start with when you have a limited budget?

By reducing preparation errors, without hesitation.

Systematic scanning and weight control require only minor adjustments or small equipment investments, while each error avoided eliminates a return trip, a reshipment, and double processing. The return on investment is immediate, and the carbon footprint is proportional.

The second most accessible lever is readjusting the picking path in your existing WMS. Many warehouses are still operating with settings dating back to their opening, even though the topology and volumes have changed.

How do I calculate the CO₂ emissions of my supply chain?

Three elements are needed: a defined scope, reliable activity data and recognized emission factors.

For transport, rely on the data that your carriers are legally required to provide you in France, and on the GLEC Framework for the international methodology.

A practical tip : don't aim for perfection in the first exercise. Establish a baseline with the data you have, then refine it year after year.

Is a SaaS-based WMS more environmentally friendly than an on-premise installation?

Generally yes, thanks to infrastructure sharing and better server utilization rates in data centers. A SaaS WMS also eliminates the need for an on-premises server room, which is often oversized and poorly cooled.

But the distinction is important: everything depends on the energy efficiency of the data center and the source of its electricity. Always ask your provider where your data is hosted, what the site's PUE is, and what energy source is used.

What reduction in kilometers can be expected by optimizing picking?

The observed ranges vary greatly depending on the initial configuration.

A simple recalculation of the picking path typically yields a 10% to 25% reduction. Switching to batch picking or zone picking can achieve 30% to 50% savings for e-commerce businesses with a low number of lines per order. Goods-to-person solutions with AMR robots go far beyond this, but require a different kind of investment.

How can I incorporate a carbon criterion into my choice of carriers without blowing my budget?

By reasoning using multi-criteria arbitration rather than a single criterion.

Create a matrix combining price, delivery time, reliability, and carbon intensity, with weightings validated by your management. The WMS or TMS software then automatically applies this rule to each assignment.

In practice, you will often find that the least emissive carrier is not the most expensive, particularly because a good load factor and good network density simultaneously reduce costs and emissions.

Does the mechanization of a warehouse improve its carbon footprint?

Not automatically. That's a common misconception that needs to be qualified.

Warehouse automation reduces human movement and allows for significant storage densification. However, it introduces continuous electricity consumption, equipment manufacturing costs, and maintenance expenses.

The net cost depends on the volume processed, the system's lifespan, and above all, the quality of its operation. A poorly orchestrated mechanized system managed by the WMS runs idle and consumes energy unnecessarily. This is why we systematically recommend simulation before investing, ideally using a digital twin.

How to reduce the impact of returns in an e-commerce context?

Start by distinguishing between unwanted returns (the customer changes their mind) and unwanted returns (your mistake). Only the latter are entirely within your control, and these are the ones you should prioritize eliminating through systematic scanning and weight checks.

Regarding involuntary returns, the objective changes: to maximize rapid restocking. A return processed within 48 hours retains its value; a return processed in three weeks often ends up being destroyed or put into clearance stock.

Finally, analyze your return reasons statistically. If a particular item consistently generates returns, the problem lies upstream (inaccurate product description, incorrect sizing, insufficient quality). Logistics reveals the problem, but it cannot solve it alone.

How long does it take to deploy a WMS and start seeing gains?

The complete cycle, from selection to production, generally extends over 6 to 12 months (or even more) depending on the complexity of the site and the number of interfaces.

But the first gains don't wait for the end of the project. The flow audit phase, at the beginning of the mission, almost always reveals immediate optimizations that can be implemented without delay: readjustment of layout, correction of picking rules, cleanup of repository.

This is actually a good test to evaluate a software publisher. If they only offer to sell you their software without asking about your data flows, move on.