Australia feeds people well beyond our borders. But the part most of us don’t see—the supply chain that sits between a farm gate and a consumer—is where margins are won or quietly lost.

If you work in agribusiness, you already know the feeling: a narrow harvest window, weather that refuses to cooperate, limited transport capacity when everyone needs it at once, and customers (local or offshore) who don’t care about any of that—they just want the product delivered on spec and on time.

Australia’s agriculture supply chain isn’t one chain. It’s a network of thousands of businesses moving food and fibre across a continent, through processing, storage, cold chain, compliance checks, distribution centres, ports and shipping lanes—often under tight time and quality constraints.

This article is a practical guide to how Australia’s agriculture supply chain works, what makes it uniquely challenging, and where the biggest improvement levers tend to sit. It also outlines how Trace Consultants can help agribusinesses, processors, exporters and government agencies strengthen performance, resilience and sustainability.

Ready to turn insight into action? Start with a conversation: Contact Trace Consultants

What “Australia’s agriculture supply chain” actually includes

When people say “ag supply chain”, they often picture trucks leaving farms. That’s part of it—but only one part.

A simple way to define it:

Australia’s agriculture supply chain is the end-to-end system that plans, produces, stores, moves, processes, certifies and delivers agricultural products from inputs and farms through to domestic consumers and export customers.

It typically includes:

• Inputs and upstream suppliers: seed, fertiliser, chemicals, feed, packaging, equipment, fuel, maintenance parts
• On-farm production: cropping, livestock, horticulture, dairy, aquaculture, etc.
• Aggregation and storage: receival sites, silos, cold rooms, packhouses, feedlots, yards
• Processing and value-add: abattoirs, dairies, grain mills, wineries, canneries, packing and grading
• Quality, safety and compliance: testing, certifications, traceability, biosecurity controls
• Transport and logistics: road, rail, intermodal, cold chain, containers, bulk freight
• Export infrastructure: port receivals, container parks, stevedores, shipping schedules
• Domestic distribution: wholesalers, DCs, retailers, food service, online channels

In the real world, the boundaries blur. For example:

• A grower might pack, chill and distribute direct.
• A processor might run its own fleet and export program.
• A cooperative might own storage, rail access or port capacity.

That’s why improving “the agriculture supply chain” isn’t about optimising one link—it’s about improving decisions and handoffs across the full system.

The Australian reality: why agriculture supply chains are harder here

Almost every supply chain leader in Australia has to deal with distance. In agriculture, distance isn’t a nuisance—it’s the operating model.

A few realities make the Australian agriculture supply chain uniquely complex:

1) Geography and freight corridors shape everything

Australia’s production regions are often far from major population centres and even further from export customers. That turns transport into a core cost driver and a core risk.

2) Seasonality creates “all at once” peaks

Most industries can smooth supply and demand over the year. Agriculture often can’t. Harvest windows, live export schedules, and perishable shelf-life create concentrated peaks—and that’s exactly when shared capacity (labour, transport, storage) is tightest.

3) Product integrity is non-negotiable

Fresh produce, chilled dairy, meat and seafood are unforgiving. A temperature excursion, poor pallet airflow, a missed cutoff, or a delay on the tarmac can turn into claims, rework, spoilage—or brand damage.

4) Export complexity is built in

Export chains add handoffs and compliance: documentation, inspections, container availability, port receivals, vessel schedules, and changing destination requirements. These aren’t “edge cases”. For many categories, they’re the standard.

5) Risk is structural, not occasional

Weather variability, water constraints, biosecurity, labour availability, and global trade disruptions aren’t rare events anymore. They’re part of the baseline. Which means resilience must be designed into the chain—not bolted on after a bad season.

A quick “paddock to port” map you can use with your team

If you’re trying to align stakeholders (operations, procurement, logistics, planning, commercial), it helps to map the chain in a shared language.

Here’s a simple flow that works across many Australian ag categories:

1. Plan (demand, acreage, herd, inputs, labour, harvest capacity, pack/processing slots)
2. Source (inputs, packaging, contractors, transport, third-party storage, services)
3. Produce (grow, raise, harvest)
4. Handle (grading, washing, chilling, packing, QA checks, lot capture)
5. Store (ambient, chilled, frozen; bulk, palletised; quarantine/hold zones)
6. Move (farm pickups, linehaul, intermodal, last mile, containerisation)
7. Process / Value-add (where relevant)
8. Export / Distribute (ports, DCs, wholesalers, retail, food service)
9. Measure & improve (service, cost-to-serve, waste, claims, working capital, emissions)

If your organisation can’t draw this in one page, with clear ownership and KPIs at each step, improvement efforts tend to fragment quickly.

Where performance leaks: common pain points in agriculture supply chains

You don’t need a massive transformation program to get value. But you do need to be honest about where the chain is leaking performance.

Here are patterns we see repeatedly across Australian agriculture and food supply chains:

1) Planning is disconnected from operational constraints

Plans get made without enough visibility of:

• harvest/receival capacity
• packhouse line rates and labour
• cold storage space
• carrier availability
• port cutoffs and container supply

The result is predictable: expediting, short shipping, overtime, demurrage, spoilage, and “heroics” to recover.

2) Inventory sits in the wrong place (or in the wrong form)

In agriculture, inventory isn’t just “how much”. It’s:

• where it sits (regional vs metro, near port vs inland)
• what state it’s in (bulk vs packed, chilled vs frozen, QA released vs held)
• how quickly it can be redirected (domestic vs export, customer-specific specs)

When inventory positioning is wrong, costs rise and service suffers—even if total stock looks reasonable.

3) Transport is managed as a series of bookings, not a system

Many agribusinesses still manage freight lane-by-lane, supplier-by-supplier, week-by-week.
That’s understandable—things move fast.

But without a system view you lose opportunities like:

• backhaul and triangulation
• standardised carrier performance management
• route optimisation and load consolidation
• contract discipline (accessorials, waiting time, credits)

4) Data exists—but isn’t decision-ready

Agriculture supply chains often have a mix of:

• legacy ERPs
• spreadsheets for harvest and intake
• standalone QA systems
• transport carrier portals
• DC/WMS data
• export documentation systems

If teams don’t trust the numbers, they default to judgement calls. That can work—until the chain is under stress.

5) Risk is tracked, but not quantified

Most organisations can list risks. Fewer can answer:

• Which risks matter most to service and margin?
• Where are the hidden single points of failure (tier-2 or tier-3)?
• What’s our realistic time-to-recover if X happens?

Without quantified scenarios, resilience discussions stay theoretical.

The improvement levers that matter most

Below are practical levers that consistently move the dial in Australian agriculture supply chains. They’re not “one size fits all”—but they are a solid menu to work from.

Lever 1: Network design that matches how your product behaves

In agriculture, network design isn’t just “number of sites”. It’s the physics of:

• time and temperature
• harvest peaks
• variability in yield and grade
• export vs domestic flows
• labour availability by region
• freight mode options (and constraints)

Network design questions worth answering properly include:

• Where should we hold inventory vs flow-through?
• Which products should be cross-docked, and which need buffer stock?
• What’s the best mix of regional aggregation and metro distribution?
• Should packing/processing be centralised, regional, or hybrid?
• What happens to cost and service under “bad season” scenarios?

This is exactly the kind of work supported by Trace’s Strategy & Network Design capability.

Lever 2: Planning that respects seasonality and constraints

Good planning in agriculture is less about having a perfect forecast and more about:

• clear assumptions
• rapid re-planning when reality changes
• shared decisions across operations, commercial and finance
• explicit trade-offs (service, waste, cost, working capital)

For larger agribusinesses and processors, structured S&OP / IBP-style rhythms can work extremely well—as long as they’re adapted to seasonal dynamics and operational constraints.

Key practices that help:

• scenario planning for weather and yield variability
• harvesting and intake plans connected to pack/processing capacity
• allocations and customer prioritisation rules agreed in advance
• clear policies for substitutions, partials, and spec changes
• exception-based workflows (so planners focus on what matters)

Trace supports these kinds of uplifts through Planning & Operations, often in tandem with technology enablement via Technology.

Lever 3: Cold chain and quality as an operational system (not just compliance)

Cold chain failures rarely come from one dramatic event. They usually come from small, repeated breakdowns:

• long dwell times at dispatch
• poor temperature monitoring handoffs
• inconsistent pre-cooling
• mismatched packaging and pallet configuration
• unclear ownership of non-conformance resolution

If your teams are dealing with frequent claims, spoilage, or quality holds, the answer is rarely “try harder”. It’s usually:

• better process design
• clearer controls
• better visibility and exception management
• clearer supplier and carrier performance measures

This connects strongly to Trace’s Warehousing & Distribution work (particularly where DCs, cold rooms, cross-docks, or yard flow are involved).

Lever 4: Transport strategy that treats freight as a profit lever

Transport is often one of the largest controllable costs in agriculture—especially in a high-distance market like Australia.

But “cutting freight cost” is a trap if it’s done in isolation. The real target is:

• lower cost-to-serve
• without creating service failures, quality issues, or capacity shortages at peak

Practical improvement areas include:

• carrier strategy and contracting aligned to seasonal peaks
• lane and rate benchmarking (including accessorial discipline)
• backhaul programs and collaborative freight models
• dynamic routing and load building (where relevant)
• performance scorecards and dispute processes that actually close the loop

If transport is a major pain point, you may also want to read:

• Improving Operating Costs in Australian Agriculture Through Enhanced Transport Management

Lever 5: Procurement that reduces risk (not just price)

Agriculture supply chains depend heavily on:

• packaging (cartons, pallets, labels)
• third-party cold storage
• transport providers
• maintenance contractors
• seasonal labour providers
• input suppliers

If procurement is managed as “buying”, you’ll miss risk signals. If it’s managed as a commercial and supplier-performance system, you can reduce disruption and improve outcomes.

High-value procurement moves include:

• category strategies that reflect seasonality and criticality
• supplier performance management (OTIF, quality, claims, responsiveness)
• contract structures that align incentives at peak
• modern slavery and sustainability risk management
• supplier concentration analysis and contingency options

Trace’s Procurement team can help structure these programs and embed supplier governance that sticks.

Lever 6: Visibility that turns data into action (without boiling the ocean)

You don’t need a “big bang” platform rollout to improve visibility. But you do need:

• clear definitions (what does “on time” mean? what is a “complete” order?)
• clean master data where it matters
• dashboards aligned to decisions, not vanity metrics
• operational rhythms that use the insights (daily, weekly, monthly)

For agriculture supply chains, visibility priorities often include:

• inbound and intake status
• cold chain temperature compliance
• order fill and DIFOT/OTIF performance
• inventory status by grade/spec/hold state
• carrier performance and dwell time
• export readiness (documentation, container status, cutoff risk)

Trace supports this via Technology and the modular Trace .Solutions Suite, including tools focused on performance and risk visibility.

Lever 7: Resilience designed into the chain (N-tier, scenarios, recovery plans)

Resilience work becomes valuable when it answers practical questions:

• Where are our tier-2 and tier-3 dependencies?
• What happens if a key input is constrained (packaging, fertiliser, spares)?
• What happens if a port lane closes or shipping schedules shift?
• What’s our recovery plan—and how quickly can we execute it?

For agriculture, this is particularly relevant because disruptions often cascade:
a weather event affects harvest timing → peak volumes compress → storage fills → carriers tighten → export cutoffs are missed → quality suffers → claims rise → working capital locks up.

Trace supports resilience programs through:

• Resilience & Risk Management
• and practical approaches like N-tier mapping (see: Agriculture Supply Chain Resilience and Risks – How N-tier Analysis Can Help)

Lever 8: Sustainability that is measurable and operational

Sustainability in agriculture can become vague quickly unless it’s tied to operations.

Practical supply-chain-led sustainability usually focuses on:

• transport emissions (route efficiency, mode shifts, utilisation)
• energy use in cold storage and processing
• packaging optimisation and recyclability
• waste reduction (spoilage, rejects, rework)
• supplier standards and traceability

Trace works with organisations to embed sustainability through Supply Chain Sustainability, often integrated with network and planning decisions rather than treated as a standalone initiative.

The metrics that actually matter (and how to avoid the usual traps)

Agriculture supply chains drown in metrics. The goal is a small set that:

1. are trusted,
2. are linked to decisions, and
3. show trade-offs clearly.

A practical scorecard usually includes:

• Service: DIFOT/OTIF, order completeness, export cutoff hit-rate
• Quality: claims rate, spoilage/waste, temperature excursion incidents
• Cost: freight cost-to-serve, handling cost per unit, premium freight events
• Working capital: days inventory (by category), stock on hold, write-offs
• Reliability: schedule adherence (processing/pack), carrier performance, dwell time
• Resilience: supplier concentration, time-to-recover for critical scenarios
• Sustainability: transport emissions intensity, waste, energy intensity (where available)

If you want a deeper dive on service measurement, Trace has a range of related content on the Insights hub: Trace Insights

How Trace Consultants can help agribusinesses strengthen supply chain performance

Agriculture supply chains don’t need theory. They need improvements that work under real-world variability.

Trace Consultants supports organisations across Australia with practical, data-led supply chain and procurement work—connecting strategy to execution, and helping teams make confident decisions when the trade-offs are real.

Here are common ways we help agriculture and food supply chain organisations:

1) End-to-end supply chain diagnostics (fast clarity, prioritised roadmap)

When leaders say, “We’re busy but not getting better,” a diagnostic creates alignment.
Typical outputs include:

• current-state mapping (flows, constraints, decision points)
• quantified cost and service baseline
• key bottlenecks and root causes
• prioritised improvement roadmap with effort/impact sizing

If you’re considering a diagnostic as a starting point, Trace’s broader service set is outlined here: Our Services

2) Network optimisation and footprint strategy

We build fact-based network models and scenarios, helping organisations choose options that hold up across:

• good seasons and bad seasons
• export disruptions
• capacity changes
• growth in new channels or markets

Start here: Strategy & Network Design

3) Planning uplift (S&OP / IBP, forecasting, inventory policies)

We help teams move from reactive firefighting to clear planning rhythms, with:

• role clarity and decision rights
• scenario planning
• inventory and allocation policies
• dashboards and exception workflows

Learn more: Planning & Operations

4) Warehousing, cold storage and distribution improvement

From regional storage strategy through to DC design, we support:

• layout, flow and dock/yard improvements
• operating model and labour planning
• WMS requirements and implementation support
• automation business cases (where it makes sense)

Explore: Warehousing & Distribution

5) Transport strategy and carrier performance improvement

We help organisations reduce transport cost and risk without breaking service, through:

• lane strategies and contracting
• benchmarking and invoice governance
• performance scorecards and supplier management
• routing and load optimisation approaches

Related reading: Transport management in Australian agriculture

6) Procurement and supplier governance

We strengthen procurement as a commercial and risk capability:

• strategic sourcing and category strategy
• supplier performance management (DIFOT/quality/claims)
• supplier risk and concentration reviews
• sustainability and compliance alignment

Explore: Procurement

7) Resilience and risk management (including N-tier analysis)

We support practical resilience programs that go beyond risk registers:

• N-tier mapping and dependency analysis
• scenario modelling and response playbooks
• resilience governance and monitoring

Explore: Resilience & Risk Management

8) Technology enablement (visibility, dashboards, planning tools)

We help organisations select, design and embed technology so it changes decisions and behaviours—not just reporting.

Explore: Technology
And: Trace .Solutions Suite

Where to start: a practical 90-day action plan

If you’re not sure where to begin, here’s a sensible sequence that works in many agribusiness settings.

Weeks 1–3: Build the fact base

• map end-to-end flows and constraints
• confirm service promise (domestic and export)
• baseline costs, waste, claims, inventory, transport performance
• define what “good” looks like for the next season

Weeks 4–8: Prioritise the big levers

• identify the few constraints that drive most issues (capacity, cold chain, transport, planning, data)
• quantify options (what happens if we shift inventory, add cross-dock, change carrier mix?)
• select initiatives with clear owners and measurable outcomes

Weeks 9–12: Start implementation where value is immediate

• lock in planning rhythms and decision rules for peak periods
• implement transport governance and performance scorecards
• tackle one or two operational bottlenecks (dock flow, staging discipline, temperature monitoring handoffs)
• align procurement and supplier management to critical lanes and inputs

If you’d like Trace to help you shape and deliver this kind of roadmap, start here: Speak to Trace

FAQs: Australia’s agriculture supply chain

What’s the biggest constraint in agriculture supply chains?

It depends on the category, but the most common constraints are capacity at peak (harvest/pack/processing), transport availability, and cold chain integrity for perishable products. The best improvements usually start by identifying the true constraint rather than attacking symptoms.

How do we reduce transport cost without hurting service?

By shifting the focus from “cheaper rates” to total cost-to-serve: better loading discipline, fewer premium moves, improved carrier performance, backhauls, and clearer rules for when to expedite. A system view beats lane-by-lane negotiations.

Do we need new technology to improve our supply chain?

Not always. Many improvements come from better decisions, clearer process, and cleaner data definitions. That said, targeted visibility and planning tools can deliver outsized value—especially when they support daily and weekly decision-making.

How do we manage export volatility and shipping disruptions?

The practical answer is scenario planning + inventory and allocation rules + clear export readiness controls (documentation, quality status, container/cutoff risk). Resilience work should be anchored in time-to-recover and customer impact—not just “lists of risks”.

What does “N-tier risk” mean in agriculture?

It means looking beyond direct suppliers to understand dependencies further down the chain—like packaging sub-suppliers, fertiliser inputs, spare parts, or subcontractor labour. In agriculture, these hidden dependencies can become supply chain “single points of failure”.

How long does a network optimisation project take?

It depends on scope and data readiness, but many network strategy programs can produce a clear recommendation set in weeks, then move into staged implementation. The key is aligning modelling to decisions the business is actually ready to make.

Closing thought

Australia’s agriculture supply chain is one of the most operationally demanding systems in the economy. It has to work across huge distances, short windows, tight quality constraints, and global market volatility—and it has to do it efficiently.

The good news is: most supply chains don’t need a reinvention. They need a small number of high-leverage decisions made well, backed by a fact base, and implemented with discipline.

If your chain feels like it’s relying on heroics to get through each peak—Trace can help you move it toward something calmer, more predictable, and more profitable.

Start the conversation here: Contact Trace Consultants

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Why your next warehouse decision is really a supply chain strategy decision

There’s a moment most operations leaders recognise instantly.

You’re standing in a DC aisle that feels narrower than it used to. Pallets are parked where “temporary overflow” somehow became permanent. The pick path snakes around new racking you never planned for. Someone mentions safety stock “until things settle” — and you both know things rarely settle. Meanwhile, the lease expiry date sits on the risk register like a silent countdown.

And then the real question lands:

Do we need a new facility… or do we need a better network?

In Australia, industrial property decisions are some of the most expensive and long-lasting bets a leadership team makes. Rent, labour access, transport connectivity, automation fit, expansion potential, planning approvals — it’s a lot. But the most common mistake is treating property as a standalone workstream.

Because if you choose the building first, you often end up forcing the supply chain to “make it work”.

A better approach flips the order:

Network strategy first. Real estate second. Facility design third.

That sequence is what separates a site that merely holds stock from a facility that creates advantage.

This article is a practical guide to linking network strategy and industrial real estate — written for Australian organisations juggling growth, cost pressure, service expectations, and risk. It also outlines how Trace Consultants supports leaders to make confident, independent, solution-agnostic property decisions that hold up operationally and commercially.

If you want the broader context on network strategy, you can also read:

• Network strategy fundamentals: https://www.traceconsultants.com.au/strategy-and-network-design
• Related insight: https://www.traceconsultants.com.au/thinking/network-strategy----how-to-optimise-your-physical-footprint-across-manufacturing-warehousing-distribution-au-nz

Why network strategy and industrial real estate are inseparable

Industrial real estate isn’t just a line item. It shapes your supply chain physics:

• Distance drives freight cost and delivery promise (especially metro vs regional).
• Building design drives productivity, safety, and automation viability.
• Site access drives carrier performance, congestion, and cut-off discipline.
• Labour availability determines whether your operation runs smoothly or permanently operates “short-staffed.”
• Expansion options determine whether the business can grow without creating a second “temporary” facility that becomes forever.

So when an organisation asks, “Where should our next DC go?”, the real question is:

What network will deliver the service we’re selling, at the cost we can afford, with the resilience we need?

Once you answer that, property becomes a logical step — not a gamble.

The Australian reality: why this is harder here than most markets

Australia’s industrial property and logistics environment has a few features that amplify the stakes:

1. Geography is unforgiving
   Long linehaul distances mean you can’t hide a suboptimal footprint behind “a bit more transport”. It adds up fast — in cost, carbon, and service variability.
2. Port and freight dependencies are real
   Shifts in import mix, container flows, and carrier capacity show up in your yard plan and your inbound rhythms.
3. Labour markets differ sharply by corridor
   Two sites that look similar on a map can behave completely differently in labour availability, turnover, and wage pressure.
4. Planning approvals and site constraints bite late
   Many projects fail quietly when planning, access, B-double movements, curfews, power supply, or flooding overlays turn into redesigns and delays.
5. E-commerce and service expectations keep tightening
   Faster delivery and higher order fragmentation put pressure on node strategy and automation readiness.

This is exactly why “property-led” decisions often disappoint. Australia punishes shortcuts.

The trap: “Let’s lock in a site, then we’ll design the operation”

This is the most expensive sequence we see:

1. Real estate starts scouting options (because the lease clock is ticking)
2. A shortlist forms based on availability and rent
3. The operation is asked to “fit into” one of the options
4. Network modelling happens late — mainly to justify the choice
5. The business signs… and then spends years paying for the mismatch

The symptoms show up quickly:

• You carry too much inventory because the node isn’t where demand is
• Transport lanes are longer and more expensive than planned
• Dock congestion becomes the new normal
• Automation becomes harder (or uneconomic) because the building isn’t suited
• Mezzanines, racking and workarounds multiply — and so do touches
• Service becomes dependent on heroics

A building can look right and still be wrong if it’s not anchored in network strategy.

A practical roadmap: linking strategy to property (without turning it into a science project)

Here’s the sequence that holds up in boardrooms and on warehouse floors.

Step 1: Confirm the service promise (what are we actually trying to deliver?)

Before anyone measures a warehouse, define the rules of the game:

• Delivery lead times by customer segment (metro vs regional)
• Cut-offs, DIFOT/OTIF targets, and dispatch expectations
• Channel mix (retail, wholesale, e-com, trade, project deliveries)
• Growth assumptions and volatility range (base + high growth + downside)
• Risk posture (single node vs multi-node resilience)
• Sustainability requirements (emissions, energy, reporting expectations)

This step sounds basic, but it prevents you designing a premium network for a standard service offer — or underbuilding a network that can’t deliver the sales strategy.

Step 2: Build the network scenarios (the “where and why”)

Network strategy should answer:

• How many nodes do we need (and what does each do)?
• Where should inventory sit (and what should flow direct)?
• Which lanes matter most for service and cost?
• What changes under different demand, fuel, labour, or disruption scenarios?

This is the home of scenario modelling — and it’s core to Trace’s Strategy & Network Design work:
https://www.traceconsultants.com.au/strategy-and-network-design

Step 3: Translate network outcomes into facility requirements (the “what it must do”)

Now we turn scenarios into a clear, measurable requirement:

• Storage profile (pallets, cartons, each pick, bulk vs forward pick)
• Throughput and dock door needs (inbound/outbound peaks)
• Temperature zones (ambient, chilled, frozen)
• Dangerous goods and compliance measures (where applicable)
• Value-add services (kitting, labelling, light assembly, returns)
• Automation/MHE assumptions (current and future)
• Site access and traffic flows (B-doubles, MR trucks, vans, containers)
• Amenities and workforce facilities (because productivity is human)

This requirement definition becomes your anchor. It prevents “nice building, wrong building”.

Step 4: Location and site assessment (the “where it can work”)

Now you can evaluate locations with a supply chain lens, not just a property lens:

• Transport connectivity and congestion
• Labour depth and competition in the corridor
• Planning controls and expansion constraints
• Power availability (critical for automation and electrification)
• Flood/fire overlays and insurance implications
• Access design (turning circles, queuing, separation of people and vehicles)

Step 5: Concept design and operational layout (the “how it will run”)

This step matters because two buildings of the same size can perform very differently.

You want:

• Clean, safe people/vehicle separation
• Dock design that prevents yard chaos
• Travel paths that reduce touches
• Pick module design that supports accuracy and speed
• Mezzanine placement that doesn’t create bottlenecks
• Automation zones that can scale without rework

Trace supports this through Warehousing & Distribution services:
https://www.traceconsultants.com.au/warehousing-and-distribution

Step 6: Tech, MHE, and automation strategy (solution-agnostic, commercially grounded)

Automation shouldn’t be “because it’s modern”. It should be because it fits:

• Order profile and variability
• Labour availability and wage pressure
• Space constraints and building geometry
• Required service level and cut-off discipline
• Maintenance capability and uptime tolerance

Where technology is part of the solution, Trace remains independent and vendor-neutral — focused on fit-for-purpose outcomes:
https://www.traceconsultants.com.au/technology
https://www.traceconsultants.com.au/solutions

Step 7: Go-to-market, procurement, and transition planning (making it real)

Once the strategy and requirements are clear, you can run a clean process:

• Property sourcing and commercial evaluation (lease vs build vs 3PL)
• Fitout scope definition and tendering support
• MHE and systems procurement support
• Transition planning, cutover, and stabilisation
• Change management and operational readiness

(If procurement support is required across property-adjacent categories or vendor selection, see: https://www.traceconsultants.com.au/procurement)

Lease, build, or 3PL? The decision is rarely just financial

A common misconception is that “lease vs build vs outsource” is primarily about cost. In practice it’s about control, flexibility, service risk, and scalability.

Leasing (common when speed matters)

Leasing can work well when you need speed and flexibility, but the risk is signing into a footprint that doesn’t match the future network. Watch for:

• expansion constraints
• power limitations (automation readiness)
• access limitations (yard and congestion realities)
• fitout restrictions and landlord constraints

Building (when the operation is strategic and stable)

Building gives control — but only if you’ve done the network work first. The risk is overbuilding based on optimistic growth assumptions or designing a “perfect facility” for a service model that shifts.

3PL / outsourced warehousing (when capability and flexibility outweigh ownership)

Outsourcing can be the right move, especially when demand is volatile, multi-client scale helps, or your business wants to stay asset-light. But it comes with performance management complexity and contract design risk.

The best programs treat 3PL as a network option to model — not a default.

Designing facilities for what actually happens (not what looks good on paper)

Industrial property projects often fail in the small details that only show up on day one:

• inbound arrives in peaks (not a neat curve)
• outbound cut-offs create a cliff
• returns and exceptions are messier than planned
• forklifts don’t travel in straight lines
• people need safe, practical walkways
• congestion costs more than rent savings

That’s why operational layout design is not “nice to have”. It’s the difference between:

• a site that looks efficient, and
• a site that stays efficient under pressure.

Sustainability and resilience: industrial property is now part of your ESG story

More boards are asking: What is the emissions impact of our footprint? And property decisions are central to that answer.

Network and site decisions can reduce emissions by:

• shortening average delivery distance
• enabling better load consolidation
• supporting electrification readiness (power capacity and charging)
• enabling solar and energy management options
• reducing rework, waste, and double-handling

Resilience also shows up in property decisions:

• dual-node strategies where single points of failure are unacceptable
• flood and fire exposure mitigation
• inbound route optionality
• supplier and carrier access redundancy

If you’re building for the next decade, these are not edge cases — they’re design inputs.

A short case example

In one Australian FMCG engagement, a network optimisation program identified that a central facility location was driving disproportionate regional transport cost and service pain. By relocating one key warehouse to a more advantageous position and reallocating inventory based on demand behaviour, the organisation achieved:

• ~15% reduction in transport costs, and
• ~20% reduction in regional customer lead times

The key point isn’t the percentages — it’s the mechanism:

the property move only worked because it was driven by network logic and inventory flow design, not property availability.

If you want more on network optimisation mechanics, see:
https://www.traceconsultants.com.au/thinking/how-network-optimisation-can-drive-cost-reduction
and
https://www.traceconsultants.com.au/thinking/network-optimisation-and-strategic-warehouse-reviews

How Trace Consultants can help (independent, client-first, solution-agnostic)

Trace Consultants supports Australian organisations to connect network strategy with industrial real estate decisions — without pushing a preferred vendor, platform, developer, broker, or automation solution.

Our work is designed to help you make decisions you can defend operationally, financially, and strategically.

Our support typically includes:

1) End-to-end supply chain and network diagnostic
We establish a clear fact base on current performance, constraints, service outcomes, cost-to-serve drivers, and growth requirements — so the property conversation starts with evidence, not assumptions.

2) Facility requirements and functional design inputs
We define sizing, operating model requirements, storage and throughput needs, dock and yard requirements, and any special constraints (e.g., temperature zones, compliance standards, dangerous goods controls where relevant).

3) Location strategy and site selection support
We assess location options against your network scenarios, transport connectivity, labour dynamics, risk overlays, compliance constraints, and growth needs — so the “best site” is best for your operation, not just best on a rent rate.

4) Property option evaluation (lease vs build vs 3PL)
We support commercial evaluation with a supply chain lens, including scenario impacts, transition complexity, and service risk — ensuring decisions aren’t made purely on a static spreadsheet.

5) Operational layout and facility concept design support
We design the operational blueprint: material flows, traffic flows, MHE zones, pick/pack design, safety pathways, value-add areas, and scalability considerations to minimise footprint and improve productivity.

6) Technology, MHE, and automation strategy (vendor-neutral)
We translate operational needs into technology requirements and help you evaluate options without bias — including WMS/WES considerations, automation fit, and phased implementation pathways.

7) Transition planning and implementation support
We help plan the move from current state to future state — cutover, training, readiness, stabilisation, and KPI control — so you protect service while the change happens.

Relevant service pages:

• Strategy & Network Design: https://www.traceconsultants.com.au/strategy-and-network-design
• Warehousing & Distribution: https://www.traceconsultants.com.au/warehousing-and-distribution
• Technology: https://www.traceconsultants.com.au/technology
• Why Trace (our independence and approach): https://www.traceconsultants.com.au/about/why-us

Quick checklist: questions to answer before you sign (or renew) a lease

If you’re approaching a lease event, expansion, or relocation decision, these are the questions that prevent expensive regret:

1. What service promise are we designing for (by segment/channel)?
2. What network scenarios have we tested — and what breaks under volatility?
3. What is our true cost-to-serve by customer/channel/SKU group?
4. What inventory policy changes could reduce required space?
5. What throughput peaks must the facility handle (not average volumes)?
6. What labour profile will the corridor support (now and in 3–5 years)?
7. What automation assumptions are realistic for our order profile?
8. What constraints exist on site access, queuing, and yard capacity?
9. What expansion options exist (land, approvals, power)?
10. What transition risk can we tolerate — and how will we protect service?

If you can answer those confidently, your property decision becomes far less stressful.

FAQs (for leaders searching “network strategy and industrial real estate”)

What is network strategy in supply chain terms?

Network strategy is the intentional design of your physical footprint — warehouses, DCs, plants, suppliers, and transport flows — to balance cost, service, risk, and sustainability under real-world constraints.

How does industrial real estate affect cost-to-serve?

Industrial real estate determines where inventory sits and how far orders travel. That directly impacts freight cost, lead times, variability, and the operational effort required to fulfil orders — which all flow into cost-to-serve.

When should we run a network strategy review?

Common triggers include lease expiry, major growth, channel change (e-commerce uplift), M&A, persistent capacity constraints, rising freight/rent, service deterioration, or major supplier/customer geography shifts.

Should we select a site first or design the network first?

Design the network first. Site selection should be the output of network scenarios and facility requirements — not the starting point.

Can Trace help even if we already have a preferred corridor or shortlist?

Yes. In fact, validating (or stress-testing) a shortlist against network scenarios is often where the biggest hidden risks are found — before they become expensive commitments.

Ready to make your next facility decision with confidence?

If you’re facing a lease event, capacity crunch, expansion, or a “we need a new DC” conversation, Trace can help you link network strategy to industrial real estate — independently and pragmatically.

Start here: https://www.traceconsultants.com.au/contact
Or explore more insights: https://www.traceconsultants.com.au/insights

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Cost to Serve Optimisation: The fastest way to improve margins without playing whack-a-mole in operations

If you’ve ever sat in a meeting where someone says, “Our logistics cost is only X% of sales,” and everyone nods like that’s the end of the conversation — you already know why cost to serve matters.

Averages are comforting. They’re also dangerous.

Because the truth is rarely “our supply chain is expensive” or “our supply chain is efficient”. The truth is usually messier:

• Some customers are highly profitable and simple to serve.
• Some customers look great on revenue but quietly drain margin through small orders, tight windows, special handling, urgent freight, and returns.
• Some products behave beautifully in a DC and travel well.
• Others create endless touches, damages, temperature constraints, or compliance effort.

Cost to serve optimisation is the discipline of making that mess visible — and then fixing it in a way that improves margin while keeping service reliable.

Not by cutting corners. Not by demanding miracles from warehouse teams. But by aligning service promise, operating model, and commercial settings so the business stops paying premium cost for standard revenue.

This article covers:

• What cost to serve is (and what it isn’t)
• How to calculate cost to serve without drowning in data
• How to segment customers, channels and SKUs for fair comparisons
• The most common “profit leaks” hiding in fulfilment
• Practical levers to reduce cost while protecting service
• How Trace Consultants can help you build a cost-to-serve model and turn it into real operational and commercial change

What is cost to serve?

Cost to serve is the true end-to-end cost of fulfilling an order (or serving a customer/channel), including the activities that most organisations underestimate or ignore.

In plain English: it’s what it really costs to deliver the service you’re promising.

A strong cost-to-serve model typically captures costs across:

• Planning and customer service effort (order processing, exceptions, expediting)
• Inbound logistics (freight in, receiving effort, supplier non-conformance handling)
• Warehousing (putaway, storage, replenishment, picking, packing, value-add, rework)
• Outbound transport (linehaul, last mile, couriers, accessorials, detention, failed deliveries)
• Inventory (working capital, holding cost, obsolescence, shrinkage)
• Returns and claims (reverse logistics, assessment, restock, write-offs, credits)
• Enablers (systems, facilities, labour overheads where appropriate)

The goal isn’t to build an accounting masterpiece. The goal is to answer practical questions like:

• Which customers and channels make money after fulfilment cost?
• Which products are operationally expensive, and why?
• What service settings drive the most avoidable cost?
• Where should we change service policy, pricing, minimum order quantities, freight rules, or network design?

Why cost to serve is suddenly on everyone’s agenda

Many Australian organisations are feeling the same squeeze from different angles:

• Input costs have risen (labour, transport, energy, compliance)
• Customers expect faster delivery, more tracking, and fewer errors
• Omnichannel adds complexity (small orders, returns, split shipments)
• Network footprints have grown, and “temporary” fixes have become permanent
• CFOs want margin improvement, but the obvious cost-cutting has already been done

In this environment, cost-to-serve optimisation becomes a smarter move than blunt budget cuts because it:

• targets the real drivers of cost (not just the visible ones)
• protects service by redesigning the system rather than starving it
• creates commercial fairness (you can price and serve in a way that matches cost)
• reduces operational chaos by removing the causes of exceptions

The big trap: confusing “cost reduction” with “cost to serve optimisation”

Traditional cost reduction often looks like:

• cut headcount
• cut carriers
• push warehouse productivity harder
• reduce inventory (without changing the policy that created it)
• delay investment

Sometimes those actions help. Often they backfire, because they don’t change the underlying demand on the supply chain.

Cost to serve optimisation is different. It focuses on:

• removing unnecessary touches and exceptions
• aligning service promise to what customers value (and what they pay for)
• improving flow and predictability
• redesigning commercial rules that create expensive behaviour

The result is usually a calmer operation — because the business stops asking the supply chain to perform contradictory tasks at the same time.

How to calculate cost to serve without overcomplicating it

A common misconception is that cost-to-serve modelling requires perfect data and months of effort. In reality, the most useful models are often built using “good enough” data, clear assumptions, and a disciplined approach.

Step 1: Choose the unit of analysis (keep it practical)

Most organisations start with one of these:

• Cost per order
• Cost per line
• Cost per unit
• Cost per customer (monthly or quarterly view)
• Cost per channel (store replenishment vs e-commerce vs wholesale)
• Cost per lane/region (metro vs regional vs remote)

Pick the unit that matches the decisions you need to make.

If you’re trying to redesign freight rules and service settings, start with customer/channel cost per order and cost per delivery.
If you’re trying to fix warehouse efficiency, cost per line and touches per unit are powerful.
If you’re trying to reset inventory policy, focus on carrying cost and service level trade-offs.

Step 2: Define the activity drivers (this is where value hides)

Cost to serve works because it links cost to the activities that cause it.

Typical drivers include:

• number of orders
• number of order lines
• units picked (each, carton, pallet)
• picks by method (each-pick vs case-pick vs pallet)
• deliveries and drops
• kilometres by region
• returns volume and return reasons
• exceptions (urgent orders, short shipments, re-deliveries)
• value-add tasks (kitting, labelling, quality checks)

You don’t need hundreds of drivers. You need the handful that explains most of the workload.

Step 3: Allocate cost logically (not perfectly)

A practical cost-to-serve model often uses a hybrid approach:

• Direct attribution where possible (e.g., transport costs by lane, courier by consignment)
• Activity-based allocation for warehouse labour and handling
• Reasonable allocation for overheads that truly scale with activity (and avoid allocating what doesn’t)

The aim is a model the business trusts and can repeat — not a once-off forensic exercise.

Step 4: Segment properly (or you’ll draw the wrong conclusion)

Segmentation is the difference between “interesting” and “useful”.

Segment by what actually drives cost:

• Channel (store replenishment, e-commerce, wholesale, projects)
• Geography (metro, regional, remote)
• Order profile (small/large, high/low line counts, urgent/non-urgent)
• Customer type (strategic accounts, independents, direct consumers, government, hospitality)
• Product profile (fragile, temperature-controlled, bulky, hazardous, slow movers)

If you don’t segment, the average will hide both the best and worst parts of your business.

Step 5: Validate with the people doing the work

This is non-negotiable if you want buy-in.

A good validation process asks:

• Does the model reflect how orders actually flow?
• Are there hidden touches and rework not captured in systems?
• Are we counting the right exceptions?
• Do the results “feel” directionally true when we walk the floor?

Cost-to-serve numbers become powerful only when operators say, “Yes, that’s exactly what makes this customer/channel painful.”

What cost-to-serve analysis usually reveals (the common profit leaks)

Once you model cost to serve properly, patterns tend to emerge quickly. These are the most common ones we see.

1) Small orders are rarely “small”

Small orders often carry a premium cost because they create:

• more picks per unit shipped
• more packaging effort
• higher freight cost per unit
• higher customer service and exception handling
• more split shipments (especially in omnichannel)

If your service policy encourages customers to place frequent, low-value orders, you’re effectively subsidising a behaviour that inflates cost.

2) Tight delivery windows are expensive — even when you “make them work”

Tight windows increase:

• transport complexity
• failed delivery risk
• warehouse cut-off pressure and expediting
• congestion at docks
• detention and waiting time

You might still hit DIFOT — but you’ll pay for it in overtime, expedited freight, and operational stress.

3) Returns quietly double your handling cost

Returns are easy to underestimate because the costs are spread out:

• transport back
• receiving and triage
• restocking or disposal
• credits and customer service time
• write-offs and damage

If returns are high in a channel, cost-to-serve analysis helps separate:

• unavoidable returns (category behaviour)
• preventable returns (quality, picking accuracy, product information, packaging)
• avoidable returns created by policy (too-lenient rules, no controls, no feedback loop)

4) Exceptions are a tax on your entire operation

The most expensive supply chains are not the ones with high volume. They’re the ones with high exceptions:

• urgent orders
• partial shipments
• inventory inaccuracies
• supplier non-conformance
• last-minute changes and cancellations
• “special” customer requests that become the norm

A cost-to-serve model makes exception costs visible and quantifies the value of reducing them.

5) Some customers are “high service, low value” — and nobody wants to say it out loud

This is where cost-to-serve becomes politically sensitive, but commercially essential.

You’ll often find customers who:

• order frequently in small quantities
• request special handling
• have high return rates
• demand tight windows
• generate high customer service workload
• negotiate hard on price but still cost a fortune to serve

Cost-to-serve analysis doesn’t exist to punish these customers. It exists to create options:

• redesign service terms
• price appropriately
• set minimum order quantities or order frequency rules
• consolidate deliveries
• move them to a more suitable fulfilment model

The levers that actually reduce cost to serve (without wrecking service)

The best cost-to-serve programs blend commercial, operational, and supply chain design levers. If you only pull one category, the gains won’t stick.

Lever 1: Service segmentation (stop treating everyone the same)

One of the most effective moves is simply defining:

• what “standard service” is
• what “premium service” is
• who qualifies for premium service and why

Examples of segmentation decisions:

• Delivery frequency (daily vs twice weekly vs weekly)
• Delivery window tightness (standard window vs timed delivery)
• Cut-off times (same-day vs next-day)
• Minimum order value or minimum dropsize
• Returns policy by channel or product
• Packaging standards and handling rules

This is not about reducing service across the board. It’s about matching service to value.

Lever 2: Order policy design (the rules that shape behaviour)

Order rules are powerful because they influence demand on your supply chain.

Common policy levers:

• minimum order quantities (MOQ) and minimum order values
• free freight thresholds and freight charge structures
• order cut-offs aligned to actual warehouse capability
• incentives for consolidated ordering (rather than frequent small orders)
• limits on last-minute changes and cancellations

Well-designed rules reduce operational chaos and improve planning stability.

Lever 3: Warehouse flow and touches reduction

Warehousing cost-to-serve often improves fastest by reducing touches:

• slotting and pick-path optimisation
• pick-face design aligned to velocity and order profile
• replenishment discipline to reduce “empty locations” and urgent top-ups
• packing standardisation to reduce rework and damage
• receiving flow improvements to reduce dock-to-stock time
• reduction of congestion and travel time

A cost-to-serve lens helps target the exact processes driving cost for high-cost segments.

Lever 4: Transport segmentation and last-mile redesign

Transport is where cost-to-serve differences become stark, especially across Australian geography.

Common levers include:

• lane segmentation (metro, regional, remote) with different service models
• route optimisation and better load building
• delivery frequency redesign (fewer drops, higher utilisation)
• carrier mix optimisation (right carrier for the right job)
• better control of accessorials (waiting time, re-delivery, tail-lift, special handling)
• delivery window rationalisation

Often, “improving transport” is less about rates and more about reducing complexity that carriers price into the job.

Lever 5: Inventory placement and working capital decisions

Inventory isn’t just a finance number. It’s a service enabler and a cost driver.

Cost-to-serve insights help answer:

• Where should stock sit to reduce transport and improve service?
• Which SKUs should be held centrally vs closer to customers?
• What service level targets are economically sensible by segment?
• Which long-tail SKUs should move to alternate fulfilment models?

The goal is to protect service where it matters and stop over-investing where it doesn’t.

Lever 6: Returns and quality loops

Returns cost-to-serve reduces when you close the feedback loop:

• improve picking accuracy and packaging
• fix product quality issues and supplier non-conformance
• improve product information (especially for online channels)
• redesign returns rules where appropriate
• triage returns faster to reduce handling and write-offs

Returns are often a symptom of upstream issues that can be fixed.

Lever 7: Commercial alignment (stop rewarding expensive behaviour)

This is where cost-to-serve becomes a margin engine.

Once you can quantify cost differences, you can:

• redesign pricing and rebates
• introduce service-based pricing tiers
• adjust contract terms and service agreements
• set fair surcharges for premium service elements
• renegotiate customer terms with evidence, not emotion

Customers don’t expect you to subsidise inefficiency forever. They do expect transparency and consistency.

How to run a cost-to-serve optimisation program that doesn’t stall

Cost-to-serve initiatives often fail for one of two reasons:

1. The model is too complex and nobody trusts it
2. The organisation sees the insights but can’t agree on what to change

Here’s a practical approach that avoids both.

Phase 1: Establish the baseline and identify the hotspots

• Agree the decisions the business wants to make
• Build a “good enough” cost-to-serve model with clear assumptions
• Segment by channel, customer type and geography
• Identify the top 10 cost hotspots (customers, lanes, products, order profiles)
• Validate the story with operational walk-throughs

Phase 2: Design the levers (commercial and operational)

• Define service tiers and policy options
• Model the impact of policy changes on cost and service
• Identify operational improvement initiatives (warehouse, transport, inventory)
• Design governance: who owns the decisions, who communicates changes, how exceptions are managed

Phase 3: Implement, measure, and keep it from slipping back

• Run pilots in selected segments where possible
• Measure changes in cost, service, and workload
• Build routines to review the right KPIs weekly and monthly
• Embed policy changes into systems and processes (not just emails)
• Train customer-facing teams to hold the line consistently

This is the difference between a clever analysis and a lasting improvement.

The human side: why cost-to-serve is often a change management challenge

Cost-to-serve optimisation touches multiple teams:

• Sales wants growth and responsiveness
• Operations wants stability and flow
• Finance wants margin and control
• Customer teams want happy customers
• Procurement wants competitive rates

If you treat cost-to-serve as an operations project, it will stall.
If you treat it as a finance project, it will create resentment.
If you treat it as a commercial project, it might ignore operational reality.

It needs to be a cross-functional program with:

• shared definitions
• clear decision rights
• a consistent story to customers
• leadership backing to sustain policy changes

How Trace Consultants can help

Cost-to-serve optimisation is one of the most practical ways to lift margins because it connects commercial reality to operational reality. Trace Consultants supports Australian organisations to build cost-to-serve models that the business trusts — and then convert them into action.

1) Cost-to-serve modelling and segmentation

We help you develop a clear, repeatable model that answers the questions leadership actually cares about:

• cost per order, per customer, per channel, per lane
• cost drivers by activity (picking, packing, transport, returns, exceptions)
• segment profitability insights that cut through averages
• practical assumptions and transparent methodology that teams can understand

2) Service policy and commercial design

We work with commercial and operational teams to redesign service in a way that protects key customers and removes unnecessary cost:

• service tier design (standard vs premium)
• delivery frequency and window redesign
• MOQ and freight policy design
• returns policy review and control loops
• pricing and surcharge structures aligned to service cost

3) Warehouse and transport improvement levers

Cost-to-serve outcomes depend on execution. We support:

• warehouse productivity uplift through touch reduction and flow improvements
• slotting, pick-face, replenishment discipline and rework reduction
• transport lane segmentation, route redesign, and utilisation improvements
• accessorial control and carrier performance governance
• operating rhythm design so improvements stick

4) Inventory and network implications

Where relevant, we connect cost-to-serve insights to bigger structural moves:

• inventory placement and service level optimisation
• network design considerations
• channel fulfilment model optimisation (especially for omnichannel and returns-heavy channels)

5) Implementation support and change management

The best model in the world is useless if the business can’t implement the changes. We help with:

• stakeholder alignment and decision-making cadence
• pilot design and rollout planning
• KPI frameworks and performance routines
• training and practical playbooks for customer-facing teams

The goal is straightforward: improve margin, protect service where it matters, and make the supply chain calmer and more predictable.

A practical 30–60–90 day plan

If you want to move quickly without creating a never-ending analytics exercise, this approach works well.

First 30 days: baseline and hotspots

• define the decisions and scope
• build the initial cost-to-serve model with clear assumptions
• segment by channel, geography and customer type
• identify the top cost drivers and hotspots
• validate findings on the floor and with customer teams

Next 60 days: design the levers

• design service tiers and policy options
• model impact and choose priority changes
• define operational improvement initiatives (warehouse and transport)
• align commercial settings (pricing, surcharges, terms)

By 90 days: implement and lock governance

• pilot policy changes in selected segments
• implement quick-win operational improvements
• embed new rules into processes and systems
• establish KPI cadence and accountability to sustain gains

Frequently asked questions

Is cost-to-serve just activity-based costing?

Activity-based costing is a common method used in cost-to-serve modelling, but cost-to-serve is broader. It’s about connecting fulfilment cost to commercial and operational decisions, then optimising service and execution together.

Do we need perfect data to start?

No. You need consistent definitions, good-enough drivers, and validation with the people who run the operation. The model improves over time, but you can make meaningful decisions early if the approach is disciplined.

Will customers accept changes to service terms?

Most customers accept changes when you:

• keep the offer clear and consistent
• protect essential service for the right segments
• provide options (standard vs premium)
• communicate early and follow through reliably

The biggest risk is inconsistency — saying one thing and doing another.

Where do most organisations find the quickest wins?

Common quick wins include:

• reducing accessorials and failed deliveries through clearer delivery policies
• improving warehouse flow to reduce touches and rework
• adjusting order rules to reduce small, frequent orders
• segmenting service promises to match value

How do we avoid cost-to-serve becoming a theoretical exercise?

Anchor it to decisions. If the organisation agrees upfront what decisions it wants to make, the model becomes a tool to act — not a spreadsheet to admire.

Closing thought

Cost-to-serve optimisation isn’t about doing less for customers. It’s about doing the right amount, in the right way, for the right segments — and building a supply chain that can deliver that promise without constant firefighting.

If your supply chain feels busy but margins aren’t improving, the question worth asking is simple:

Which parts of your customer base are you unintentionally subsidising — and what would change if you could see it clearly?

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