Network Strategy and Industrial Real Estate

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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Supply Chain Benchmarking

Turning operational noise into clear, confident decisions

Most supply chains don’t fall over in a single dramatic moment. They wear down over time.

The warehouse is flat out. Transport is juggling competing priorities. Planners are living in exceptions. Customer teams are fielding complaints about delivery windows and stock availability. And somewhere in the background, the cost base quietly creeps upward — overtime here, expediting there, another “temporary” workaround that becomes permanent.

When leadership asks, “Are we actually performing well?” the answers tend to be unsatisfying:

• “It depends what you compare us to.”
• “We’re unique.”
• “We’re improving, but demand is changing.”
• “The market’s tough right now.”

All of those statements can be true. None of them help you make a decision.

That’s what supply chain benchmarking is for. It replaces guesswork with evidence. It creates a shared view of reality across operations, finance, procurement and the executive team. And, most importantly, it tells you what to do next — not in theory, but in the real world.

This article covers:

• What supply chain benchmarking is (and what it isn’t)
• The metrics that matter across planning, inventory, warehousing and transport
• How to benchmark fairly (so you don’t compare apples with forklifts)
• How to translate benchmarks into practical improvement levers
• How Trace Consultants can help Australian organisations benchmark in a way that leads to measurable uplift

What is supply chain benchmarking (really)?

Supply chain benchmarking is the disciplined practice of measuring performance and comparing it against meaningful reference points — then explaining the “why” behind the differences.

A strong benchmarking program compares you against:

1. Your own baseline over time (this year vs last year, peak vs non-peak)
2. Internal comparators (site vs site, channel vs channel, state vs state)
3. External benchmarks (peer operations, industry references, best-practice ranges)

But the value isn’t in the comparison itself. The value is in what the comparison reveals:

• Where costs are structurally higher than they should be
• Where service promise and operational capability are misaligned
• Where productivity is being eaten by rework, congestion, or poor flow
• Where commercial terms are leaking money quietly
• Where capability gaps (process, data, technology) are driving avoidable workload

What benchmarking is not

Benchmarking isn’t:

• A generic maturity score that doesn’t connect to your P&L
• Copying someone else’s operating model without context
• A one-off “health check” report that sits in a folder
• A KPI parade with 200 measures no one owns
• A blunt cost-cutting exercise that damages service and burns out teams

Good benchmarking is practical. It points to decisions you can make and actions you can take.

Why benchmarking matters in Australia right now

Australian supply chains carry some unique characteristics that can make performance harder to interpret — and easier to rationalise away.

Common realities include:

• Distance and geography: long linehaul, regional service obligations, low backhaul density in many lanes
• Labour constraints: competition for warehouse and transport labour, wage pressure, reliance on labour hire during peaks
• Customer expectations: faster delivery promises, tighter delivery windows, rising expectations for perfect orders
• Omnichannel complexity: stores plus e-commerce, returns, direct-to-consumer, wholesale, and special handling
• Network complexity: multi-node networks, cross-docks, spoke DCs, consolidation hubs
• Compliance and safety: increasing scrutiny on transport practices, fatigue management, safe loading/unloading
• Sustainability pressure: greater visibility of emissions and waste, without a blank cheque for transformation

In this environment, it’s very easy to be “busy” without getting “better”. Benchmarking helps you separate:

• what’s genuinely structural (and needs a strategic response)
• what’s operational (and can be improved through discipline)
• what’s commercial (and can be fixed through procurement and contract design)
• what’s system-driven (and needs process and technology enablement)

The four lenses of supply chain benchmarking

Benchmarking works best when it is structured around four lenses that leaders understand and operators can act on.

1) Cost: “What does it cost to serve?”

Cost benchmarking should answer:

• What does it cost to fulfil and deliver by channel and region?
• Where do costs drift (accessorials, rework, overtime, inefficiency)?
• How much cost is structural vs avoidable?

Common cost metrics include:

• Logistics cost as a percentage of sales (useful, but only when segmented properly)
• Warehouse cost per order / per line / per unit handled
• Transport cost per drop / per pallet / per carton / per tonne-kilometre
• Cost per return and cost of quality (damage, claims, rework)
• Inventory carrying cost, obsolescence and write-offs
• 3PL rate benchmarking (storage, handling, value-add, management fees)

2) Service: “What do customers experience?”

Service benchmarking should reflect customer reality, not internal comfort.

Core measures include:

• DIFOT / OTIF (On Time In Full)
• Perfect order rate (on time, in full, undamaged, correct paperwork)
• Order cycle time (promise-to-deliver)
• Fill rate, backorders and stockout rates
• Returns rates and reasons
• Claims and damage incidence

3) Productivity: “How efficiently do we convert effort into throughput?”

Productivity benchmarking exposes the operational truth: what your people and systems are actually producing for the cost.

Core measures include:

• Units or lines picked per labour hour (by process)
• Receiving productivity and dock-to-stock time
• Putaway and replenishment productivity
• Pack and dispatch rates
• Rework rates (short picks, relabels, repacks, damages)
• Equipment utilisation and downtime
• Space utilisation and congestion indicators

4) Capability and resilience: “Can we keep performing under pressure?”

This is where many supply chains win or lose — not on average days, but on peak days and disruption days.

Measures include:

• Forecast accuracy and bias by category and horizon
• Plan stability (how much churn planners push into ops)
• Inbound discipline (supplier conformance, lead time variability)
• Capacity planning maturity (labour, dock, storage, transport capacity)
• Data quality and master data discipline
• Risk controls and business continuity practices

What to benchmark across the supply chain (a practical Australian metric set)

You do not need a thousand KPIs. You need a consistent set that explains cost, service and workload drivers.

Below is a practical metric set that works across most Australian organisations, whether you’re in retail, FMCG, manufacturing, health, government, mining, hospitality, or services.

Demand planning and replenishment

• Forecast accuracy (weighted measures are often more meaningful than simple averages)
• Forecast bias (consistent over-forecasting or under-forecasting)
• Service level performance vs targets
• Replenishment stability (how often plans change)
• Exceptions per planner per week (workload proxy)
• Supplier lead time variability and adherence

Inventory and working capital

• Inventory turns by category/channel
• Days of supply (and how it changes through peaks)
• Excess and obsolete stock as a percentage of inventory
• Ageing profile and slow mover proportion
• Stockout rates and lost sales proxies (where available)
• Safety stock effectiveness (stock held where it matters)

Warehouse operations

• Labour productivity by activity (receive, putaway, replenishment, pick, pack, dispatch)
• Cost per order and cost per line (with clear definitions)
• Dock-to-stock time (receipt to available)
• Inventory accuracy (system vs physical)
• Order accuracy and error cost
• Space utilisation: cube utilisation, slot utilisation, and congestion hotspots
• Rework rate and root cause categories

Cross-dock and flow-through (if applicable)

• Flow-through volume proportion (true cross-dock vs short-term storage)
• Dwell time and missed connections
• Touches per unit (how many times handled)
• Cut-off adherence and outbound departure conformance
• Exception handling performance (damages, missing labels, overs/shorts)

Transport and distribution

• Cost per drop, per pallet, per carton (segmented by metro, regional, remote)
• On-time delivery and delivery-in-full
• Failed delivery rate and root causes
• Carrier performance scorecards (service, claims, responsiveness)
• Detention and demurrage costs (and the drivers)
• Accessorials and surcharge trends
• Empty running, fill rates, and utilisation (for in-house fleets)

Commercial and 3PL benchmarking (where relevant)

• Storage and handling rates (with clear activity definitions)
• Rate card complexity and invoice “grey areas”
• Service level commitments vs actual performance
• Contract governance maturity (how issues are raised, resolved, and prevented)
• Change control discipline (how scope creep is priced and approved)

Sustainability benchmarking (practical and measurable)

• Transport emissions proxy by lane (where data allows)
• Warehouse energy intensity (kWh per unit handled, when measurable)
• Waste and recycling rates, and disposal cost per unit
• Packaging efficiency and damage-related waste

The golden rule: compare fairly, or don’t compare at all

Benchmarking fails when the comparison isn’t fair.

Two warehouses might look similar on paper but operate in completely different worlds:

• One is pallet-in/pallet-out with stable store replenishment
• The other is high-churn e-commerce with thousands of small orders and returns

If you compare their cost per unit without context, you’ll draw the wrong conclusion.

To benchmark fairly, you must normalise for:

• Product profile: case/pallet vs each-pick, fragility, temperature control, dangerous goods
• Order profile: lines per order, units per line, volatility, cut-off times
• Channel mix: retail, e-commerce, wholesale, projects, service supply
• Geography and density: metro vs regional, delivery windows, access constraints
• Service promise: same-day, next-day, weekly replenishment
• Automation level: manual vs mechanised vs automated systems
• Operating hours and labour model: single shift vs multi-shift, agency reliance, overtime patterns
• Network constraints: number of sites, cross-docks, consolidation strategy

A proven method is segmented benchmarking:

• Benchmark each channel or segment separately (e.g., metro parcel, regional B2B, store replenishment)
• Compare like-for-like
• Then roll it up into a full cost-to-serve view

This approach protects credibility and gives you levers you can actually pull.

Where organisations usually get stuck (and how to get unstuck)

“We don’t have the data”

Most organisations do have the data — it’s just scattered, inconsistent and defined differently across sites.

The fix isn’t perfection. The fix is:

• clear KPI definitions
• repeatable extraction logic
• transparent assumptions
• validation on the floor with the people doing the work

“Our operation is unique”

Every operation has quirks. Benchmarking still works when you:

• choose sensible peer groups
• use ranges, not single-point targets
• compare trends over time and across internal comparators
• focus on drivers, not only outcomes

“People don’t trust benchmarking”

Trust is earned by how you run the process:

• involve operators early
• explain definitions and assumptions
• validate the story with site walk-throughs
• use results to learn and prioritise, not blame

Benchmarking should feel like a problem-solving exercise, not an audit.

A benchmarking approach that leads to action (not just insight)

A high-impact benchmarking program follows a sequence that builds momentum.

Step 1: Define the decisions you need to make

Benchmarking should support real decisions such as:

• Where should we focus improvement effort first?
• Should we renegotiate or go to market for transport/3PL?
• Do we have a structural network issue, or an execution issue?
• Is automation justified, and where would it actually help?
• Are we over-servicing some customers and under-servicing others?

If you don’t define the decisions, benchmarking becomes academic.

Step 2: Build a tight metric pack with clean definitions

A good pack includes:

• a handful of core KPIs per function
• clear inclusions/exclusions (what counts and what doesn’t)
• a consistent time horizon (typically 12 months plus peak views)
• segmentation that matches how you operate (channel, site, region)

Step 3: Clean, normalise and triangulate

This is where benchmarking becomes valuable, because the cleaning reveals hidden truths:

• costs not linked to activity (making cost-to-serve invisible)
• labour hours masked by cost centres (hiding rework and congestion)
• transport charges that quietly drift (accessorials and surcharges)
• service failures driven by planning churn, not warehouse effort

Step 4: Compare and explain the gap

The comparison itself is only the start. The real output is the explanation:

• what’s structural and what’s fixable
• what’s creating workload (rework, congestion, variability)
• what’s leaking money (commercial, invoicing, poor governance)
• what trade-offs exist (cost vs service vs resilience)

Step 5: Translate gaps into improvement levers

This is where the program earns executive support. Common levers include:

Warehousing levers

• slotting and pick-path optimisation
• replenishment discipline and pick-face design
• labour standards and shift redesign
• reduction of travel and congestion
• receiving and putaway flow improvements
• reduction of rework and exceptions

Transport levers

• lane segmentation and “right carrier for the right job”
• route redesign and load building improvements
• carrier rationalisation and governance uplift
• invoice hygiene and accessorial reduction
• delivery promise alignment (windows and policies that match reality)

Planning and inventory levers

• forecast bias reduction and exception management
• inventory policy reset (service segmentation and safety stock logic)
• supplier lead time performance and inbound discipline
• plan stability routines that reduce operational churn

Step 6: Build a prioritised roadmap with owners and cadence

A roadmap should be practical:

• quick wins (4–12 weeks)
• medium initiatives (3–6 months)
• structural moves (6–18 months)
• owners, dependencies, investment, and benefit ranges
• a KPI cadence that measures outcomes without gaming

Benchmarks should lead to a living improvement program, not a static report.

What “good” looks like: outcomes that matter

Benchmarking should translate into outcomes people feel:

• fewer fire drills
• more predictable service
• reduced overtime and rework
• better utilisation of assets and labour
• clearer commercial control and fewer invoice surprises
• inventory that supports service without bloating working capital
• calmer peak periods because capacity and variability are managed, not guessed

Anonymised examples (real outcomes expressed as percentages)

To illustrate the kind of value benchmarking can unlock, here are outcomes achieved in anonymised engagements where benchmarking fed into targeted improvement programs:

• Inventory reduction with service protected: In a large Australian retail environment, improvements to planning and replenishment contributed to an initial 10% inventory reduction, while maintaining in-store service levels at or above 97.5%.
• Supplier on-time uplift: In a hospitality supply chain with chronic inbound variability, operational performance improved significantly, including an 80% improvement in supplier on-time arrival performance after tightening inbound discipline and reshaping processes.
• Reduced manual handling: In a high-throughput cold storage environment, a technology and process uplift reduced manual handling by 90%, improving safety and freeing capacity for growth.

Every network is different, but the pattern is consistent: when you measure the right things, compare fairly, and act on root causes, the results follow.

How Trace Consultants can help

Benchmarking only creates value when it leads to action. Trace Consultants supports Australian organisations to run benchmarking that is credible on the floor, defensible in the boardroom, and practical to implement.

1) Rapid supply chain benchmarking diagnostic

When you need clarity quickly, we run a focused diagnostic that:

• confirms scope and decisions required
• builds a benchmark-ready KPI pack with clear definitions
• benchmarks cost, service and productivity across the end-to-end supply chain
• identifies the few high-impact opportunities that matter most

2) Warehouse benchmarking (in-house or 3PL)

We benchmark warehouse performance in a way that connects operations to cost:

• productivity and labour model analysis by activity
• capacity and space utilisation benchmarking
• rework and exception workload diagnosis
• inventory accuracy and fulfilment quality benchmarking
• 3PL rate and service benchmarking where relevant
• prioritised uplift roadmap tied to measurable outcomes

3) Transport benchmarking and optimisation

Transport costs can drift quietly through accessorials, surcharges and inconsistent governance. We support:

• lane segmentation (metro, regional, remote) and fair comparisons
• rate benchmarking and invoice hygiene review
• carrier performance scorecards and service baselines
• opportunities in routing, load building, and network design
• tender support and negotiation preparation when required

4) Cost-to-serve benchmarking and customer/channel segmentation

Cost-to-serve is where supply chain performance becomes commercial truth. We help with:

• customer and channel segmentation aligned to your operating model
• activity-based cost drivers and service policy mapping
• identification of over-servicing and leakage
• service model redesign that protects strategic customers while improving overall profitability

5) KPI frameworks and performance operating rhythm

Benchmarking fades when nobody owns it. We help establish:

• KPI definitions, governance and accountability
• practical reporting that drives decisions
• a cadence of performance routines (weekly/monthly) that sustains gains
• continuous improvement practices that stop performance drifting back

6) Technology and data enablement (when it’s the real constraint)

When the benchmark gap is driven by poor data or system limitations, we support:

• reporting automation and data model design
• planning process and system configuration improvements
• WMS/TMS and planning capability uplift
• change management and implementation support

The aim is straightforward: give you a clean, trusted performance baseline, then help you turn it into better service and lower cost-to-serve — sustainably.

A simple way to start: a 30–60–90 day benchmarking plan

If you want action without a drawn-out exercise, this phased approach works well.

First 30 days: establish the baseline

• agree scope and decisions to support
• define KPIs and segmentations
• extract and cleanse core datasets
• validate definitions with operators and finance

Next 60 days: benchmark and diagnose

• compare performance across segments and sites
• identify drivers of variance (structural vs operational vs commercial)
• quantify opportunity ranges
• start quick wins (invoice hygiene, accessorial reduction, rework hotspots)

By 90 days: lock the roadmap and governance

• prioritise initiatives by value, effort, risk and timing
• assign owners and build the delivery plan
• establish KPI cadence and tracking
• prepare for procurement/tender decisions if applicable

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Closing thought

Benchmarking is one of the few supply chain disciplines that reliably cuts through noise. It gives you a fair view of performance, identifies what’s driving cost and service outcomes, and creates a roadmap your teams can actually implement.

If your supply chain feels like it’s working hard but not moving forward, the question worth asking is: what would you discover if you benchmarked properly — a commercial leakage problem, a productivity constraint, or a service promise that no longer matches what customers value?

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Frequently asked questions

How often should we benchmark?

At least annually to support planning and budgeting. Many organisations benefit from a lighter quarterly review of key drivers (productivity, service, cost drift) to prevent slow erosion.

Can we benchmark without external data?

Yes. Internal benchmarking across sites and channels is powerful and often the fastest path to improvement. External benchmarks become critical when you need to validate commercial terms or justify strategic investment decisions.

What’s the biggest benchmarking mistake?

Comparing the wrong things and acting on the wrong conclusion. Always segment and normalise before making decisions.

Can benchmarking help with 3PL contract renewal?

Yes. Benchmarking strengthens your position by clarifying whether rates and service represent value for money and by identifying where contract structure and scope definitions need improvement.

How do we stop benchmarking becoming a one-off report?

Tie it to decision-making and build a cadence. If leaders review performance, assign actions, and follow up consistently, the benchmarking becomes part of how the business runs — not a project.

Glossary

• Cost-to-serve: Total cost to fulfil and deliver to a customer or channel, usually segmented to reveal drivers.
• DIFOT/OTIF: Delivery in full, on time — a practical measure of service reliability.
• Forecast bias: A consistent tendency to over-forecast or under-forecast.
• Accessorials: Additional transport charges beyond the base rate (waiting time, re-delivery, tail-lift, special handling).
• Dock-to-stock: Time from receiving goods to inventory being available for picking or sale.
• Rework: Any extra handling caused by errors, poor flow, damages, or exceptions that should not occur in a stable system.

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