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Research libraryInventory as a Decision

Chapter 09 of 14 · Part III · Draft web edition

Pool material and demand only where specifications and risks permit it

Centralisation and postponement can reduce duplicated buffers while increasing transit time, concentration and conversion risk.

Sections
7
Exhibits
4
Minutes
25
Sources
14
EX 37 · 0.0: Two separate exposures 2, Pooled exposure 1.4 (illustrative standard-deviation units)

The cloth is woven from this chapter's 4 exhibits: each weft is one exhibit's own data, normalised; each warp group is a section. The probe reads the exhibit's own value where it crosses. Procedural visualisation, not a measurement.

The chapter as a draft: 7 sections, 3 exhibit wefts, one shuttle.

Lead exhibit · 36LayersillustrativeInventory boundaries differ from ownership boundaries
Promise and decisionCustomer or operation due dateAllocation and replenishment…Approved service exceptionOwnership and exposureTitle and payment obligationLoss and residual-stock bearerReturns and termination rightsPhysical and conversion stateFactory, hub, distributor or…Usable, held, rejected or in…Generic, converted or custome…Measurement signalUsable receipt and issue even…Route and transfer observatio…Stock, backorder and service…

Read-outPromise and decision: Customer or operation due date, Allocation and replenishment authority, Approved service exception

Method and source

Illustrative GFT network-design schema. The layers are separate questions for every proposed pool. No supplier, factory, hub or distributor is asserted to exist, and no service or stock reduction is claimed. S01 supports differentiated supply-chain policies, S07 location-based planning and S08 explicit contractual allocation.

Unit: . Status: illustrative. Sources: S01, S07, S08. Illustrative figures are teaching examples, not measured factory results.

The chapter's warpBar: share of the reading · square: an exhibit

Section 9.0 · Opening · 1 min · no exhibit of its own · one movement Go to section ↓

Overture · 1 min

Material and demand should be pooled only where the materials are genuinely interchangeable, the combined uncertainty is smaller, and the network can still convert and deliver within the customer promise. A common warehouse or a common fabric code does not establish those conditions. Green Future Tech Limited (GFT), Hong Kong SAR, therefore treats pooling as a conditional network design, not a standing instruction to centralise. The decision must combine demand dependence, technical compatibility, conversion capacity, usable-receipt time, shared disruption exposure and residual-stock ownership.[S01][S05][S07][S17]

¶ 01 · 4 sources

S01S05S07S17

This chapter compares factory, hub, distributor and consignment positions without presenting any of them as existing GFT assets. It derives the pooling equation, tests common-input postponement, reconciles local and network stock boundaries, prices transport consolidation and examines suppliers that fail together. Every numerical case is illustrative because no factory demand history, route sample, supplier quotation or warehouse ledger has been supplied. The recommendation is to prove each proposed pool against end-customer service and whole-chain inventory before moving either stock or ordering authority.[S03][S08][S12][S30]

¶ 02 · 4 sources

S03S08S12S30

9.13 min · 8 paragraphs · 1 exhibit

A stock location is a service decision

Related · chapter 018 paragraphs step it

Related exhibit 03 · chapter 01Decision mapillustrativeEvery stock decision needs a purpose and an owner
Service-led reviewJoint promise and cash approvalRelease candidateFinance-led reviewCash committed before recovery →Delivery consequence if unavailable →Order-specific fabricApproved collar zipGeneric packagingSpeculative finished…

Read-outOrder-specific fabric: Cash committed before recovery 8, Delivery consequence if unavailable 9. Quadrant: Joint promise and cash approval

Method and source

Illustrative GFT decision charter informed by segmentation (S01), explicit service definitions (S05) and accountable discrepancy review (S27). Both axes run from 0 to 10 and are invented ordinal scores, not measured probabilities or monetary values. Each real item-location decision must separately name its service owner, cash owner, usable-stock boundary and next review; a matrix position does not assign those authorities.

Unit: illustrative ordinal screening score. Status: illustrative. Sources: S01, S05, S27. Illustrative figures are teaching examples, not measured factory results.

Read this exhibit in its chapter ↗
9.1 · Introduction · paragraph 1 of 8

A stock location earns its place by protecting a defined promise at a defined point of use. Fabric held at a sewing factory may support immediate cutting. The same fabric at a central hub may serve several factories but require a transfer, a receiving check and another allocation decision. Stock at a regional distributor may be close to a customer while remaining too far from the production operation that needs it. Consignment changes the ownership arrangement, not automatically the physical distance. Distribution requirements planning connects locations and replenishment timings, but it does not choose the service promise on the planner's behalf.[S07]

The comparison should therefore begin with the event that the buffer must protect. A make-to-order garment producer may need accepted fabric at the cutting room before a scheduled operation. A repeat-stock seller may need a complete size assortment at a dispatch point before the confirmed collection. A distributor may need saleable finished goods rather than material that still requires finishing. These promises have different stock objects and different clocks. Combining them in one network total would conceal the very shortage that the location decision is meant to prevent.[S01][S07]

Four boundaries make the choice inspectable. The physical boundary records where the material is and whether it is usable. The service boundary records the point and time at which a customer or internal operation may rely on it. The conversion boundary records what work remains before differentiation is complete. The ownership boundary records who carries the cost, loss and residual-risk exposure. A centralised design can improve one boundary while weakening another. For example, moving generic fabric upstream may reduce duplicated factory buffers but lengthen the interval between a confirmed style requirement and approved fabric at the cutting table.

A hub also introduces an allocation rule. When several factories or channels draw from one pool, the planner must decide which requirement receives stock after a delayed receipt. An aggregate availability report cannot answer that question. The policy needs a priority rule, an exception owner and a record of the orders that lose coverage when priorities change. Otherwise, centralisation can report good network service while repeatedly starving the same location. This is a governance requirement proposed by GFT, not a feature that a warehouse automatically supplies.

Exhibit 36 separates these responsibilities before any quantities are compared. It is an illustrative design, not a map of an implemented network. Its purpose is to stop a change of address or title being mistaken for a change in service or physical stock.[S01][S07][S08]

The layered view also prevents a false choice between one central warehouse and many independent stores. A network may centralise information while leaving stock near use, or centralise a generic input while distributing finished variants. It may also hold a small operational buffer locally and a contingency pool upstream, provided each buffer has a distinct protection period. The relevant design variable is not the number of buildings. It is where an irreversible commitment and a measurable service risk are placed.[S01][S05]

Actual route and channel evidence must settle the final choice. The planner needs measured transfer time to usable receipt, handling and inspection requirements, shipment frequency, channel returns, stock visibility and the cost of an emergency allocation. A location drawn on a diagram supplies none of these inputs. GFT would leave them unresolved until dated observations or explicitly approved scenarios are available, rather than insert a nominal journey time into a business case.[S12][S30]

9.23 min · 9 paragraphs · 1 exhibit

Demand correlation determines pooling potential

Step 1 of 5-1.0

Exhibit 37 · illustrativePooling benefits shrink as demands move together

00.511.52-1.0-0.50.00.51.0
00.511.52-1.0-0.50.00.51.0

-1.0

-1.0: Two separate exposures 2, Pooled exposure 0 (illustrative standard-deviation units) · illustrative

Pooling combines uncertain requirements before a buffer is sized.

-0.5

-0.5: Two separate exposures 2, Pooled exposure 1 (illustrative standard-deviation units) · illustrative

0.0

0.0: Two separate exposures 2, Pooled exposure 1.4 (illustrative standard-deviation units) · illustrative

0.5

0.5: Two separate exposures 2, Pooled exposure 1.7 (illustrative standard-deviation units) · illustrative

1.0

1.0: Two separate exposures 2, Pooled exposure 2 (illustrative standard-deviation units) · illustrative

The method behind it: Worked example: covariance changes the buffer, not the mean.

Method and source · Exhibit 37

Illustrative equal-variance pair with sigma 1 = sigma 2 = 1. Separate total = sigma 1 + sigma 2 = 2. Pooled standard deviation = sqrt(1 + 1 + 2 rho), for correlation rho from -1 to 1. The chart compares uncertainty exposure only. It excludes means, cycle stock, pipeline stock, transfer time, capacity, cash and service differences. Correlation scenarios are not measured observations.

Unit: illustrative standard-deviation units. Status: illustrative. Sources: S05. Illustrative figures are teaching examples, not measured factory results.

9.2 · the bodyExhibit 37 above; its figures are illustrative where marked.

Pooling combines uncertain requirements before a buffer is sized. Its statistical benefit comes from imperfectly correlated deviations, not from adding average demand together. For two demand or forecast-residual series D_1 and D_2, with standard deviations σ_1 and σ_2 and correlation ρ, the variance of their sum is Var(D_1 + D_2) = σ_1² + σ_2² + 2ρσ_1σ_2. This is arithmetic applied to the probabilistic inventory framework, with both series measured in the same unit over the same protection period.[S05]

The covariance term is decisive. If deviations in one location tend to offset those in another, the combined series can be less variable than the sum of separate exposures. If the same promotion, season, tender or disruption raises demand in both locations together, positive covariance removes much of that benefit. At perfect positive correlation between equal-variance demands, pooling does not reduce the standard-deviation total at all. Negative correlation can produce a larger reduction, but a planner should demonstrate a stable mechanism rather than assume that an attractive historical coefficient will persist.[S05]

¶ 02 · 1 source

S05

The familiar square-root result is a special case. For n comparable, independent demands with equal standard deviation σ, the pooled standard deviation is σ√n, while the sum of separate standard deviations is nσ. A buffer proportional to standard deviation would therefore grow with √n rather than n under that construction. The result does not say that total inventory must fall by the same proportion. Cycle stock, pipeline stock, minimum lots, local response stock, conversion losses and different service targets sit outside the simplified comparison.[S03][S05]

¶ 03 · 2 sources

S03S05

Three further conditions matter. First, the input should be the forecast residual relevant to the replenishment decision, not automatically raw sales. Second, the pooled stock must be able to reach each requirement before its due date. Third, one service definition must govern the comparison. A central buffer that offers a lower unit fill rate or a later delivery cannot be declared more efficient merely because it holds fewer units. GFT would compare the policies on common demand paths and record any unmet or late demand separately.[S05][S07]

¶ 04 · 2 sources

S05S07

Exhibit 37 shows the equal-variance boundary for a pair of demands. Both separate locations have one standard-deviation unit each, so their separate standard-deviation total is two. The pooled line follows the variance equation across constructed correlation scenarios. These are teaching values, not estimated apparel demand parameters.[S05]

¶ 05 · 1 sourceExhibit 37

S05

The horizontal separate-exposure line is not a recommended buffer. It is the benchmark that makes the covariance effect visible. Likewise, the zero at perfect negative correlation is a mathematical boundary for this equal-variance pair, not an operational promise of zero stock. Real policies still need expected demand coverage, feasible replenishment and protection against model error. The chart cannot establish that centralisation is worthwhile once transfer time and concentration are included.

¶ 06

A usable empirical study would retain aligned residual series and explain missing observations. It would test correlation across ordinary and disrupted periods, rather than report one coefficient for the full history. A positive shift during a shared selling event may be predictable and removed by the forecast, while the remaining residuals may behave differently. Conversely, a calm historical sample may contain no common port closure, supplier failure or coordinated promotion. WP04 owns the demand-estimation method; the network decision here consumes that evidence without treating a correlation estimate as a permanent physical property.[S05][S24]

¶ 07 · 2 sources

S05S24

The practical output is a range of pooling scenarios with their conditions. The planner should preserve the separate-stock comparator, show the covariance assumption, and add route and capacity constraints before interpreting the stock difference. Where the dependence structure is unstable or the sample is too small, a scenario range is more honest than a single optimised network. The pooling equation remains valid arithmetic, but its input credibility determines the strength of the recommendation.[S05]

¶ 08 · 1 source

S05

9.33 min · 9 paragraphs · 1 exhibit

Common fabric can pool risk before differentiation

Exhibit 389 paragraphs step it

Exhibit 38Decision mapillustrativePostponement is feasible only when conversion and promise times fit
Redesign conversionTest shared poolKeep separateApprove substitution firstVerified input commonality →Conversion and transfer time fit →Undyed approved fabricCertified base clothUnprinted generic lab…Customer-specific trimFinished shade variant

Read-outUndyed approved fabric: Verified input commonality 8.4, Conversion and transfer time fit 7.8. Quadrant: Test shared pool

Method and source

Illustrative GFT screening model. The horizontal axis combines verified technical and commercial interchangeability. The vertical axis represents fit among conversion, quality release, transfer and remaining promise time. Coordinates are constructed teaching judgements, not observations or statistical estimates. S07 supports specification-based requirements, S17 the conditional postponement evidence and S19 finite-capacity process modelling.

Unit: illustrative screening score from 0 to 10. Status: illustrative. Sources: S07, S17, S19. Illustrative figures are teaching examples, not measured factory results.

9.3 · Introduction · paragraph 1 of 9

Demand pooling and material pooling are related but not identical. Two styles can have imperfectly correlated demand yet still require incompatible fabric. Two styles can use the same approved fabric yet face demand that rises together, leaving little statistical pooling benefit. The strongest candidate combines technical commonality with useful demand behaviour, but it must also survive the conversion and delivery tests. A shared item name is not evidence of interchangeability. Material planning relies on the product structure and the exact component requirement.[S05][S07]

A technical commonality review should compare fibre and construction requirements, width, weight, finish, colour or shade rules, performance tests, customer approvals and permitted substitutions. It should also retain the bill-of-material version. An unprinted fabric may be common at one process stage and become non-interchangeable after dyeing, printing, coating or cutting. A trim may be physically similar but commercially unique because a customer has approved only a named specification. GFT would pool at the latest verified common stage, not at the earliest convenient purchasing description.[S07]

Postponement can preserve that common stage until better demand information arrives. Instead of holding finished stock for every style, the network holds a generic input and converts the required variant after an order or a more reliable allocation signal. The statistical buffer is then attached to the common input. This can reduce duplicated variant buffers, but it creates work that must still be performed. Dyeing, printing, embroidery, cutting, finishing, inspection and transfer all consume time and may require minimum batches or setups.[S07][S17]

The Japanese apparel evidence supports a conditional rather than promotional reading. The opened study reports that postponed manufacturing was associated with lower inventory, while postponed planning increased inventory when apparel firms externalised their retail function. It is a wholesaler survey in Japan, not a causal forecast for a Cameroon garment producer. Its useful warning is that delaying a decision can weaken control or information quality even when delaying physical differentiation helps.[S17]

A feasible postponement interval must fit inside the remaining promise window. If T_p is the time left after the demand signal, T_c the conversion and quality-release time, and T_t the transfer to the point of use, the simple feasibility condition is T_c + T_t ≤ T_p. The terms must use the same calendar and end at usable availability. Setup queues, failed inspection and capacity contention require scenarios or measured distributions, not a single optimistic duration. A mathematical pool that cannot be converted in time is only stock in the wrong form.[S07][S19]

Exhibit 38 places illustrative candidates against commonality and time fit. The positions are proposed screening judgements, not measured factory scores. They show why technical approval and process timing must be assessed together before a shared buffer is approved.[S07][S17][S19]

A candidate in the test quadrant still needs an operating trial. The trial should record conversion setup, first-pass acceptance, queue time, transfer to usable receipt and service by originating requirement. Finite-buffer simulation can represent queues, breakdowns and maintenance where those mechanisms matter, but a model does not validate its own input distributions. No such factory simulation has been performed for this chapter.[S19]

The economic comparison must also include new cycle stock. A common dye or print process may require a minimum run larger than the immediate variant requirement. Pooling can then reduce safety stock while increasing batch stock and residual variants. Setup cost and lost capacity may outweigh the uncertainty benefit, particularly when differentiation is inexpensive at a later stage closer to use. GFT would compare total relevant cost across the whole protection and conversion cycle rather than count only the reduction in variant safety stock.[S03][S07]

The decision is reversible only before differentiation becomes irreversible. That makes approval of the common stage a technical and commercial gate. If a late specification change invalidates the pool, the record should identify which commitments consumed the old version and who owns the residual material. The aim is not maximum commonality. It is the latest common form that can still meet the promise without creating a larger conversion or obsolescence exposure.[S07][S17]

Interlude · the cloth half-woven

4 exhibits carry this chapter's argument.

Woven: sections 9.0 to 9.3Still to weave: 9.4 to 9.7

  1. 36Inventory boundaries differ from ownership boundariesLayers
  2. 37Pooling benefits shrink as demands move togetherTrajectory
  3. 38Postponement is feasible only when conversion and promise times fitDecision map
  4. 39Freight savings can be consumed by slower replenishmentReconciliation
Hover or focus an exhibit to light its weft; select it to jump to it.

9.42 min · 6 paragraphs · read with a related exhibit

Multiple echelons can count the same uncertainty more than once

A network can duplicate protection without duplicating a warehouse code. A hub may size its buffer from factory orders, while each factory sizes its own buffer from end demand and uncertainty about the hub. If those decisions are made independently, both stages can protect against the same downstream deviation. The factory orders also contain batching and replenishment logic, so they are not an independent demand process that can simply be added to end-customer variability. A coordinated comparison needs one network boundary and a shared service definition.[S05][S07]

Installation stock answers a local question: what accepted quantity is held at this location under the stated status rules? Pipeline stock is moving between locations and is not yet usable at the destination. Customer backorders are unfilled obligations, not negative physical stock on a shelf. Echelon stock looks across a defined downstream network boundary so that inventory and commitments can be coordinated without treating each location as an isolated business. Distribution planning provides the location-and-time structure; the precise accounting convention must still be declared.[S07]

¶ 02 · 1 source

S07

For a proposed GFT echelon view, physical stock within the boundary is counted once, whether it sits at the hub, a downstream site or an internal transfer buffer. Firm inbound receipts are shown separately until they qualify under the planning rule. Backorders reduce the echelon inventory position under the selected convention but never turn quarantined or rejected goods into usable supply. Returns await inspection rather than being added immediately to sellable stock. These are control definitions for comparison, not claims that one formula fits every contract or accounting system.[S07][S09]

¶ 03 · 2 sources

S07S09

Note · 2 sources

S05S07

The comparison should then run the same demand and supply paths through both policies. Independent local buffers form the comparator, not an assumed inefficient straw case. The coordinated policy may place a common buffer upstream, preserve a small local response quantity and allocate against visible downstream positions. It wins only if end-customer service, total usable stock, cash exposure and exception outcomes improve under the agreed measures. A reduction at the hub accompanied by larger factory shortages is not a network improvement.[S05][S07]

¶ 04 · 2 sources

S05S07

A decentralised policy can remain preferable. Long or unreliable transfers, weak stock visibility, different local promises and frequent urgent requirements may make upstream coordination too slow. Local ownership can also make discrepancies easier to investigate. The purpose of echelon analysis is not to prove that central control is superior. It is to reveal where uncertainty is protected, where inventory is counted and which stage has authority when the plan becomes infeasible.[S01][S07]

¶ 05 · 2 sources

S01S07

9.53 min · 8 paragraphs · 1 exhibit

Transport consolidation trades freight cost against stock and time

Step 1 of 7Frequent policy

Exhibit 39 · illustrativeFreight savings can be consumed by slower replenishment

05101512Frequentpolicy−1.8Freight saving+0.9Cycle andpipeline+0.7Delay buffer+0.2Handling anddamage+0.6Expediteexposure12.6Consolidatedpolicy051015Frequent policy12Freight saving−1.8Cycle and pipeline+0.9Delay buffer+0.7Handling and damage+0.2Expedite exposure+0.6Consolidated policy12.6

Frequent policy

Frequent policy: total 12. Running total 12 illustrative XAF million per year · illustrative

Consolidation can reduce freight per unit while increasing the inventory needed to support the same promise.

Freight saving

Freight saving: removes 1.8. Running total 10.2 illustrative XAF million per year · illustrative

Cycle and pipeline

Cycle and pipeline: adds 0.9. Running total 11.1 illustrative XAF million per year · illustrative

Delay buffer

Delay buffer: adds 0.7. Running total 11.8 illustrative XAF million per year · illustrative

Handling and damage

Handling and damage: adds 0.2. Running total 12 illustrative XAF million per year · illustrative

Expedite exposure

Expedite exposure: adds 0.6. Running total 12.6 illustrative XAF million per year · illustrative

Consolidated policy

Consolidated policy: total 12.6. Running total 12.6 illustrative XAF million per year · illustrative

Method and source · Exhibit 39

Illustrative whole-chain annual cost bridge. Opening frequent-shipment policy cost = 12.0. Consolidation saves 1.8 in freight, then adds 0.9 cycle and pipeline carrying cost, 0.7 additional delay-buffer cost, 0.2 handling and damage exposure and 0.6 expedite exposure. Closing consolidated cost = 12.0 - 1.8 + 0.9 + 0.7 + 0.2 + 0.6 = 12.6. Every input is a teaching assumption. No Cameroon quote, tariff, lead time or realised cost is asserted.

Unit: illustrative XAF million per year. Status: illustrative. Sources: S03, S29, S30. Illustrative figures are teaching examples, not measured factory results.

9.5 · the bodyExhibit 39 above; its figures are illustrative where marked.

Consolidation can reduce freight per unit while increasing the inventory needed to support the same promise. A larger shipment may lower the transport rate or reduce handling events, but waiting to fill the load can lengthen the replenishment interval. That interval creates cycle stock and may delay the usable receipt that triggers a reorder. A central hub can add another transfer and inspection before material reaches production. The transport quote is therefore one component of the network policy, not its total cost.[S03][S07]

A useful comparison holds the delivered service boundary constant. For each shipment design, record order frequency, minimum and maximum load, planned dispatch interval, transit to physical arrival, clearance, receiving, quality release and emergency recovery. The inventory side includes expected cycle stock, pipeline quantity, uncertainty protection, damage or rejection, ageing and residual goods. The cost side includes freight, handling, carrying, expected expediting and service failure where those can be estimated without duplicating charges. Total-relevant-cost thinking is more informative than minimising a single rate.[S03][S30]

¶ 02 · 2 sources

S03S30

Contract terms must be read alongside the physical route. The selected Incoterms rule and named place help allocate carriage tasks, costs and risks, but they do not make the journey instantaneous and do not by themselves settle every question of title or payment. The model should retain the party responsible for each stage and the actual elapsed time whoever pays for it. Legal interpretation of a live contract requires professional review; this chapter is not legal advice.[S29]

¶ 03 · 1 source

S29

Evidence quality is especially important for route comparisons. The World Bank's revised logistics indicators use shipment-level operational data to examine connectivity, speed and reliability, reinforcing the value of observed movements rather than perception alone. That international source does not provide a factory-specific Cameroon transit distribution. The World Customs Organization guide instead supports process mapping, sampling and segmented time analysis around release. Together they justify collecting actual route events, not adopting a generic corridor average.[S12][S30]

¶ 04 · 2 sources

S12S30

Exhibit 39 constructs a case in which a freight saving is more than offset by inventory and recovery effects. All amounts are illustrative annual teaching assumptions in millions of CFA francs (XAF). They are not quotations, tariffs, measured savings or a recommendation against consolidation.[S03][S29]

¶ 05 · 2 sourcesExhibit 39

S03S29

In the illustration, a procurement view sees an annual freight reduction of XAF 1.8 million, while the whole-policy comparison shows an increase of XAF 0.6 million. Both statements follow from the constructed inputs, but only the second includes the inventory and recovery consequences. The result could reverse with reliable frequent departures, low-value materials, short transfer times or a genuine reduction in duplicated handling. The waterfall is a reconciliation template, not a universal direction of effect.[S03][S30]

¶ 06 · 2 sources

S03S30

The decision should also expose service outcomes that are difficult to price honestly. If a late consolidated shipment stops a line or misses a customer collection, the planner should show the affected order and recovery action rather than bury it in a speculative goodwill charge. Where cash limits prevent the extra stock, the consolidated design may be infeasible even when its modelled annual cost is lower. The alternative is then to change shipment frequency, renegotiate the minimum load or revise the service promise explicitly.[S03][S05]

¶ 07 · 2 sources

S03S05

Before approval, GFT would request dated carrier and handling quotations, actual transit and release samples, packaging and damage evidence, and a statement of which party bears each cost. Open shipments must remain visible in the sample so completed journeys do not hide the tail. Until those inputs exist, the network case should present scenarios with unresolved fields, not a precise freight or journey claim.[S12][S30]

¶ 08 · 2 sources

S12S30

9.62 min · 7 paragraphs · read with a related exhibit

Two suppliers may still share one disruption

Supplier count is not the same as independent supply. Two vendors may buy from the same upstream mill, use the same port, depend on the same power or communications infrastructure, or subcontract to the same specialist process. A garment network can therefore appear diversified at the first contractual tier while remaining concentrated at the point that actually determines usable receipt. The OECD notes that subcontracting is common in garment and footwear supply chains, which makes indirect stages a necessary part of the dependence map.[S25]

The same caution applies to pooled inventory. A single hub may serve several demand points efficiently during ordinary variation but concentrate exposure to a site outage, system failure, transport interruption or quality hold. Separate local stocks can contain some events, while a common pool can deplete everywhere after one upstream shock. The choice is not between resilience and efficiency as slogans. It is between explicit failure modes, quantities and recovery times under each design.[S05][S24]

¶ 02 · 2 sources

S05S24

Probability notation makes the missing evidence visible. If A and B are the events that two sources are usable when required, the probability that at least one is usable is P(A or B) = P(A) + P(B) - P(A and B). Independence would simplify the joint term, but it is precisely the assumption that a shared mill, route or subcontractor can invalidate. The planner needs evidence about the intersection, not just each supplier's separate on-time history.[S05][S25]

¶ 03 · 2 sources

S05S25

Stochastic lead-time research provides another warning against convenient assumptions. The opened manuscript analyses models with independent and identically distributed lead times while also discussing their limitations and the need to study dependence between lead times and demand. It does not establish that any garment supplier has independent delays. GFT would use such models as scenario structures and test their assumptions against usable-receipt observations.[S24]

¶ 04 · 1 source

S24

A stress design should contain at least three distinct paths: ordinary separate delays, a shared upstream or corridor event, and loss of the pooled location or conversion process. The first path tests routine buffers. The second tests whether apparent source diversification survives common dependence. The third tests concentration created by the network itself. Each path should record which customer promises fail, which substitute is technically approved, how much stock remains usable and who may authorise emergency allocation. No probability needs to be invented to make those actions inspectable.

¶ 05

Qualification must precede the emergency. An alternate source needs the same specification, test-lot, capacity and usable-receipt checks as any other source, together with a map of its upstream dependencies. A second contact in a procurement database is not a qualified recovery route. If both qualified sources share an unavoidable dependency, the policy should say so and consider a different material, route, stock position or customer promise rather than assign false independence.[S07][S25]

¶ 06 · 2 sources

S07S25

This analysis can also change the demand-pooling result. A common disruption may raise demand for substitutes at the same time that it restricts supply, producing adverse correlation between requirements and availability. The calm-period covariance estimate would then overstate pooling protection precisely when the buffer is most needed. GFT would therefore report ordinary-demand pooling and shared-shock stress separately, with no claim that one historical correlation coefficient covers both.[S05][S24]

¶ 07 · 2 sources

S05S24

9.72 min · 7 paragraphs · read with a related exhibit

The network decision must state who carries residual stock

Pooling changes incentives as well as quantities. A supplier-owned buffer, a factory-owned hub, distributor stock and consignment arrangements allocate ordering authority, payment, loss and obsolete material differently. Supply-chain contract analysis shows why the allocation of overage risk matters to ordering incentives and why a buyback or return right must be assessed across the chain. A contract can move exposure without removing the physical units or the uncertainty that created them.[S08]

The decision record should state who forecasts, who may release replenishment, when quantity becomes binding, who owns stock at each stage, who pays for carriage and storage, and who may return or redirect residual units. It should also define damage, shrinkage, quality rejection, specification change, termination and dispute treatment. Visibility is a separate field: a party that owns stock may still lack timely quantity and status information, while a party without title may carry the operational consequence of a shortage.[S07][S08]

¶ 02 · 2 sources

S07S08

Consignment is a clear example of why factory stock and whole-chain stock must be reported separately. Moving material to a supplier's balance sheet may reduce the factory's recorded inventory or change its cash timing, but the material still occupies a location and may still be reserved for the same customer promise. Conversely, shifting finished goods to a distributor does not prove that end demand has been served. The network review should count physical quantities once and show ownership as an additional dimension rather than using ownership to erase stock.[S07][S08]

¶ 03 · 2 sources

S07S08

Residual value requires equal care. IAS 2 states that inventories are measured at the lower of cost and net realisable value, which provides accounting context for write-down exposure. It does not tell the network which pooling policy is operationally preferable, and applicable reporting treatment needs professional confirmation. A pooled generic input may retain more recovery options than differentiated variants, but that advantage depends on actual alternative uses, approval rules and selling or recovery costs.[S09]

¶ 04 · 1 source

S09

A whole-chain review should also ask how the apparent improvement was obtained. The ILO's global supplier survey motivates attention to purchasing practices and working conditions, while its age, voluntary response and international scope prevent any inference about current Cameroon prevalence. Within this chapter, the implication is narrow: do not describe lower factory inventory as a clean gain if it depends on unexamined supplier pressure, unrealistic changes or unpaid recovery work.[S10]

¶ 05 · 1 source

S10

Note · 3 sources

S05S07S08

The final network choice should present a frontier rather than a universal answer. A central generic-material pool may suit compatible inputs, offsetting demand and reliable conversion. Local buffers may dominate where promises are short, routes unreliable or failure containment matters. A mixed design may be appropriate when local response stock and upstream contingency stock protect different horizons. In each case, the recommendation remains conditional on measured service, feasible conversion, visible stock and an accountable owner for what remains.[S01][S05][S07]

¶ 06 · 3 sources

S01S05S07

Check the record

The chapter keeps its sources within reach.

Every knot is a source this chapter cites; select one to read its record, or filter the register by grade. Publication dates and inherited-source limits stay explicit. Read the paper's full evidence summary.

14 sources · 111 citation marks on this pageMost cited: S07, 26 times

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c09-S01 · Grade A

MIT OpenCourseWare

Supply chain fundamentals and segmentation analysis

This resource contains lecture slides on supply chain fundamentals and segmentation analysis.

2006. Register access date: 2026-10-30. Source provenance is supplied by the paper evidence register.

Open the recorded source ↗
Chapter source notes

S01 MIT OpenCourseWare. 2006.

S05 MIT OpenCourseWare. 2006.

S07 MIT OpenCourseWare. 2006.

S17 Japan Marketing Academy, Quarterly Journal of Marketing. 2020-03-31.

S03 MIT OpenCourseWare. 2006.

S08 MIT OpenCourseWare. 2006.

S12 World Bank. 2025.

S30 World Customs Organization. 2025.

S24 arXiv, Michna, Nielsen and Nielsen. 2015-03-20.

S19 National Institute of Standards and Technology. 2022-01-05.

S09 IFRS Foundation. n.d..

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Keep the thread · chapter 09 of 14

Chapter 10 picks up the thread.

Move the shuttle along the rack to preview any chapter: its sections, exhibits and reading time. Draft web edition. This research is not investment, legal or tax advice; illustrative models are not measured factory results.

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10Part III: Resolve constraints across the supply chain

Supplier reliability and fair contracts change how much stock is needed

Procurement should price usable delivery and shared risk rather than reward low quotes that create expensive disruption.

  • 10.1An on-time dispatch can still be an unusable delivery
  • 10.3Supplier scoring needs visible trade-offs
  • 10.5Order amplification is a system outcome
  • 10.7Shared demand information needs an agreed meaning
Reading time
27 min
Exhibits
5
Sections
7
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