1. Foundations of Supply Chain PlanningIntroduction and contextSupply chain planning is the coordinated process through which an organisation anticipates demand, determines how that demand will be fulfilled, allocates resources, and aligns activities across suppliers, manufacturers, logistics providers, distributors, retailers, and customers. It is broader than production planning or inventory control. It connects commercial intentions with operational capability and translates uncertain market requirements into decisions about capacity, materials, labour, inventory, transportation, and customer service. A supply chain exists because the activities required to create and deliver value are distributed across multiple organisations and locations. Raw materials may be sourced globally, transformed in several production stages, stored in regional facilities, and delivered through different channels. Each participant makes decisions based on incomplete information, different objectives, and different time horizons. Planning provides the mechanisms for coordinating these decisions. The central managerial problem is deceptively simple: customers want products in particular quantities, at particular times, locations, prices, and service levels, while supply is constrained by resources, lead times, capacity, quality requirements, regulations, and uncertainty. Supply chain planning seeks a feasible and economically sound match between demand and supply. It must also recognise that a plan is not a prediction of the future alone; it is a set of choices about how the organisation intends to respond to possible futures. For postgraduate logistics students, this foundation is important because later topics—forecasting methods, sales and operations planning, inventory optimisation, procurement, distribution requirements planning, and supply chain analytics—depend on an understanding of the structure and logic of the planning system. Learning objectivesBy the end of this chapter, the reader should be able to: 1. Describe the structure of a supply chain and distinguish its principal flows. 2. Explain strategic, tactical, and operational planning horizons and their interdependence. 3. Compare push, pull, and hybrid supply chain systems. 4. Identify decoupling points and explain their significance for responsiveness and inventory. 5. Analyse how demand and supply are matched under uncertainty and constraints. 6. Explain the bullwhip effect, its causes, consequences, and mitigation approaches. 7. Apply supply chain planning concepts to managerial and logistics decisions. 8. Evaluate the role of digital systems, analytics, governance, and professional judgement in planning. The supply chain as an interconnected systemA supply chain is a network rather than a simple linear chain. It includes upstream suppliers, focal firms, contract manufacturers, logistics service providers, wholesalers, retailers, customers, and reverse-flow partners. A firm may simultaneously belong to several supply chains: a manufacturer purchases components from one network, sells finished goods through another, and manages returns through a third. The network can be viewed in terms of several structural dimensions. The echelon describes a stage or level in the network, such as supplier, plant, distribution centre, or retailer. Upstream refers to activities closer to sources of raw materials, while downstream refers to activities closer to the final customer. The focal firm is the organisation whose planning problem is being examined. Supply chain scope defines which organisations, processes, products, and geographic areas are included in the analysis. A useful distinction is between the physical network and the information network. The physical network contains facilities, inventories, vehicles, equipment, and material-handling systems. The information network contains forecasts, orders, inventory records, production schedules, shipment notifications, prices, capacity data, and performance measures. Financial flows connect the two through invoices, credit terms, payments, working capital, and investment decisions. The principal flowsMaterial flow moves upstream-to-downstream in the form of raw materials, components, work-in-process, finished products, packaging, and spare parts. In many sectors, material flow is not continuous. It may be interrupted by batch production, transport consolidation, customs clearance, or storage constraints. Information flow moves in both directions. Customer orders, point-of-sale data, forecasts, inventory positions, and market signals generally move upstream. Product availability, order confirmations, shipment status, lead times, and delivery commitments move downstream. Information quality is often more important than information volume. A large quantity of delayed or inconsistent data can produce worse decisions than a smaller quantity of timely, reliable information. Financial flow usually moves from customers toward suppliers through payments, although financing arrangements, rebates, deposits, and credit support may move in other directions. Financial constraints influence planning because a theoretically feasible plan may be unacceptable if it creates excessive working-capital requirements. Return and recovery flow moves in the reverse direction. It includes customer returns, defective products, reusable packaging, repairs, recycling, remanufacturing, and disposal. Reverse logistics is not merely a service activity; it affects inventory availability, transport capacity, environmental performance, and product-life-cycle economics. These flows are interdependent. A change in payment terms can influence supplier capacity; a change in product design can alter transport and return requirements; and an inaccurate inventory record can cause both excessive purchasing and customer shortages. Planning horizons and the architecture of decisionsSupply chain planning is commonly divided into strategic, tactical, and operational levels. The boundaries are not universal, but the distinction is useful because decisions differ in time horizon, level of aggregation, reversibility, and information requirements. Strategic planningStrategic planning normally considers a horizon of several years. It addresses decisions that are expensive or difficult to reverse, including facility location, network design, production technology, make-or-buy policy, supplier development, distribution-channel architecture, and long-term capacity. Strategic decisions establish the operating conditions within which tactical and operational plans must function. For example, a company deciding to serve a national market from one central distribution centre may reduce facility costs but accept longer delivery distances and greater transport exposure. Establishing regional facilities may improve responsiveness but increase inventory duplication and fixed costs. Network design therefore requires analysis of total cost, service, risk, resilience, tax, labour, sustainability, and regulatory conditions rather than a narrow focus on transport expense. Strategic planning uses aggregated data and scenarios. Forecasts at this level may concern product families, regions, or market segments rather than individual stock-keeping units. The objective is not to produce a detailed schedule but to determine whether the network can support the intended business strategy. Tactical planningTactical planning usually covers several months to approximately two years, depending on the industry. It converts strategic choices into medium-term plans for capacity, workforce, procurement, production rates, inventory policies, transport commitments, and supplier collaboration. Sales and operations planning, or integrated business planning, is a central tactical process. It brings together demand, supply, finance, marketing, sales, procurement, manufacturing, and logistics. The process commonly compares an unconstrained demand plan with available supply, identifies gaps, evaluates alternatives, and obtains management agreement on a feasible plan. Tactical planning works with product families and time buckets such as weeks or months. It may decide whether to build inventory before a seasonal peak, use overtime, subcontract production, adjust promotions, revise safety-stock policies, or allocate scarce supply among markets. The tactical plan provides guidance to master production scheduling, procurement, and distribution planning. Operational planningOperational planning concerns the near term: days, weeks, or sometimes hours. It converts aggregate plans into specific orders, schedules, routes, assignments, and replenishment actions. Examples include releasing a purchase order, sequencing production jobs, assigning a vehicle, picking an order, or reallocating inventory between locations. Operational decisions rely on more detailed and current information than strategic decisions. They are also more exposed to execution variability, such as machine breakdowns, late deliveries, labour absence, traffic disruption, and order changes. Operational planning must therefore combine system-generated recommendations with human judgement and escalation rules. The three levels are connected but not interchangeable. Strategic plans define capacity and network boundaries; tactical plans allocate resources within those boundaries; operational plans execute and adjust the chosen response. A weakness at one level often appears as a problem at another. For instance, chronic operational expediting may indicate a tactical capacity gap or a strategic network design problem. Push, pull, and the location of responsivenessA push system initiates production or replenishment in anticipation of future demand. Decisions are based primarily on forecasts, planned orders, historical patterns, and expected market requirements. Push systems are appropriate when production or purchasing lead times are long, demand is relatively predictable, or economies of scale make advance production advantageous. Their risk is that forecast error creates excess inventory, markdowns, obsolescence, or shortages. A pull system initiates activity in response to actual consumption or a downstream signal. A replenishment order, kanban signal, or customer configuration request can trigger movement or production. Pull reduces the risk of producing without a demand signal, but it cannot eliminate the effects of long lead times or limited capacity. If demand arrives faster than the system can respond, shortages result. Most real supply chains are hybrid systems. Upstream activities may be forecast-driven while downstream activities respond to actual orders. The point at which the system changes from push to pull is called the customer order decoupling point, order penetration point, or, in a broader inventory context, a decoupling point. It is the location where inventory or capacity separates forecast-dependent operations from order-driven operations. Consider four configurations. In make-to-stock, finished goods are produced before the customer order and held in inventory. In assemble-to-order, components are forecast-positioned but final assembly waits for an order. In make-to-order, production begins after the order is received. In engineer-to-order, design and production are both substantially driven by a specific customer requirement. As the decoupling point moves upstream, customer responsiveness may increase, but the firm generally needs more flexible processes and may expose the customer to longer lead times. Decoupling points are managerial choices, not merely physical locations. They are influenced by demand variability, product variety, lead time, postponement opportunities, component commonality, capacity flexibility, service commitments, and the cost of inventory. Postponement deliberately delays final product differentiation until demand is known. For example, generic components may be held centrally and configured or packaged closer to the customer. Matching demand and supplyDemand planning begins with an estimate of what customers may require. Forecasts may use historical sales, causal variables, market intelligence, customer commitments, promotions, economic indicators, and expert judgement. A forecast is not the same as a sales target. A forecast describes expected demand under specified assumptions; a target expresses desired performance. Confusing the two can lead to systematic bias in supply decisions. Supply planning determines how the organisation will meet the demand plan using available or attainable resources. It considers production capacity, supplier capability, inventory, labour, equipment, transportation, lead times, storage space, cash, and service priorities. The supply plan may be constrained by physical capacity or may include decisions to obtain additional capacity through overtime, outsourcing, subcontracting, inventory pre-build, or alternative sourcing. Demand and supply matching is not simply a matter of equating two quantities. Timing, location, product identity, quality, and service level matter. Ten thousand units available in the wrong region or at the wrong time may not satisfy the demand requirement. Similarly, aggregate capacity may appear sufficient while a particular machine, component, skill, or transport lane is a bottleneck. A basic planning balance can be expressed as: Projected ending inventory = beginning inventory + planned receipts − expected demand If projected inventory falls below the required safety level, the planner may bring forward a receipt, increase supply, substitute a product, reallocate inventory, or accept a service-risk decision. Safety stock protects against uncertainty in demand and replenishment, but it is not a substitute for reliable processes. Excessive safety stock can conceal poor forecasting, long lead times, or inaccurate records. A useful planning process distinguishes between the unconstrained demand plan and the constrained supply plan. The first asks what customers and commercial functions expect to sell. The second asks what can actually be supplied within available resources. The reconciliation process makes trade-offs explicit. It may result in revised demand assumptions, capacity investment, allocation rules, price changes, or differentiated service levels. Allocation is especially important when supply is scarce. Possible rules include serving contractual commitments first, protecting strategic customers, allocating proportionally, prioritising high-margin products, or distributing according to transparent fairness criteria. Each rule has commercial, ethical, and operational consequences. The bullwhip effect and amplification of variabilityThe bullwhip effect occurs when variability in orders increases as one moves upstream in a supply chain, even when final customer demand is comparatively stable. A retailer may experience modest fluctuations in sales, while its distributor sees larger order changes and the manufacturer experiences still larger production swings. Several mechanisms contribute to amplification. First, each stage may forecast from the orders it receives rather than from actual end-customer demand. Second, long replenishment lead times encourage firms to place larger orders to protect against uncertainty. Third, order batching reduces transaction or transport costs but creates lumpy demand. Fourth, temporary price discounts and promotions encourage forward buying. Fifth, shortages may cause customers to inflate orders, while rationing rules can further distort signals. Finally, poor data quality and weak coordination cause each organisation to compensate independently. The consequences include excess inventory in some locations, shortages in others, unstable production schedules, overtime, expediting, inefficient transport, supplier stress, and deteriorating customer service. The bullwhip effect is therefore a system problem, not simply a forecasting problem. Mitigation requires coordinated action. Organisations can share point-of-sale data, shorten and stabilise lead times, reduce order batching, use electronic replenishment, improve forecast collaboration, establish consistent pricing, and agree on allocation and replenishment rules. Vendor-managed inventory and collaborative planning, forecasting, and replenishment can reduce duplicated decision-making when governance and incentives are properly designed. Information sharing alone is insufficient if participants do not trust the data or continue to optimise conflicting local objectives. A framework for integrated supply chain planningAn effective planning system links five analytical questions: 1. What is likely to be demanded? This is the forecasting and market-intelligence question. 2. What has already been committed? Orders, contracts, promotions, and service agreements create obligations. 3. What resources are available? Inventory, capacity, labour, suppliers, finance, and transport determine feasibility. 4. What alternatives exist? The organisation may change timing, sourcing, production, allocation, pricing, or service priorities. 5. How will performance and assumptions be reviewed? Plans require feedback, exception management, and learning. The framework should operate at multiple levels of aggregation. Strategic plans use product families and network scenarios; tactical plans use families, locations, and time buckets; operational plans use individual items, orders, work centres, and routes. Poor aggregation can produce either excessive complexity or a loss of decision-relevant detail. Planning also requires a clear hierarchy of plans. A business or strategic plan sets financial and market direction. The demand plan translates market expectations into volumes and timing. The supply plan tests feasibility. The master production schedule identifies what finished goods or major assemblies should be produced. Material requirements planning converts this into component and purchasing requirements. Distribution requirements planning coordinates replenishment across locations. Execution systems then release, monitor, and revise orders. This hierarchy should not be interpreted as a rigid one-way cascade. Feedback is essential. If a supplier cannot meet a component requirement, the tactical plan may need revision. If customers respond differently to a promotion, the demand plan must be updated. Planning is therefore a controlled learning cycle rather than a single annual exercise. Digital planning, analytics, and professional judgementEnterprise resource planning systems integrate transactions and provide a common data structure for inventory, orders, procurement, production, and finance. Advanced planning and optimisation systems add forecasting, finite-capacity scheduling, network modelling, inventory optimisation, and scenario analysis. Warehouse management, transport management, point-of-sale, supplier portals, and electronic data interchange extend visibility across the network. Analytics can improve planning in several ways. Descriptive analytics shows what happened; diagnostic analytics investigates why it happened; predictive analytics estimates what may happen; and prescriptive analytics evaluates possible actions. Machine-learning models may identify nonlinear demand patterns, forecast intermittent demand, detect anomalies, or estimate lead-time risk. Digital twins and scenario models can test the effects of capacity loss, facility closure, supplier disruption, or demand surges. Technology does not remove the need for managerial judgement. Algorithms depend on data quality, assumptions, objective functions, and governance. A model trained on historical data may reproduce past bias or fail during structural change. Automated recommendations can also create correlated decisions across many facilities, amplifying errors. Planners should therefore use exception-based management, sensitivity analysis, audit trails, human approval for material decisions, and clear accountability. Important data controls include common item and location identifiers, consistent units of measure, accurate bills of material, reliable inventory records, valid lead times, disciplined master-data maintenance, and documented forecast overrides. Cybersecurity is also a planning concern because disruption to planning or execution systems can interrupt material flow and expose commercially sensitive information. Illustrative case: postponement and allocation in a consumer-electronics networkBackgroundThe following is a fictional illustrative case. Orion Devices sells a family of smart home controllers through online retailers and specialist distributors. The products share a common electronic core but require different power adapters, language configurations, and packaging for five regional markets. Situation and problemOrion historically produced finished regional versions in a plant close to its principal component suppliers. Forecast errors were frequent because regional demand varied with promotions and exchange rates. Some markets accumulated obsolete inventory while others experienced stockouts. Retailers responded by increasing order quantities before promotions, which magnified variability for Orion’s plant and suppliers. The company’s logistics director identified three related problems: the push system extended too far downstream, regional forecasts were being treated as firm commitments, and allocation rules during shortages were unclear. The firm also lacked a single view of inventory in transit and available-to-promise stock. AnalysisAn analysis of the product structure showed that approximately 70 per cent of the unit’s components were common across regions. Regional differentiation occurred mainly through the adapter, software configuration, documentation, and packaging. These activities could be postponed until a customer order or a more reliable regional signal was available. The team compared three alternatives. Producing all finished goods regionally preserved short delivery times but retained high obsolescence risk. Producing generic units centrally and completing regional configuration near demand would require investment in late-stage facilities but reduce forecast exposure. Producing only to order would minimise finished-goods inventory but create unacceptable lead times during promotions. Approach and solutionOrion adopted a hybrid design. Generic units were produced against an aggregate family forecast and held at a central postponement facility. Regional configuration and packaging were triggered by replenishment signals based on actual distributor consumption and agreed promotional information. Common components were protected with targeted safety stock, while regional finished-goods safety stock was reduced. The company also introduced a cross-functional monthly planning meeting. The demand team presented an unconstrained regional forecast; supply planners tested component and configuration capacity; commercial managers disclosed promotions; and logistics managers reviewed transport and inventory-position data. During shortages, allocation prioritised contractual service commitments, then allocated remaining supply by a transparent proportional rule rather than accepting inflated orders. OutcomeThe redesigned process reduced dependence on detailed regional forecasts before demand became visible and made the decoupling point more responsive. It did not eliminate uncertainty: configuration capacity became a new constraint, and the central facility required accurate inventory records. Nevertheless, the planning team obtained better control of product variety, improved the quality of demand signals, and reduced the risk that one region’s forecast error would create another region’s obsolete stock. Learning pointsThe case illustrates that postponement is effective only when product architecture, process flexibility, information quality, and logistics capability support it. It also shows that a decoupling point is a strategic and tactical design decision. Finally, better planning requires both physical redesign and behavioural coordination; changing the inventory location without changing order policies would have preserved the bullwhip effect. Challenges, risks, and common planning errorsSupply chain planning is difficult because uncertainty exists at every stage. Demand may change, suppliers may fail, transport may be disrupted, and the organisation may not know its true inventory position. Common errors include: - treating a forecast as a commitment rather than an uncertain estimate;
- planning at an inappropriate level of detail;
- ignoring capacity, cash, labour, or transport constraints;
- using average lead times when variability is operationally important;
- allowing local cost targets to damage total supply chain performance;
- placing excessive reliance on safety stock;
- changing forecasts without recording the reason or responsible decision-maker;
- measuring forecast accuracy without considering bias and service impact;
- releasing urgent orders to compensate for weak master data; and
- failing to distinguish a temporary exception from a structural problem.
Performance measures can also create dysfunctional behaviour. If a plant is measured only on utilisation, it may produce unwanted inventory. If procurement is measured only on purchase price, it may favour large batches or distant suppliers that increase total logistics cost and risk. Balanced measures should cover service, inventory, cost, capacity utilisation, forecast bias, schedule stability, resilience, quality, and sustainability. Governance, ethics, and sustainabilityPlanning decisions distribute scarce resources and therefore have ethical as well as financial consequences. During shortages, allocation rules should be transparent, consistently applied, and reviewed for discriminatory effects. Customer data used for demand sensing must be handled lawfully and responsibly. Supplier information should be protected, and collaborative forecasting should not become a mechanism for sharing competitively sensitive information improperly. Governance requires defined decision rights: who owns the forecast, who approves overrides, who can change allocation rules, and who accepts service or financial risk. Assumptions should be documented, scenarios retained, and significant decisions auditable. Regulatory requirements may affect product traceability, safety stock, import controls, hazardous materials, data protection, and environmental reporting. Sustainability should be integrated into planning rather than treated as a separate reporting activity. Choices about transport mode, facility location, packaging, inventory obsolescence, returns, and supplier selection affect emissions and resource use. A plan that minimises financial cost while generating avoidable waste may be economically incomplete. Lifecycle analysis and total-cost assessment provide a broader basis for decision-making. Current developments and best practicesSeveral developments are changing supply chain planning. Demand sensing uses near-real-time signals such as point-of-sale data, web activity, weather, and promotional information. Control towers combine data from multiple systems to support exception management. Scenario planning and probabilistic forecasts are increasingly used to represent ranges of possible demand rather than one supposedly precise number. Resilience planning emphasises multi-sourcing, strategic buffers, alternate logistics routes, and recovery capability. Sustainability requirements are also driving supplier traceability and carbon-aware network decisions. Best practice is not a single software package or forecasting algorithm. It is a disciplined management system that: 1. aligns planning horizons and decision rights; 2. separates assumptions, commitments, and targets; 3. integrates demand, supply, finance, and logistics; 4. uses end-customer signals wherever possible; 5. positions inventory deliberately around decoupling points; 6. exposes constraints and evaluates alternatives; 7. measures total system performance rather than isolated departmental efficiency; 8. combines automation with human review and accountability; and 9. learns from forecast error, disruptions, and execution outcomes. Chapter SummarySupply chain planning coordinates demand, supply, resources, and decisions across a network of interconnected organisations. The network contains material, information, financial, and reverse flows, and its performance depends on how these flows are synchronised. Strategic planning shapes the network and long-term capacity; tactical planning reconciles demand and supply over the medium term; and operational planning executes detailed orders, schedules, and logistics activities. Push systems act in anticipation of demand, while pull systems respond to actual consumption or orders. Most supply chains combine both, with a decoupling point separating forecast-driven and order-driven activity. Demand–supply matching must consider timing, location, capacity, inventory, and service rather than volume alone. The bullwhip effect demonstrates how local decisions, long lead times, order batching, promotions, and weak information can amplify variability upstream. Collaboration, shorter lead times, better data, stable policies, and transparent governance can reduce this amplification. Digital planning systems, advanced analytics, and AI can improve visibility and scenario analysis, but they require sound data, appropriate objectives, cybersecurity, and professional judgement. Effective planning is a continuous learning process supported by integrated governance, balanced performance measures, ethical allocation, and sustainability-aware decisions. Key TermsSupply chain: A network of organisations, processes, resources, and flows involved in creating and delivering value to customers. Focal firm: The organisation whose supply chain or planning problem is being analysed. Echelon: A stage or level in a supply network, such as supplier, plant, warehouse, or retailer. Material flow: The movement of raw materials, components, work-in-process, and finished products through the network. Information flow: The exchange of forecasts, orders, inventory data, schedules, and status information among supply chain participants. Financial flow: The movement of payments, credit, invoices, and working capital associated with supply chain transactions. Reverse logistics: The management of returns, repairs, recycling, remanufacturing, reusable packaging, and disposal. Strategic planning: Long-term planning concerning network design, technology, sourcing, facilities, and structural capacity. Tactical planning: Medium-term planning concerning aggregate demand, capacity, procurement, inventory, and resource allocation. Operational planning: Short-term planning concerning detailed orders, schedules, routes, assignments, and execution decisions. Push system: A system in which production or replenishment is initiated mainly from forecasts or anticipated demand. Pull system: A system in which production or replenishment is triggered mainly by actual consumption or downstream demand signals. Decoupling point: The location or stage separating forecast-driven activities from order-driven activities. Postponement: Delaying product differentiation or final configuration until demand information becomes more certain. Safety stock: Inventory held to protect against uncertainty in demand, supply, or replenishment lead time. Bullwhip effect: The amplification of demand variability as orders move upstream through a supply chain. Demand plan: An estimate of expected market requirements over specified products, locations, and periods. Supply plan: A feasible proposal for meeting demand using available or attainable resources. Sales and operations planning: A cross-functional process for reconciling demand, supply, finance, and business priorities. Available-to-promise: The quantity and timing of supply that can credibly be committed to customer orders. Review QuestionsShort Answer Questions1. What are the four principal flows in a supply chain? 2. Distinguish strategic, tactical, and operational planning. 3. What is meant by a decoupling point? 4. Why is a forecast not the same as a sales target? 5. Define the bullwhip effect. Long Answer Questions1. Explain how material, information, financial, and reverse flows interact in a supply network. 2. Compare push, pull, and hybrid systems, including the conditions under which each is appropriate. 3. Discuss how strategic, tactical, and operational planning decisions depend on one another. 4. Explain the main causes and consequences of the bullwhip effect and evaluate methods for reducing it. 5. Describe how an organisation can reconcile an unconstrained demand plan with a constrained supply plan. Analytical / Application Questions1. A retailer has stable weekly sales, but its distributor and manufacturer experience increasingly variable orders. Diagnose the likely causes and recommend a coordinated response. 2. A firm sells customised products with common components and region-specific packaging. Where would you place the decoupling point, and what factors would determine the decision? 3. A company has high inventory, frequent shortages, and strong plant utilisation. Use supply chain planning concepts to explain how these outcomes may coexist and propose corrective measures. 22. Multiple Choice Questions with AnswersQuestion 1Which statement best describes the relationship between strategic, tactical, and operational supply chain planning? A. Operational planning determines the network structure, while strategic planning releases daily orders. B. Strategic planning establishes structural conditions, tactical planning allocates medium-term resources, and operational planning executes detailed activities. C. Tactical planning is concerned only with financial reporting and has no connection with logistics. D. The three levels are independent because each uses a different supply chain. Correct Answer: B. Strategic planning establishes structural conditions, tactical planning allocates medium-term resources, and operational planning executes detailed activities. Question 2A company holds generic products centrally and adds country-specific packaging only after regional demand becomes clearer. What planning concept does this illustrate? A. Forward buying B. Order batching C. Postponement at a decoupling point D. Complete make-to-stock production Correct Answer: C. Postponement at a decoupling point Question 3Which situation is most likely to produce a bullwhip effect? A. Retailers share point-of-sale data and replenish frequently in small quantities. B. All members use stable prices and a common replenishment policy. C. Upstream suppliers receive accurate end-customer demand data in real time. D. Customers inflate orders during shortages while each stage forecasts from incoming orders. Correct Answer: D. Customers inflate orders during shortages while each stage forecasts from incoming orders. Question 4A firm has sufficient total inventory, but customers in one region face shortages while another region holds excess stock. What does this most directly demonstrate? A. Volume alone does not ensure demand–supply matching; timing and location also matter. B. The firm has necessarily eliminated all supply risk. C. Strategic planning is unnecessary when aggregate inventory is high. D. Pull systems always create regional imbalance. Correct Answer: A. Volume alone does not ensure demand–supply matching; timing and location also matter. Question 5Which is a principal risk of relying exclusively on a push system? A. It cannot use any forecast information. B. It may create excess or obsolete inventory when forecasts are inaccurate. C. It always produces longer customer lead times than a pull system. D. It eliminates economies of scale. Correct Answer: B. It may create excess or obsolete inventory when forecasts are inaccurate. Question 6Which action would most directly reduce order amplification caused by order batching? A. Increase the size of every replenishment order. B. Use more temporary price discounts. C. Increase ordering frequency while reducing transaction and transport barriers. D. Require each stage to forecast independently. Correct Answer: C. Increase ordering frequency while reducing transaction and transport barriers. Question 7In an integrated planning process, what is the purpose of comparing an unconstrained demand plan with a constrained supply plan? A. To hide capacity shortages from commercial functions. B. To determine whether expected demand can be met and evaluate alternatives when it cannot. C. To replace all forecasts with financial targets. D. To ensure that production utilisation is always maximised. Correct Answer: B. To determine whether expected demand can be met and evaluate alternatives when it cannot. Question 8Which statement about safety stock is most accurate? A. It eliminates the need for accurate inventory records. B. It protects against uncertainty but can conceal process problems if used excessively. C. It should always be located as close as possible to the final customer. D. It is required only in push systems. Correct Answer: B. It protects against uncertainty but can conceal process problems if used excessively. Question 9A machine breakdown causes a planner to reallocate scarce products among customers. Which governance practice is most appropriate? A. Allow allocation to depend entirely on the largest customer’s latest order. B. Use transparent, predefined allocation rules and document the decision. C. Permit every department to apply its own undisclosed priority rule. D. Ignore contractual and service commitments. Correct Answer: B. Use transparent, predefined allocation rules and document the decision. Question 10Why should AI-based demand recommendations be reviewed by planners? A. Algorithms cannot process any historical data. B. Human review is unnecessary when a system produces a numerical forecast. C. Model outputs depend on data, assumptions, and objectives and may fail during structural change. D. AI systems are designed only for strategic facility-location decisions. Correct Answer: C. Model outputs depend on data, assumptions, and objectives and may fail during structural change.
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