7. Inventory and Materials Management

Introduction and Context

Inventory is one of the most consequential assets in a supply chain. It enables production and customer service, protects operations against uncertainty, and permits firms to exploit purchasing and transportation economies. At the same time, inventory ties up working capital, occupies space, becomes obsolete, incurs handling and insurance costs, and can conceal problems such as poor quality, unreliable suppliers, inaccurate forecasts, and weak process discipline. Inventory and materials management is therefore not the simple act of “keeping enough stock.” It is the managerial discipline of deciding what materials should be held, in what quantities, at which locations, and at what time, while balancing cost, availability, risk, and strategic priorities.

The issue is particularly important in logistics because inventory decisions connect procurement, production, warehousing, transportation, sales, finance, and customer service. A purchasing department may seek large orders to obtain discounts, while finance prefers lower working capital. Operations may want buffers against machine failure, whereas warehousing faces space constraints. Marketing may promise rapid delivery, while suppliers have long and uncertain lead times. Effective management integrates these competing perspectives rather than optimizing one function in isolation.

Inventory decisions also differ according to the nature of demand. Independent demand arises from external customers and must generally be forecast. Dependent demand is derived from the requirements of another item, as in components required for a finished product, and can often be calculated through a bill of materials. Some items are inexpensive but numerous; others are costly, critical, or highly regulated. A useful system consequently combines classification, quantitative models, managerial judgement, and digital information.

Learning Objectives

After studying this chapter, the reader should be able to:

1. Explain the strategic and operational role of inventory and materials management.

2. Distinguish major inventory types, demand patterns, and inventory costs.

3. Apply ABC and related classification methods to prioritize control.

4. Calculate economic order quantity, reorder point, safety stock, and periodic-review levels.

5. Interpret service levels and manage demand and lead-time uncertainty.

6. Evaluate quantity discounts, single-period decisions, and multi-echelon inventory policies.

7. Diagnose practical inventory problems and recommend balanced solutions.

8. Assess the contribution of information systems, analytics, automation, and AI.

9. Recognize ethical, governance, sustainability, and implementation issues in inventory decisions.

The Inventory Decision: Availability versus Commitment of Capital

Inventory may be viewed as a stock of materials, components, work in process, finished goods, spare parts, supplies, or returned items held for future use or sale. The central decision is not to minimize inventory absolutely, but to determine an economically and strategically appropriate level.

The principal categories are raw materials and purchased components, work-in-process inventory, finished-goods inventory, maintenance-repair-operating supplies, and goods in transit. Pipeline inventory is stock moving between locations. Anticipation inventory is built before a predictable seasonal peak, promotion, strike, or price increase. Cycle stock results from ordering or producing in batches. Safety stock protects against uncertainty. Decoupling stock separates processes so that disruption in one operation does not immediately stop another.

Inventory creates several forms of value. It permits production and sales to continue despite timing differences between supply and demand. It consolidates purchases and transportation, supports product variety, and can protect against supplier disruption. However, excessive inventory creates a carrying burden. The relevant costs include:

• Purchase or production cost: the price paid for an item or the variable cost of making it.
• Ordering or setup cost: administrative processing, receiving, inspection, transportation coordination, and production changeover costs.
• Holding or carrying cost: capital, storage, insurance, deterioration, taxes, handling, and obsolescence.
• Shortage cost: lost contribution, expediting, production interruption, penalties, customer dissatisfaction, and reputational damage.
• Disposal and recovery cost: costs associated with obsolete, damaged, expired, or returned stock.

A sound analysis must also distinguish inventory accuracy from physical inventory. A warehouse may contain adequate units physically while the information system shows a different quantity or location. Conversely, a high recorded balance may conceal unusable, damaged, expired, or quarantined material. Inventory management therefore depends on both physical control and information integrity.

Classification Before Calculation

No organization should manage every stock-keeping unit (SKU) in the same manner. Classification directs managerial attention toward the items that matter most, although “importance” can be defined in several ways.

ABC analysis

ABC analysis ranks items according to annual usage value:

Annual usage value = Annual demand × Unit cost

Items are then ordered from highest to lowest usage value and grouped into classes. A typical policy may place a relatively small proportion of items in Class A but assign them a large share of total value; Class B items receive intermediate control; Class C items are numerous but account for a relatively small value. The exact percentages are not universal and should be derived from the organization’s data rather than treated as a rule.

A-items normally justify accurate records, frequent review, supplier collaboration, executive attention, cycle counting, and close forecasting. C-items may be controlled through simple reorder systems, two-bin methods, standardization, or larger order quantities. ABC analysis is a prioritization method, not a statement that C-items are unimportant. A low-cost safety-critical bearing, medical component, or regulatory item may deserve A-level control despite low annual usage value.

Multi-criteria classification

Annual value alone can mislead. A practical classification may add criticality, lead time, substitutability, supply risk, shelf life, demand variability, and environmental or regulatory consequences. A criticality matrix, for example, may identify items that are low in value but capable of stopping a production line. Combining ABC with criticality produces policies such as “A-critical,” “C-critical,” or “A-noncritical.”

Other useful classifications include XYZ analysis by demand variability, VED analysis by vital, essential, and desirable status, and FSN analysis by fast-, slow-, and non-moving behavior. These methods should complement rather than mechanically replace managerial assessment. A slow-moving item may be obsolete, but it may also be an essential emergency spare.

Materials requirements and bills of material

For dependent-demand items, the bill of materials (BOM) specifies the components and quantities required for a finished product. Material requirements planning (MRP) combines the master production schedule, BOM, inventory records, scheduled receipts, and lead times to calculate net requirements and planned orders. This is fundamentally different from forecasting each component independently. Errors in the production schedule, BOM, inventory records, or lead-time assumptions can nevertheless propagate through the MRP system.

Quantitative Models for Replenishment

Quantitative models provide disciplined starting points, but their outputs are only as reliable as their assumptions and data. The most familiar model is the economic order quantity.

Economic order quantity

The basic EOQ model assumes relatively stable annual demand, constant ordering cost, constant unit price, instantaneous replenishment, and no shortages. Under these assumptions:

EOQ = √(2DS / H)

where D is annual demand, S is ordering cost per order, and H is annual holding cost per unit. If holding cost is expressed as a percentage i of unit price C, then H = iC.

The logic is a trade-off. Larger orders reduce the number of orders and therefore ordering cost, but increase average cycle stock and holding cost. Smaller orders do the opposite. Under the basic assumptions, average cycle inventory is EOQ/2, annual ordering cost is (D/EOQ)S, and annual holding cost is (EOQ/2)H. At EOQ these two variable costs are approximately equal.

Illustrative example. Suppose annual demand is 12,000 units, ordering cost is $75 per order, and annual holding cost is $3 per unit. EOQ is approximately 775 units:

EOQ = √[(2 × 12,000 × 75) / 3] ≈ 775 units.

The firm would place about 15.5 orders per year, subject to practical rounding and supplier constraints. EOQ does not determine when to order; that is the role of the reorder point. Nor does it automatically account for capacity, minimum order quantities, quantity discounts, or uncertainty.

Reorder point and lead time

For known demand and constant lead time, the reorder point is:

ROP = Demand during lead time

If daily demand is d and lead time is L days, ROP = dL. For example, daily demand of 40 units and a lead time of five days produce a reorder point of 200 units. When the inventory position reaches 200 units, an order is released.

Inventory position is generally calculated as on-hand inventory plus on-order inventory minus backorders. Using on-hand inventory alone can lead to duplicate ordering when outstanding orders are ignored.

Safety stock under uncertainty

Demand, lead time, or both may vary. Safety stock provides protection against that uncertainty. If demand during lead time is approximately normally distributed and lead time is constant, a common formulation is:

ROP = Average demand during lead time + Safety stock

Safety stock = z × σDL

where z is the standard normal factor associated with the desired cycle service level and σDL is the standard deviation of demand during lead time. For example, a 95 percent cycle service level uses a z-value of approximately 1.65, assuming the normal approximation is appropriate.

When daily demand varies but lead time is constant, the standard deviation of lead-time demand is approximately √L times the standard deviation of daily demand. When both demand and lead time vary, a widely used approximation is:

σDL = √(Lσd² + d²σL²)

where d and L are average daily demand and average lead time, and σd and σL are their standard deviations. If both variables are materially variable and correlated, the covariance term should be considered rather than ignored.

Safety stock is not free protection. Increasing the target service level raises the required safety stock disproportionately near very high service levels. Management should therefore compare the marginal carrying cost of additional stock with the marginal cost of shortages, lost sales, disruption, and customer dissatisfaction.

Service-level measures

A cycle service level is the probability of not experiencing a stockout during a replenishment cycle. Fill rate is the proportion of total demand immediately supplied from stock. These measures are related but not identical. A system can avoid stockouts in most cycles while still having a poor fill rate if occasional shortages are large. Service targets should therefore be stated precisely and differentiated by item or customer segment.

A high service level may be justified for a production-critical spare or emergency medical item but uneconomic for a low-margin, predictable, readily available product. Service levels should reflect customer promises, item criticality, substitution possibilities, shortage consequences, and total supply-chain cost.

Continuous and Periodic Review Policies

Under a continuous-review or Q-system, inventory position is monitored continuously. A replenishment order of approximately Q units is placed whenever the position reaches the reorder point. This policy responds quickly to demand but requires reliable transaction data and often more intensive monitoring.

Under a periodic-review or P-system, inventory is reviewed at fixed intervals. At each review, an order raises the inventory position to a target or order-up-to level. If the review interval is P and lead time is L, protection is required for approximately P + L time units. A simplified target is:

Order-up-to level = Expected demand during (P + L) + Safety stock for (P + L)

The quantity ordered equals the target level minus the current inventory position. Periodic review can simplify administration and coordinate supplier visits, but it exposes the system to demand during the interval between reviews. Consequently, it commonly requires more safety stock than an equivalent continuous-review system.

The choice depends on item value, transaction technology, supplier schedules, review cost, demand volatility, and operational risk. Hybrid policies are common: high-value items may be reviewed continuously, while low-value consumables are reviewed weekly or monthly.

Quantity Discounts and Total-Cost Reasoning

Suppliers may offer all-units quantity discounts, incremental discounts, freight concessions, or price breaks. A larger order may reduce purchase price but increase holding cost and possibly obsolescence. The decision should compare total annual cost rather than unit price alone:

Total cost = Annual purchase cost + Annual ordering cost + Annual holding cost

For each feasible price bracket, calculate the EOQ using that bracket’s holding cost, adjust it to meet the minimum quantity for the bracket, and compare total costs. An order quantity is not eligible for a discount merely because its calculated EOQ is below the price-break quantity; it must meet the supplier’s stated threshold. The analysis should also test capacity, cash-flow, shelf-life, quality, and demand-risk implications.

Quantity discounts can be strategically valuable when demand is stable, the item is nonperishable, storage is available, and the price reduction is substantial. They are dangerous when purchasing incentives cause speculative buying, hide supplier quality problems, or shift costs from procurement to warehousing and obsolescence.

Single-Period and Perishable-Inventory Decisions

The single-period, or newsvendor, problem applies when inventory has one principal selling opportunity or a sharply limited useful life. Examples include fashion products, newspapers, seasonal merchandise, event catering, and fresh food. The decision balances the cost of ordering too much against the cost of ordering too little.

Let Cu be the underage cost, the consequence of ordering one unit too few, and Co the overage cost, the consequence of ordering one unit too many. The critical ratio is:

Critical ratio = Cu / (Cu + Co)

The optimal order quantity is the demand percentile corresponding to this ratio. A higher underage cost leads to a higher target percentile and therefore a larger order. Salvage value, markdowns, returns, lost goodwill, and environmental disposal should be included in estimating overage cost. Forecast bias is especially damaging in short-life products because there is little opportunity to correct an initial decision.

Multi-Echelon Inventory Management

In a multi-echelon network, inventory is held at several connected levels, such as suppliers, a central distribution centre, regional warehouses, and stores. Managing each location independently can produce excessive total stock because every echelon protects itself against the same uncertainty. Multi-echelon management instead considers the network-wide placement of inventory and the relationship between upstream and downstream policies.

An important concept is echelon inventory, which includes stock at a particular location plus stock held downstream from that location. Echelon reorder policies evaluate the total inventory position across the relevant network. Risk pooling allows centralized inventory to serve multiple markets, often reducing aggregate safety stock when demands are not perfectly correlated. However, centralization may increase transportation time, reduce responsiveness, and create a single point of failure.

Strategic questions include where to hold safety stock, which products should be postponed or configured late, whether a distribution centre should be bypassed, and how service commitments should be allocated across echelons. The right answer depends on demand correlation, lead times, transportation costs, product modularity, customs requirements, and customer proximity.

Materials Management in Practice

Inventory policy succeeds only when supported by disciplined processes. A practical materials-management cycle includes demand and supply planning, item master-data governance, purchasing, receiving, inspection, put-away, storage, issue or shipment, replenishment, counting, reconciliation, and disposition of excess or obsolete stock.

Procurement and logistics managers should establish clear ownership for SKU creation, units of measure, supplier lead times, minimum order quantities, pack sizes, prices, and approved substitutes. Cycle counting is generally more useful than relying exclusively on an annual physical count. Counting frequency can be aligned with ABC or criticality classes, while root-cause analysis should investigate discrepancies rather than merely adjust records.

Useful performance measures include inventory turnover, days of supply, stockout frequency, fill rate, order-line service, forecast error, obsolete inventory percentage, supplier on-time delivery, inventory record accuracy, carrying cost, and cash-to-cash cycle time. No single measure is sufficient. High turnover may result from excellent flow or chronic shortages; a high fill rate may be achieved through excessive stock. Metrics should therefore be interpreted together and segmented by product, location, and customer promise.

Technology, Analytics, and Automation

Enterprise resource planning and warehouse management systems provide transaction visibility, replenishment parameters, purchase-order control, location management, and traceability. Barcode scanning and radio-frequency identification improve the timeliness and accuracy of movements. Automated storage and retrieval systems, pick-to-light technologies, and mobile devices can reduce handling time and errors when volumes justify investment.

Advanced analytics can improve demand forecasting, identify intermittent-demand patterns, detect abnormal consumption, estimate lead-time distributions, and recommend differentiated safety stocks. Machine-learning systems may identify relationships among promotions, weather, prices, events, and demand. Their value depends on data quality, explainability, monitoring, and human accountability. An algorithm trained on stockout-constrained sales may interpret lost demand as low demand and systematically recommend insufficient inventory.

Digital twins and control towers can simulate network disruptions and compare alternative inventory placements. Internet-connected sensors support condition monitoring for temperature-sensitive or high-value materials. Yet technology does not remove the need for sound policies. Automation can accelerate bad master data, incorrect units, or inappropriate reorder points. Governance should include parameter ownership, exception management, access controls, audit trails, cybersecurity, and periodic model validation.

Illustrative Case: Spare Parts at Meridian Rail Components

Background

Meridian Rail Components, a fictional manufacturer of braking assemblies, supplies several railway maintenance depots. Its operations team had experienced frequent emergency purchases despite a reported inventory value of $8 million. Finance argued that stock was excessive, while maintenance managers insisted that critical spares were unavailable when needed.

Situation and analysis

A review found that 4,200 SKUs were managed with the same monthly reorder rule. ABC analysis showed that 11 percent of items represented 72 percent of annual usage value. A separate criticality assessment identified 86 low-demand items capable of stopping a repair line. Inventory records were only 91 percent accurate for A-items, supplier lead times varied substantially, and obsolete items remained in active locations.

The company also measured service only as monthly shipments completed. This masked the operational effect of a shortage of a single critical bearing. Demand for common fasteners was stable, but demand for emergency brake modules was intermittent and highly consequential.

Approach

Meridian introduced differentiated policies. High-value, noncritical items received continuous review and statistically calculated reorder points. Critical spares received management-approved service targets, supplier collaboration, and documented substitutes rather than automatic high quantities. Low-value consumables were placed on two-bin or periodic-review systems. The firm corrected BOMs, standardized units of measure, quarantined unusable stock, and began cycle counting A-items weekly, B-items monthly, and C-items quarterly.

For emergency modules, the team used an intermittent-demand approach and reviewed the cost of shortage against the cost of holding and obsolescence. A central pool was created for selected slow-moving spares, while regional depots retained only items needed for immediate response. Supplier lead-time data were incorporated into safety-stock calculations, and dashboards displayed fill rate, emergency freight, record accuracy, and obsolete inventory together.

Outcome

The changes reduced duplicate local buffers and improved visibility of critical items. Emergency purchases declined, while the company did not pursue an indiscriminate reduction in stock. The principal improvement came from segmentation, data correction, and network coordination rather than from applying EOQ to every SKU.

Learning points

The case illustrates four principles. First, inventory value and operational criticality are different dimensions. Second, service levels must be defined in a way that reflects the customer or production consequence of shortage. Third, inventory reduction requires process and data improvement, not merely lower reorder quantities. Finally, centralization can pool risk but must be balanced against response time and disruption exposure.

Challenges, Risks, and Common Mistakes

One common error is treating EOQ as an exact answer under conditions of highly variable demand, supplier minimums, capacity restrictions, or short product life. Another is calculating safety stock from averages while ignoring demand spikes, lead-time variability, correlation, or forecast bias. Managers also frequently confuse on-hand stock with inventory position, fail to subtract allocated quantities, or overlook goods in transit.

Other risks include forecast-driven overstock, duplicate safety stock across echelons, unauthorized substitutions, inaccurate BOMs, poor item descriptions, hidden obsolete stock, and incentives that reward purchasing price reductions rather than total cost. The bullwhip effect can amplify small demand changes when organizations batch orders, revise forecasts excessively, or lack shared information.

Inventory reduction programs may create operational fragility if they remove protection without addressing unreliable suppliers, long changeovers, poor quality, or unstable schedules. Conversely, excessive safety stock can postpone corrective action by making a weak process appear reliable. Managers should use inventory as a deliberate buffer, not as a substitute for process improvement.

Ethical, Governance, and Sustainability Considerations

Inventory decisions affect more than financial performance. Overstock may lead to waste, unsafe disposal, unnecessary energy use, and environmental harm. Understock of medicines, safety equipment, or essential public-service materials can create serious social consequences. Organizations should establish traceability, expiry controls, recall procedures, segregation of hazardous materials, and compliance with applicable storage and transport regulations.

Procurement staff must manage conflicts of interest, gifts, preferential treatment, and supplier transparency. Quantity discounts should not encourage purchases that exceed legitimate requirements. Data-driven systems should be auditable and should not systematically disadvantage particular suppliers or customers through unexplained allocation rules. Governance also requires clear approval limits for write-offs, emergency buying, and changes to service-level parameters.

Current Developments and Best Practices

Contemporary inventory management is moving toward differentiated, network-wide, and exception-based control. Firms increasingly combine demand sensing with supplier collaboration, postponement, strategic inventory buffers, and scenario planning for disruption. Resilience does not necessarily mean holding maximum stock; it may involve dual sourcing, modular product design, flexible capacity, visibility, and rapid substitution.

Best practice is to:

• segment items by value, variability, criticality, and supply risk;
• define service measures and targets explicitly;
• use EOQ, reorder-point, periodic-review, and single-period models according to the situation;
• calculate total cost rather than optimizing purchase price alone;
• maintain accurate master data and inventory records;
• integrate procurement, operations, finance, sales, and logistics decisions;
• review parameters after changes in demand, lead time, price, or product design;
• treat obsolete and excess inventory as a management issue, not merely a warehouse issue; and
• combine automation and analytics with human oversight and governance.

Chapter Summary

Inventory and materials management balances product availability, operational continuity, capital commitment, and risk. Inventory includes cycle, safety, anticipation, pipeline, work-in-process, finished-goods, and maintenance stock, each serving a different purpose. Costs include purchase, ordering, holding, shortage, and obsolescence costs. ABC analysis prioritizes control by annual usage value, while criticality, variability, and supply risk provide important additional dimensions.

The EOQ model balances ordering and holding costs under simplified assumptions. Reorder points determine when replenishment should occur, while safety stock protects against demand and lead-time uncertainty. Service level must be distinguished from fill rate, and targets should reflect shortage consequences. Periodic-review systems replenish at fixed intervals; quantity-discount decisions require total-cost comparisons; single-period models address perishable or time-sensitive stock. Multi-echelon management coordinates inventory across a network and considers risk pooling and echelon inventory.

Effective practice depends on accurate data, differentiated policies, cycle counting, cross-functional governance, and appropriate technology. Analytics and AI can improve forecasting and parameter setting but cannot compensate for poor data or weak accountability. Sustainable and ethical management requires traceability, responsible disposal, regulatory compliance, and balanced decisions that protect both organizational performance and broader stakeholders.

Key Terms

ABC analysis: Classification of inventory according to annual usage value to prioritize control effort.

Annual usage value: Annual demand multiplied by unit cost.

Carrying cost: The annual cost of holding inventory, including capital, storage, insurance, deterioration, and obsolescence.

Cycle stock: Inventory arising from replenishment or production in batches.

Cycle service level: Probability that no stockout occurs during a replenishment cycle.

Dependent demand: Demand derived from the requirements of another item or production schedule.

Echelon inventory: Inventory at a location plus inventory held downstream from that location.

Economic order quantity: Order quantity that balances ordering and holding costs under specified assumptions.

Fill rate: Proportion of total demand supplied immediately from available stock.

Independent demand: Demand originating from external customers and generally requiring forecasting.

Inventory position: On-hand inventory plus on-order inventory minus backorders or allocations, according to the policy used.

Lead time: Time between placing a replenishment order and receiving usable stock.

Material requirements planning: A system that calculates dependent-material requirements from schedules, bills of material, inventory, and lead times.

Pipeline inventory: Stock currently moving between supply-chain locations.

Periodic-review system: Inventory policy in which stock is reviewed at fixed intervals and replenished to a target level.

Reorder point: Inventory-position level that triggers a replenishment order.

Safety stock: Additional inventory held to protect against demand, supply, or lead-time uncertainty.

Single-period model: Inventory model for a one-time or short-life selling opportunity.

Stock-keeping unit: A uniquely managed item or product variant in an inventory system.

Underage cost: Cost associated with having one unit less than required, including shortage or lost-sales consequences.

Review Questions

Short Answer Questions

1. Distinguish cycle stock from safety stock.

2. What is the purpose of ABC analysis?

3. State the basic EOQ formula and identify its variables.

4. Differentiate cycle service level from fill rate.

5. Why is inventory position more useful than on-hand inventory for replenishment decisions?

Long Answer Questions

1. Explain the major categories of inventory and the costs associated with holding them.

2. Discuss how ABC analysis can be combined with criticality and demand variability to create differentiated policies.

3. Explain the assumptions, logic, and managerial limitations of the EOQ model.

4. Compare continuous-review and periodic-review inventory systems.

5. Discuss the strategic importance of multi-echelon inventory management and risk pooling.

Analytical / Application Questions

1. Annual demand for an item is 18,000 units, ordering cost is $60 per order, and annual holding cost is $2.40 per unit. Calculate EOQ and explain two practical factors that might require adjustment of the result.

2. Daily demand averages 50 units, average lead time is six days, and demand during lead time has a standard deviation of 35 units. Using a z-value of 1.65, calculate the reorder point and explain the service-level meaning of the result.

3. A retailer faces uncertain demand for a seasonal product. The cost of a unit short is $24, while the cost of a leftover unit after markdown or salvage is $8. Calculate the critical ratio and explain how it should influence the order quantity and forecast decision.

22. Multiple Choice Questions with Answers

Question 1

A firm classifies SKUs by annual demand multiplied by unit cost. Which method is being used?

A. ABC analysis

B. VED analysis

C. FSN analysis

D. Newsvendor analysis

Correct Answer: A. ABC analysis

Question 2

Annual demand is 12,000 units, ordering cost is $75, and annual holding cost is $3 per unit. Which order quantity is closest to the basic EOQ?

A. 300 units

B. 550 units

C. 775 units

D. 1,200 units

Correct Answer: C. 775 units

Question 3

When both demand and lead time are uncertain, the principal purpose of safety stock is to:

A. Reduce the supplier’s unit price

B. Protect against uncertainty during replenishment

C. Eliminate the need for forecasting

D. Increase annual ordering cost

Correct Answer: B. Protect against uncertainty during replenishment

Question 4

A continuous-review system normally places an order when:

A. The calendar month ends

B. The inventory position reaches the reorder point

C. The warehouse is completely empty

D. The annual budget is approved

Correct Answer: B. The inventory position reaches the reorder point

Question 5

Which statement best distinguishes fill rate from cycle service level?

A. Fill rate measures order frequency, while cycle service level measures unit cost

B. Fill rate measures the proportion of demand supplied, while cycle service level measures the probability of avoiding a stockout in a cycle

C. They are different names for exactly the same measure

D. Fill rate applies only to suppliers, while cycle service level applies only to customers

Correct Answer: B. Fill rate measures the proportion of demand supplied, while cycle service level measures the probability of avoiding a stockout in a cycle

Question 6

A quantity discount should generally be accepted when:

A. The discounted unit price is lower, regardless of other costs

B. The order meets the discount threshold and produces the lowest feasible total cost after holding and ordering costs

C. The item has highly uncertain demand and a short shelf life

D. The warehouse has no remaining capacity

Correct Answer: B. The order meets the discount threshold and produces the lowest feasible total cost after holding and ordering costs

Question 7

Which situation is most appropriate for a single-period inventory model?

A. A standard component used continuously for ten years

B. A seasonal fashion product with limited selling opportunity

C. A replenishable office supply with stable demand

D. A machine part with a five-year lead time and regular usage

Correct Answer: B. A seasonal fashion product with limited selling opportunity

Question 8

A low-cost item can stop an entire production line if unavailable. What does this illustrate?

A. Annual usage value is the only valid classification criterion

B. Criticality may justify stronger control than ABC value alone suggests

C. Low-cost items should never receive safety stock

D. The item must be classified as obsolete

Correct Answer: B. Criticality may justify stronger control than ABC value alone suggests

Question 9

What is a major benefit of multi-echelon inventory management?

A. It guarantees zero transportation time

B. It allows network-wide consideration of inventory placement and risk pooling

C. It removes the need for service-level decisions

D. It requires every location to hold identical safety stock

Correct Answer: B. It allows network-wide consideration of inventory placement and risk pooling

Question 10

An AI replenishment system is trained on sales data from periods when frequent stockouts occurred. What is a likely risk?

A. It may interpret lost demand as low demand and recommend insufficient inventory

B. It will automatically correct all master-data errors

C. It will eliminate the need for human governance

D. It will always increase inventory turnover without affecting service

Correct Answer: A. It may interpret lost demand as low demand and recommend insufficient inventory