Lean, Agile, Resilient and Risk-Aware Supply Chains

Introduction

Contemporary supply chains operate in conditions of persistent uncertainty. Demand changes rapidly, global sourcing creates long and exposed networks, customers expect short delivery times, and disruptions may arise from pandemics, cyberattacks, extreme weather, geopolitical conflict, labour shortages, quality failures or transport interruptions. Cost efficiency remains important, but efficiency without adaptability can create fragility. A supply chain with minimal inventory, a single source and highly specialised capacity may perform well in stable conditions yet fail severely when assumptions change.

This chapter examines four complementary perspectives: lean, agile, resilient and risk-aware supply-chain management. Lean seeks to remove activities that do not create customer value. Agility develops the ability to respond rapidly to volatile demand and variety. Resilience concerns the capacity to prepare for, absorb, recover from and adapt to disruption. Risk-aware management makes uncertainty visible and incorporates risk into sourcing, planning, investment and governance decisions.

These perspectives should not be treated as mutually exclusive slogans. A lean system may support resilience by reducing complexity, but excessive inventory reduction may also weaken resilience. Agility may require postponement and flexible capacity, while resilience may require redundancy. The managerial task is therefore to design an appropriate balance between efficiency, responsiveness and protection.

Learning Objectives

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

1. Explain the principles and strategic roles of lean, agile, resilient and risk-aware supply chains.
2. Construct and interpret a value-stream map.
3. Identify the eight major forms of waste and select suitable reduction methods.
4. Apply the Theory of Constraints to a supply-chain bottleneck.
5. Identify, assess and prioritise supply-chain risks using risk registers and FMEA.
6. Evaluate supplier risk, visibility, redundancy, postponement and continuity options.
7. Design an appropriate response to a major supply disruption.
8. Critically assess the trade-offs among cost, speed, flexibility, resilience and sustainability.

1. Four Complementary Supply-Chain Logics

Lean supply chains

Lean management originated in the Toyota Production System and is associated with the elimination of waste, flow, pull, standardised work, built-in quality and continuous improvement. “Value” is defined from the customer’s perspective: an activity is value-adding when it transforms the product or service in a way the customer requires and is willing to recognise. Necessary non-value-adding activities, such as regulatory inspection, may be unavoidable but should still be controlled.

The traditional eight wastes are:

Lean does not mean simply “holding little inventory.” It means designing a stable, capable and visibly controlled process. Inventory may conceal defects, unreliable suppliers and imbalanced capacity. Reducing it without correcting underlying problems can make performance worse.

Agile supply chains

Agility is the ability to sense market changes and respond rapidly, economically and accurately. Agile supply chains are particularly valuable when demand is volatile, product life cycles are short, product variety is high and forecast error is significant. They use flexible processes, rapid information flows, modular products, postponement, cross-trained employees, responsive suppliers and short decision cycles.

Lean and agile are sometimes contrasted as efficiency versus responsiveness. In practice, they can be combined. Stable, high-volume upstream operations may be lean, while downstream configuration and distribution are agile. The point at which a generic product becomes customer-specific is called the decoupling point or order penetration point. Moving this point downstream through postponement can reduce finished-goods variety while preserving response speed.

Resilient supply chains

Resilience is the capability of a supply chain to maintain or restore an acceptable level of performance after disruption and to improve its future capability through learning. It has four broad stages:

1. Prepare: identify vulnerabilities, establish controls and develop continuity plans.
2. Absorb: sustain critical operations during the disturbance.
3. Recover: restore capacity, service and quality.
4. Adapt: redesign the network so that similar events cause less damage.

Resilience is multidimensional. It may concern time to recover, service continuity, financial survival, employee safety, information integrity, regulatory compliance and reputational protection. A resilient design may use multiple suppliers, alternate transport routes, strategic inventory, flexible manufacturing, reciprocal capacity agreements, local sourcing or modular products. Each option has a cost and may create new risks.

Risk-aware supply chains

Risk-aware management integrates risk into everyday decisions rather than treating it as a specialist compliance exercise. Supply-chain risk includes any uncertain event or condition that may adversely affect supply, operations, demand, information, finance, compliance, safety or reputation.

A useful distinction is:

• Operational risk: routine variability, such as forecast error, machine failure or late delivery.
• Disruption risk: low-frequency, high-impact events, such as a port closure or major cyberattack.
• Strategic risk: choices concerning network structure, technology, suppliers or business models.
• External or systemic risk: events transmitted across many firms, such as war, financial crisis or climate events.

Risk management should also recognise opportunities. Flexible capacity, better visibility and supplier collaboration can reduce downside exposure while creating faster service and innovation.

2. Strategic Design: Balancing Efficiency and Protection

Supply-chain design is a portfolio decision. A low-cost design may concentrate purchases in one geographic region, use large batches and minimise buffer inventory. A more resilient design may duplicate tooling, qualify a second supplier, maintain emergency stock or pay for alternative transport. Neither design is universally superior.

The correct choice depends on product criticality, disruption probability, disruption impact, recovery time, customer tolerance and the cost of mitigation. A useful managerial question is not “How do we eliminate all risk?” but “Which risks are unacceptable, which can be tolerated, and which controls provide proportionate value?”

The following design levers are especially important:

• Visibility: timely, reliable information about inventory, orders, capacity, quality, location and risk.
• Redundancy: additional suppliers, capacity, stock, routes or information systems.
• Flexibility: the ability to change volume, mix, sequence, supplier or transport mode.
• Modularity: common components and postponement that permit late configuration.
• Collaboration: shared forecasts, joint problem solving, capacity information and coordinated recovery.
• Segmentation: differentiated policies for strategic, bottleneck, leverage and routine items.
• Governance: clear decision rights, escalation rules, audit controls and ethical standards.

Redundancy and flexibility are not identical. A second supplier provides redundancy; a plant capable of producing several products provides flexibility. Visibility also does not automatically create resilience. Information must be accurate, interpreted and connected to authority for action.

3. Value-Stream Mapping and Flow Improvement

A value-stream map (VSM) represents the flow of materials and information required to deliver a product or service. It normally shows customer demand, suppliers, production or service steps, inventory points, information signals, transport, process times and lead times. The purpose is not to draw every detail but to reveal the total system and identify queues, rework, batching and interruptions.

A typical VSM study follows these steps:

1. Select a product family or service family with a common process.
2. Define the customer, scope and demand period.
3. Walk the process and collect actual observations rather than relying only on standard data.
4. Record cycle time, changeover time, uptime, queue or inventory, staffing, defects and information triggers.
5. Draw the current state.
6. Identify constraints and waste.
7. Design a future state using pull, flow, workload balancing, quality at source and appropriate controls.
8. Develop an implementation plan with owners, measures and review dates.

Key VSM measures

Takt time is the available production time divided by customer demand during the same period:

Available production time excludes planned breaks and other excluded periods. Both quantities must refer to the same time unit and demand horizon. Takt time is a demand pace, not the actual cycle time. To meet demand reliably, the effective process capacity must be at least the required pace, with allowance for losses and variability.

Lead time is the elapsed time from release or order initiation to delivery. Value-added time is the time spent transforming the product or service in a way the customer requires. A simple process-flow efficiency measure is:

This ratio is descriptive, not a universal productivity law. It should not be maximised by eliminating necessary controls or customer service activities.

Worked example: interpreting flow

A warehouse order has a total elapsed time of 8 hours. Picking, packing and labelling that directly transform the order account for 36 minutes. Therefore:

The low percentage does not prove that every remaining minute is waste; some time may be required for safety, verification or transport. It does, however, indicate that queues and waiting deserve investigation.

A future-state map might introduce a supermarket pull system, standard work, electronic order release, smaller batch sizes and a quality-at-source check. These changes should be tested against actual constraints and not implemented merely because they are fashionable.

Figure: A simplified value-stream map showing material flow, information flow and inventory queues.

4. Theory of Constraints and Bottleneck Management

The Theory of Constraints (TOC) views the system as being limited by at least one constraint. Improving a non-constraint may produce local efficiency but not improve total throughput. The five focusing steps are:

1. Identify the system constraint.
2. Exploit it by using existing capacity effectively, for example by reducing downtime and ensuring that it is never starved by poor scheduling.
3. Subordinate other activities to the constraint’s requirements.
4. Elevate the constraint through additional shifts, equipment, outsourcing or redesign.
5. When the constraint moves, return to step one and prevent inertia from becoming the new constraint.

TOC encourages managers to distinguish local utilisation from system performance. A non-bottleneck operating at 100% may create excess work-in-process and lengthen lead time. A constraint should receive priority for maintenance, quality support and schedule protection.

At a basic level, throughput is limited by the capacity of the bottleneck. If a process has capacities of 100, 80 and 120 units per day in sequence, the maximum steady-state throughput is 80 units per day, assuming compatible flows and no other losses. Increasing the 120-unit operation to 150 units does not raise system throughput until the 80-unit constraint is addressed.

5. Risk Identification and Assessment

Risk identification should use several perspectives because no single workshop reveals the whole exposure. Useful methods include process mapping, supplier-site visits, historical loss analysis, scenario analysis, interviews, audits, hazard analysis, contract review, cyber assessment and external intelligence.

A risk register normally records the risk event, cause, consequence, owner, existing controls, indicators, response, due date and residual exposure. Causes and events should be distinguished. For example:

• Cause: dependence on one qualified semiconductor supplier.
• Event: supplier plant becomes unavailable.
• Consequence: production stops and customer orders are delayed.

This distinction improves the selection of controls.

Probability–impact assessment

A qualitative matrix ranks likelihood and consequence. It is useful for prioritisation but can create false precision if scales are poorly defined. A “high” rating should have an explicit meaning, such as a specified frequency range or service impact. Risks with low probability but catastrophic consequences should not be ignored merely because their product score is moderate.

Where data are available, expected loss can be estimated as:

Probability is dimensionless and consequence must be expressed in a consistent monetary unit. This is an expected-value measure, not a prediction of the actual loss in a particular year. It is inadequate by itself for safety, legal or existential risks, where consequences may not be appropriately monetised.

Failure Mode and Effects Analysis (FMEA)

FMEA examines possible failure modes, their effects, causes and controls. Traditional FMEA commonly scores:

• Severity (S): seriousness of the effect if failure occurs.
• Occurrence (O): likelihood or frequency of the cause or failure.
• Detection (D): likelihood that existing controls will fail to detect the problem before impact. A high score normally means poor detectability.

The Risk Priority Number is:

The scores are ordinal rankings, often on a 1–10 scale. Thus, RPN is a prioritisation aid rather than a probability measure. A high-severity failure should receive attention even if its RPN is not the highest. Organisations should document scoring definitions and review the residual risk after controls are implemented.

Worked FMEA example

Suppose a cold-chain distributor assesses a refrigeration failure:

Possible controls include redundant refrigeration, calibrated sensors, alarm escalation, emergency transfer capacity and documented product-disposition rules. After controls, the scores must be reassessed rather than assuming that the risk has disappeared.

6. Supplier-Risk Assessment

Supplier risk extends beyond purchase price. Assessment should consider financial stability, capacity, quality capability, process technology, location, labour practices, cyber controls, environmental exposure, logistics dependence, intellectual-property protection, regulatory compliance and the supplier’s own critical sub-tier suppliers.

A practical supplier assessment combines three methods:

1. Prequalification: verify capability, certifications, financial and ethical requirements before approval.
2. Ongoing monitoring: track delivery, defects, responsiveness, capacity, incidents and leading indicators.
3. Contingency validation: test whether alternate sources, tooling, specifications and logistics routes actually work.

Supplier segmentation helps allocate effort. Strategic suppliers may require joint business continuity plans and executive governance. Bottleneck suppliers require exposure reduction and technical alternatives. Leverage suppliers may be managed through competition and negotiation. Routine suppliers should be simplified through catalogues, automation and standard terms.

Supplier diversification is not automatically beneficial. Two suppliers may share the same sub-tier source, port, region or cyber vulnerability. Effective diversification requires independence of failure, not simply two names in a database. Dual sourcing may also reduce economies of scale and weaken supplier commitment. The appropriate policy depends on criticality and total risk-adjusted cost.

7. Continuity Planning and Disruption Response

A business continuity plan identifies critical products and processes, minimum acceptable service levels, dependencies, recovery priorities, communication channels, decision authority and alternative operating arrangements. A disaster-recovery plan is often narrower, focusing on restoration of facilities, technology or data.

Two useful time measures are:

• Recovery Time Objective (RTO): maximum acceptable time to restore a function after disruption.
• Recovery Point Objective (RPO): maximum acceptable amount of data loss, expressed as time between the last recoverable data point and the disruption.

A continuity plan should specify triggers rather than relying on improvisation. For example, a supplier’s confirmed inability to ship for 72 hours may trigger allocation rules, alternate transport and customer communication.

A disruption-response cycle is:

1. Detect and verify the event.
2. Protect people, product, data and regulatory compliance.
3. Establish a cross-functional incident team.
4. Estimate the impact on supply, demand, inventory, capacity and cash.
5. Prioritise critical customers and products using transparent rules.
6. Activate alternatives, such as substitute materials, alternate suppliers, routes or facilities.
7. Communicate internally and externally without speculation or concealment.
8. Monitor recovery and revise decisions as evidence changes.
9. Conduct a post-incident review and implement corrective action.

Allocation decisions require ethical discipline. Critical medical or safety-related products may appropriately receive priority, but criteria should be defined before a crisis where possible. Firms should avoid exploiting scarcity through unfair pricing, misrepresenting availability or shifting undisclosed risks to vulnerable suppliers and communities.

8. Visibility, Digital Systems and Artificial Intelligence

Visibility is the ability to know what is happening across relevant supply-chain tiers and to act on that knowledge. It may include order status, inventory position, shipment location, capacity, quality events, temperature, supplier financial health and external hazards. Visibility should be designed around decisions: what information is needed, by whom, at what frequency and with what response authority?

Digital technologies may support this objective:

• Enterprise resource planning systems integrate transactions.
• Warehouse and transport systems provide operational status.
• Internet-of-Things sensors monitor location, temperature and condition.
• Control towers aggregate events and exceptions.
• Digital twins support scenario analysis.
• Artificial intelligence can improve forecasting, anomaly detection, route planning and supplier-risk monitoring.

Technology does not cure poor master data, unclear ownership or weak processes. AI outputs can reproduce biased historical decisions, generate false alarms or conceal uncertainty behind a confident score. Governance should therefore include data lineage, human review for high-impact decisions, cybersecurity, access control, model validation, explainability appropriate to the use case and monitoring for drift. Suppliers and employees should not be subjected to opaque automated decisions without a fair escalation path.

9. Integrated Performance Measurement

A balanced measurement system prevents local optimisation. Useful measures include:

No single metric is sufficient. Inventory turns may improve while stockouts increase. Utilisation may rise while lead time becomes unacceptable. A risk dashboard should distinguish leading indicators, such as supplier financial deterioration or overdue maintenance, from lagging indicators, such as missed deliveries and customer complaints.

10. Illustrative Case: Medical Device Component Disruption

Background

MedEquip, a fictional medical-device manufacturer, produces diagnostic monitors using a specialised sensor purchased from one overseas supplier. The sensor is technically approved and difficult to substitute. The company adopted lean purchasing and reduced safety stock to three days because the supplier historically delivered reliably.

Problem

A regional earthquake damages the supplier’s plant and interrupts power and transport. The supplier estimates that shipments will stop for four weeks. MedEquip has only three days of stock, and a substitute sensor would require regulatory validation. Hospital customers rely on the monitors for critical care.

Analysis

The event exposes several interacting risks: single-source dependence, long replenishment lead time, limited visibility into the supplier’s facility and sub-tier components, regulatory lock-in and insufficient strategic inventory. A simple expected-loss calculation would not capture the full ethical and safety consequences. FMEA would likely assign very high severity, even if occurrence had previously been judged low.

The response team maps available stock by product priority, confirms exact inventory and work-in-process, contacts the supplier and its logistics providers, and investigates whether undamaged stock exists at distributors. It also checks whether the supplier can produce partial quantities at an alternate site. Legal, quality and regulatory teams assess permitted substitutions and temporary approvals.

Approach and solution

Immediate actions include:

• allocating sensors to life-critical orders using documented criteria;
• freezing non-essential production and protecting remaining stock;
• obtaining verified inventory from distributors and the supplier’s alternate facility;
• using expedited transport where it materially improves recovery;
• communicating realistic delivery dates to hospitals;
• beginning an emergency validation programme for a second sensor source.

Medium-term actions include qualifying a second supplier, retaining duplicate tooling, increasing strategic stock for the sensor, developing a regional contract manufacturer and improving tier-two visibility. The company also revises its supplier scorecard to include business continuity evidence, recovery time, geographic concentration and sub-tier exposure.

Outcome

MedEquip maintains supply to the most critical hospitals, although lower-priority deliveries are delayed. The organisation incurs additional logistics and validation costs but avoids an uncontrolled shutdown. After the event, it adopts differentiated inventory policies: ordinary components remain lean, while the high-severity bottleneck sensor receives a risk-based buffer and tested alternatives.

Learning points

The case demonstrates that lean inventory is not inherently resilient. Criticality, substitutability and recovery time must shape inventory and sourcing decisions. A second supplier is valuable only if it is qualified, independent and capable during the same disruption. Ethical allocation, regulatory discipline and truthful communication are central to continuity management, not optional public-relations activities.

11. Challenges and Limitations

First, lean initiatives may transfer rather than remove waste, for example by reducing a buyer’s inventory while increasing supplier expediting. The unit of analysis should therefore be the end-to-end value stream.

Second, resilience investments compete for capital with visible short-term cost reductions. Their value may appear only when a disruption occurs, making them vulnerable to budget cuts. Scenario analysis and board-level risk appetite can make the trade-off explicit.

Third, risk assessments are affected by incomplete data, optimism bias, anchoring and political pressure. Workshops should include independent challenge and evidence-based scoring.

Fourth, visibility can create surveillance and privacy concerns. Data sharing must be proportionate, secure and governed by contractual and ethical rules.

Fifth, global networks may reduce cost but increase exposure to carbon regulation, human-rights violations and climate hazards. Resilience should not be achieved by transferring environmental or social harm to less powerful stakeholders.

12. Best-Practice Implementation Roadmap

An organisation can integrate the four approaches through the following sequence:

1. Define customer-critical outcomes, risk appetite and strategic priorities.
2. Map major value streams and network dependencies.
3. Identify constraints, waste, single points of failure and high-severity risks.
4. Segment products, suppliers and processes by value and criticality.
5. Establish baseline measures for service, cost, flow, quality and resilience.
6. Improve stability through standard work, quality at source and reliable data.
7. Introduce pull and flow where demand and processes are sufficiently stable.
8. Add agility through postponement, modularity, flexible capacity and rapid information.
9. Build resilience through tested alternatives, appropriate buffers and continuity plans.
10. Exercise the plans, audit controls and learn from incidents and near misses.
11. Review trade-offs at executive level and update the network as conditions change.

The strongest programmes treat improvement as a management system rather than a collection of isolated tools. Leaders must align incentives, invest in capability, involve suppliers and frontline employees, and reward prevention as well as short-term output.

Chapter Summary

Lean supply chains focus on customer value, flow and waste reduction; agile supply chains emphasise rapid sensing and response; resilient supply chains prepare for, absorb, recover from and adapt to disruption; and risk-aware supply chains incorporate uncertainty into decisions and governance. These approaches are complementary but involve trade-offs.

Value-stream mapping reveals material and information flows, queues and non-value-adding time. Takt time connects available capacity with demand, while process cycle efficiency provides a descriptive view of value-added time relative to lead time. The Theory of Constraints directs attention to the system bottleneck rather than local utilisation.

Risk management requires clear separation of causes, events and consequences. Risk registers, probability–impact analysis and FMEA provide structured prioritisation, but numerical scores must not replace judgement, especially for safety-critical or catastrophic risks. Supplier assessment must include sub-tier exposure, geographic concentration, financial health, continuity capability and ethical performance.

Resilience is strengthened through visibility, flexibility, redundancy, postponement, strategic inventory, alternate routes, tested continuity plans and effective disruption governance. Digital systems and AI can improve detection and decision support, but they require reliable data, human oversight, cybersecurity and accountability. Ultimately, supply-chain excellence means achieving an appropriate balance among efficiency, responsiveness, continuity, sustainability and stakeholder responsibility.

Key Terms

Lean supply chain: A supply chain designed to maximise customer value while reducing waste and instability.

Agile supply chain: A supply chain capable of sensing and responding rapidly to volatile demand and variety.

Resilience: The ability to prepare for, absorb, recover from and adapt to disruption.

Risk-aware management: Decision-making that explicitly incorporates uncertainty, exposure and controls.

Value: The product or service attributes the customer requires and recognises.

Value-stream mapping: A visual representation of material and information flows across a value stream.

Takt time: Available production time divided by customer demand over the same period.

Lead time: Elapsed time from process initiation or order release to completion or delivery.

Process cycle efficiency: Value-added time divided by total lead time, expressed as a percentage.

Waste: Resource consumption that does not create customer value.

Theory of Constraints: An approach that improves system performance by managing its limiting constraint.

Bottleneck: A resource or activity that restricts total system throughput.

Postponement: Delaying final configuration or commitment until demand information is more certain.

Visibility: The ability to obtain and use timely information about supply-chain conditions.

Redundancy: Additional sources, capacity, stock, routes or systems intended to reduce vulnerability.

FMEA: Failure Mode and Effects Analysis, a structured method for examining potential failures and controls.

Risk Priority Number: The product of severity, occurrence and detection scores in traditional FMEA.

Recovery Time Objective: The maximum acceptable time to restore a function after disruption.

Recovery Point Objective: The maximum acceptable data-loss interval after a disruption.

Control tower: A technology-enabled coordination capability that aggregates information and manages exceptions.

Review Questions

Short Answer Questions

1. What is the principal difference between lean and agile supply-chain objectives?
2. List the five focusing steps of the Theory of Constraints.
3. Define takt time and state the units that must be consistent when calculating it.
4. What do severity, occurrence and detection represent in FMEA?
5. Distinguish a Recovery Time Objective from a Recovery Point Objective.

Long Answer Questions

1. Explain how a firm can combine lean and agile principles across different stages of the same supply chain.
2. Describe the process of constructing a value-stream map and explain how it supports improvement decisions.
3. Critically evaluate supplier diversification as a resilience strategy, including its benefits and limitations.
4. Explain how visibility, redundancy and flexibility contribute differently to supply-chain resilience.
5. Discuss the ethical, governance and data-quality issues involved in using AI for supply-chain risk management.

Analytical / Application Questions

1. A process has 420 available minutes per day and customer demand of 140 units per day. Calculate takt time and explain what it implies for process capacity.
2. A firm’s FMEA scores for a failure are S = 8, O = 5 and D = 6. Calculate the RPN, then explain why the score should not be used as the sole basis for prioritisation.
3. Design a continuity response for a single-source component whose supplier has announced a probable six-week shutdown. Identify immediate actions, medium-term controls, ethical considerations and measures of recovery.

Multiple Choice Questions with Answers

Question 1

Which statement best describes a resilient supply chain?

A. It minimises inventory regardless of disruption exposure.

B. It prepares for, absorbs, recovers from and adapts to disruption.

C. It uses only domestic suppliers.

D. It maximises utilisation at every individual facility.

Correct Answer: B. It prepares for, absorbs, recovers from and adapts to disruption.

Question 2

A process has 480 available minutes per day and demand is 160 units per day. What is the takt time?

A. 2 minutes per unit

B. 3 minutes per unit

C. 160 minutes per unit

D. 640 minutes per unit

Correct Answer: B. 3 minutes per unit

Question 3

Which activity is an example of overproduction waste?

A. Producing goods before customer demand exists

B. Correcting a defective shipment

C. Walking to retrieve a tool

D. Waiting for a quality approval

Correct Answer: A. Producing goods before customer demand exists

Question 4

In the Theory of Constraints, what should generally occur immediately after identifying the constraint?

A. Subordinate the constraint to all non-bottlenecks

B. Exploit the constraint using existing resources effectively

C. Replace every supplier

D. Increase inventory everywhere

Correct Answer: B. Exploit the constraint using existing resources effectively

Question 5

In traditional FMEA, the Risk Priority Number is calculated as:

A. S + O + D

B. S × O × D

C. S ÷ O × D

D. O − S + D

Correct Answer: B. S × O × D

Question 6

What does a high detection score normally indicate in FMEA?

A. The failure is easy to detect before impact

B. The failure has low severity

C. Existing controls are poor at detecting the failure

D. The failure occurs frequently

Correct Answer: C. Existing controls are poor at detecting the failure

Question 7

Which statement about supplier diversification is most accurate?

A. Two suppliers always eliminate supply risk.

B. Diversification is effective only when suppliers are independent in relevant ways.

C. Diversification is unnecessary for critical components.

D. Diversification always reduces total cost.

Correct Answer: B. Diversification is effective only when suppliers are independent in relevant ways.

Question 8

A product has 36 minutes of value-added time and an 8-hour total lead time. What is its process cycle efficiency?

A. 4.5%

B. 7.5%

C. 13.3%

D. 36%

Correct Answer: B. 7.5%

Question 9

What is the principal purpose of postponement?

A. To increase finished-goods variety held in stock

B. To delay final configuration until demand is better known

C. To eliminate all supplier relationships

D. To maximise batch size at the beginning of production

Correct Answer: B. To delay final configuration until demand is better known

Question 10

Which measure states the maximum acceptable time for restoring a disrupted function?

A. Recovery Point Objective

B. Takt time

C. Recovery Time Objective

D. Process cycle efficiency

Correct Answer: C. Recovery Time Objective