Integrated Cold-Chain Strategy and Applied Capstone

Introduction

Cold-chain performance is not created by refrigeration equipment alone. It emerges from the interaction of product biology, packaging, facilities, transport, information, people, regulation, finance, and environmental conditions. A shipment may leave a plant at the correct temperature and still arrive commercially unacceptable because of loading delays, poor air circulation, inaccurate forecasts, inadequate packaging, customs interruption, or weak exception management.

An integrated cold-chain strategy therefore treats temperature control as a cross-functional system rather than an isolated logistics activity. The central managerial question is not simply, “Was the product cold?” It is: “Did the network preserve the required product attributes, service level, regulatory status, economic value, and environmental performance from source to final customer?”

This chapter provides a capstone framework for answering that question. It combines product requirements, network design, operational controls, financial analysis, regulation, digital technology, sustainability, risk governance, and implementation planning. The illustrative case of NorthStar Biologics demonstrates how these dimensions can be integrated into an evidence-based recommendation.

Learning Objectives

By the end of this chapter, students should be able to:

1. Diagnose cold-chain performance using product, process, financial, regulatory, and sustainability evidence.
2. Distinguish temperature compliance from broader product-quality and service outcomes.
3. Evaluate strategic trade-offs among inventory, transport mode, packaging, facilities, resilience, cost, and emissions.
4. Apply appropriate cold-chain metrics and financial calculations.
5. Design a technology-enabled governance and implementation roadmap.
6. Present a defensible capstone recommendation with explicit assumptions, risks, and controls.

1. The Integrated Cold-Chain System

A cold chain is a temperature-controlled supply network that protects products whose quality, safety, efficacy, or commercial value is sensitive to time and temperature. Product categories include fresh food, frozen food, vaccines, biologics, clinical specimens, pharmaceuticals, flowers, and selected chemicals.

The system has five linked layers:

• Product layer: allowable temperature range, sensitivity to excursions, shelf life, freezing risk, light sensitivity, humidity sensitivity, and packaging requirements.
• Physical layer: farms or factories, pre-cooling, storage rooms, docks, vehicles, containers, airports, ports, and customer facilities.
• Process layer: forecasting, order release, picking, loading, documentation, handoffs, quarantine, release, and disposition.
• Information layer: sensors, event records, chain-of-custody data, forecasts, alerts, dashboards, and master data.
• Governance layer: accountability, standard operating procedures, quality systems, contracts, audits, regulatory controls, and improvement routines.

A useful systems model is:

Figure: An integrated cold chain links product requirements to operational execution, measurable outcomes, and value through information and governance.

Product requirements and quality risk

A temperature range is not a complete product specification. Managers must identify the critical quality attributes (CQAs), such as potency, microbial safety, texture, appearance, viability, or diagnostic accuracy. They must then determine the critical process parameters (CPPs), such as product temperature, ambient temperature, exposure duration, humidity, vibration, light, and handling time.

Temperature excursions should be interpreted using validated stability evidence. A brief deviation may be harmless for one product and unacceptable for another. Conversely, repeated small deviations can accumulate damage even when no single event appears severe. “Within range” is therefore a necessary but not always sufficient condition for quality.

The time-temperature relationship is often represented using cumulative exposure. A simple operational exposure measure is:

where T_i is the observed temperature during interval i, T_ref is a reference temperature, ∆t_i is interval duration, and (x)⁺ = max(x, 0). This index is useful for screening warm exposure but is not a substitute for a validated product-degradation model. It assumes that exposure above the reference temperature is relevant and that a linear approximation is acceptable for the management purpose.

For products with validated kinetics, degradation may be modeled more specifically. A first-order model is:

where C₀ is initial quality or potency, C_t is quality at time t, and k is a temperature-dependent degradation constant. The model is applicable only when first-order behavior and the relevant temperature dependence have been established through appropriate scientific evidence. It must not be invented from sensor data alone.

2. Strategic Design Choices and Trade-offs

Network configuration

A cold-chain network may use centralized distribution, regional cold stores, direct shipment, cross-docking, or a hybrid design. Centralization can increase inventory pooling and reduce duplicated facilities, but it may increase transportation distance and exposure to a single disruption. Regionalization can improve responsiveness and reduce final-mile distance, but it usually requires more inventory, facilities, qualified personnel, and capital.

The choice should be assessed across total landed cost, lead time, service reliability, quality risk, resilience, and emissions. Local optimization—such as selecting the cheapest carrier—can create system-wide cost through spoilage, emergency shipments, claims, or lost customers.

Inventory and service

Perishable inventory has a time-dependent value. A conventional cycle-stock decision is not enough; managers must consider remaining shelf life and the probability of demand before expiry. First-expiry-first-out (FEFO), shelf-life segmentation, dynamic allocation, and near-expiry markdowns may be more appropriate than simple first-in-first-out.

Safety stock protects against demand and supply uncertainty but increases holding cost and potential waste. A basic service-risk relationship is:

where SS is safety stock in units, z is the selected standard-normal service factor, and σ_LT is the standard deviation of demand during lead time. This expression assumes a reasonably stable demand distribution, known lead-time demand variability, and a continuous-review interpretation. If demand and lead-time variability are correlated, or if shelf life is short, a more complete model is required.

Packaging, equipment, and transport mode

Active containers provide powered temperature control but may have high acquisition, positioning, energy, and return costs. Passive packaging uses insulation and phase-change materials, often lowering operational complexity but imposing strict pack-out, conditioning, and duration limits. Dry ice, gel packs, refrigerated vehicles, and thermal blankets each create different risks, including freezing, sublimation, ventilation, or inadequate duration.

Air freight reduces transit time but often increases cost and emissions. Ocean or road transport may be economically and environmentally attractive but requires stronger forecasting, longer-duration packaging, and greater schedule discipline. The correct question is not which mode is universally best, but which mode provides the required product protection at acceptable total cost and risk.

3. Measuring Performance Correctly

A graduate-level diagnosis uses a balanced scorecard rather than a single temperature KPI.

On-time-in-full is commonly calculated as:

The organization must define “on time,” “in full,” order lines, split shipments, and customer acceptance consistently. A high OTIF can conceal poor quality if damaged or temperature-excursed products are counted as successful deliveries.

Spoilage rate can be expressed as:

Financially, expected loss from a failure mode can be estimated as:

This is a screening tool. It assumes probability and consequence are meaningfully estimated and does not capture non-linear effects, reputational damage, regulatory sanctions, or correlated failures unless those are included in the consequence estimate.

Root-cause analysis should combine sensor data with event data. A temperature graph may show when a deviation occurred, but scan records, door openings, loading timestamps, weather, maintenance records, and handoff evidence are needed to explain why it occurred. Useful methods include process mapping, Pareto analysis, fault-tree analysis, five-whys analysis, and failure mode and effects analysis (FMEA).

In FMEA, a risk-priority score is sometimes calculated as:

where S is severity, O is occurrence, and D is detectability, each assigned an agreed ordinal scale. Because ordinal scores are not true interval measurements, the resulting risk-priority number should support discussion rather than determine decisions mechanically. High-severity risks may require action even when their RPN is modest.

4. Financial and Investment Analysis

Cold-chain decisions require life-cycle analysis. Relevant costs include equipment, installation, qualification, energy, labor, maintenance, packaging, transport, inventory, waste, insurance, claims, compliance, and end-of-life disposal. Benefits may include higher service, longer market reach, reduced spoilage, lower emergency freight, improved patient outcomes, and avoided penalties.

Net present value (NPV) is:

where I₀ is initial investment, CF_t is net cash flow in period t, r is the discount rate per period, and n is the number of periods. Cash flows should be incremental, consistently measured, and expressed in the same currency and price basis. NPV greater than zero indicates value creation relative to the selected discount rate, but does not by itself prove operational feasibility.

Worked financial example

A regional cold room requires an initial investment of $600,000. It is expected to generate incremental annual after-tax cash savings of $190,000 for four years, with no residual value. At a 10% discount rate:

The present values are approximately $172,727, $157,025, $142,750, and $129,773. Therefore:

The investment is marginally positive. Management should test sensitivity to energy prices, utilization, spoilage reduction, maintenance, volume growth, and the discount rate. A small positive NPV should not be presented as robust unless it remains positive under plausible downside scenarios.

5. Regulation, Quality, and Governance

Cold chains operate within overlapping legal and contractual systems. Depending on product and jurisdiction, these may include food-safety rules, pharmaceutical distribution requirements, customs and import controls, workplace safety, dangerous-goods rules, environmental requirements, data protection, and customer-specific quality agreements.

A defensible governance system includes:

1. Product requirements: approved temperature ranges, excursion limits, stability evidence, and disposition rules.
2. Qualification and validation: evidence that rooms, vehicles, packaging, routes, software, and procedures perform as intended under representative conditions.
3. Document control: current SOPs, work instructions, forms, training records, and change history.
4. Traceability: lot, serial, shipment, location, custody, and temperature records.
5. Deviation and CAPA: investigation, root cause, corrective action, preventive action, effectiveness review, and escalation.
6. Supplier governance: qualification, contracts, service-level agreements, audits, and performance reviews.
7. Business continuity: backup power, alternate carriers, alternate facilities, emergency communication, and recovery priorities.

The principle of data integrity is as important as data availability. Digital records should be attributable, legible, contemporaneous, original or appropriately preserved, accurate, complete, consistent, enduring, and available. A dashboard that displays attractive averages while suppressing missing data is a governance failure.

Responsibility should be allocated explicitly through a RACI matrix. For example, quality may be accountable for product disposition, operations responsible for execution, IT responsible for system availability, procurement responsible for supplier contracts, and the business owner accountable for economic outcomes. Ambiguous accountability is a leading cause of repeated excursions.

6. Technology, Analytics, and AI

Internet of Things (IoT) sensors can record temperature, humidity, location, shock, light, door status, and battery condition. However, sensor deployment should begin with a decision requirement: what action will follow an alert? Unactionable alerts produce alarm fatigue.

A practical architecture contains:

• calibrated sensors and gateways;
• secure device identity and time synchronization;
• validated data capture and storage;
• event rules and escalation workflows;
• integration with warehouse, transport, quality, and enterprise systems;
• role-based dashboards;
• audit trails and retention controls.

AI can support demand forecasting, route-risk prediction, anomaly detection, predictive maintenance, image-based pallet inspection, and prioritization of investigations. It should not replace validated product knowledge or qualified quality decisions. Models may fail because of concept drift, missing data, biased historical records, cyberattack, or a change in lane, season, packaging, or product mix.

A sound AI control framework requires documented purpose, data lineage, model validation, performance monitoring, human review, explainable escalation logic, access control, and a fallback process. “Black-box optimization” is inappropriate when a shipment may be quarantined, released, or destroyed on the basis of an unexplained recommendation.

7. Sustainability and Resilience

Cold-chain sustainability involves energy, refrigerants, transport, packaging, food or product waste, water, labor, and social effects. Reducing temperature-control energy by raising a set point may be beneficial in one application and harmful in another; product protection remains the boundary condition.

Transport emissions can be estimated using an activity-based approach:

For freight, activity may be tonne-kilometers and the emission factor may be kilograms of CO₂e per tonne-kilometer. The estimate must state whether empty returns, temperature-control energy, warehousing, packaging, and upstream electricity are included. Comparisons are meaningful only when system boundaries are consistent.

Resilience should be designed rather than assumed. Important capabilities include supplier and carrier diversity, validated alternate lanes, inventory positioning, emergency power, cybersecurity, reciprocal agreements, weather monitoring, and rehearsed crisis procedures. Resilience has a cost; the strategic decision is to invest where the consequence of failure justifies the cost.

8. Applied Capstone Case: NorthStar Biologics

Background

NorthStar Biologics distributes a temperature-sensitive injectable from one manufacturing plant to 14 hospitals across a national market. The approved storage range is 2–8 °C. Product value is high, shelf life is 12 months at release, and product disposition after a temperature excursion requires quality review. The network currently uses one central warehouse, a third-party logistics provider (3PL), and a mixture of refrigerated road transport and passive parcel packaging.

Annual volume is 48,000 shipments. Baseline performance is:

• OTIF: 91.5%;
• shipments with at least one temperature alert: 3.8%;
• product discarded or quarantined after logistics events: 1.6% of shipment value;
• average order cycle time: 3.2 days;
• annual cold-chain logistics cost: $4.8 million;
• documented emissions: 1,950 tonnes CO₂e per year;
• 27% of deliveries pass through a single airport gateway.

Hospital customers report late deliveries and inconsistent remaining shelf life. The quality department reports that investigations are slow because sensor data, carrier scans, and warehouse records are not integrated.

Problem definition

The apparent problem is temperature performance, but the evidence indicates a broader service and governance problem. Late deliveries create additional exposure and reduce usable shelf life. Reliance on one gateway creates concentration risk. Incomplete data increases investigation time and may cause unnecessary product quarantine. The case therefore requires a multi-objective solution, not simply more refrigeration.

Diagnostic approach

The capstone team should begin by validating the baseline. It should reconcile shipment counts, define an alert, distinguish true excursions from sensor or handling anomalies, and segment performance by lane, carrier, product lot, packaging configuration, season, and customer.

A likely analytical sequence is:

1. Map the end-to-end process, including all custody transfers and dwell points.
2. Construct a shipment-level event table linking order, lot, packaging, sensor, location, carrier, timestamps, and disposition.
3. Pareto-rank alerts by location and cause.
4. Compare service, quality, cost, and emissions by transport mode and lane.
5. Estimate expected loss for major failure modes.
6. Develop and test improvement scenarios.

Suppose the investigation finds that 62% of alerts occur during airport handoffs, 21% during warehouse staging, and 17% during final delivery. Suppose also that 40% of airport alerts are caused by tarmac dwell exceeding the qualified packaging duration. This evidence points toward lane and handoff redesign rather than a general increase in warehouse cooling capacity.

Options

Option A: Status quo with additional monitoring. This has low capital cost but does not remove the airport bottleneck or improve service reliability.

Option B: Regionalize inventory. Two regional depots could reduce final-mile time and improve customer responsiveness, but would add inventory, qualification, and facility cost.

Option C: Redesign the current network. NorthStar could qualify a longer-duration passive pack-out, establish a second gateway, use active containers for the highest-risk lanes, introduce appointment-based handoffs, and integrate sensor and scan data.

Option D: Premium all-air service. This could reduce transit time but would increase cost, emissions, and dependence on air capacity. It would also fail to address weak data and handoff controls.

A weighted decision matrix can compare options. Weights should be approved before scoring to reduce retrospective bias. For example, quality risk might receive 30%, service 25%, financial value 20%, resilience 15%, and sustainability 10%. Scores should be supported by evidence, and sensitivity analysis should test whether the preferred option changes when weights vary.

Recommended solution

The recommended approach is a staged version of Option C combined with targeted regionalization only if demand density justifies it.

Stage 1—Control the process: standardize pack-out, enforce FEFO, introduce airport handoff appointments, establish clear escalation times, and retrain the 3PL. Create a single deviation workflow and define product-disposition authority.

Stage 2—Improve visibility: integrate IoT sensor data with transport milestones and warehouse events. Use rules based on product, lane, and remaining packaging duration. Escalate actionable exceptions to named owners rather than sending generic alerts.

Stage 3—Reduce structural risk: qualify a second gateway and carrier, use active containers for the most exposed lanes, and negotiate service-level agreements with measurable handoff and recovery requirements.

Stage 4—Optimize the network: model regional stock positioning using demand, lead time, shelf life, inventory cost, and service requirements. Pilot one regional depot only after the first three stages produce reliable data.

Illustrative outcome

Assume the program reduces alert-related loss by $420,000 annually, lowers emergency freight by $180,000, increases technology and operating cost by $250,000, and requires $900,000 in initial investment. The annual net benefit is $350,000. At a 10% discount rate over four years, the approximate NPV is:

The present value of the four benefits is approximately $1,109,843, producing an NPV of approximately $209,843. This result is attractive but should be stress-tested. If the benefit falls below about $284,000 per year, the investment becomes approximately break-even under the same assumptions. That threshold is a useful management control: benefit realization should be tracked against it.

The proposed targets are OTIF above 97%, alert rate below 1.5%, logistics-related discard below 0.7% of shipment value, investigation closure within 10 business days, and a 10% reduction in emissions per shipment. Targets should be baselined, defined precisely, and reviewed for unintended effects—for example, whether lower alert rates result from missing data rather than better performance.

Governance roadmap

The steering committee should include supply chain, quality, finance, IT, procurement, operations, regulatory affairs, and customer representatives. Monthly operational reviews should examine leading indicators, while quarterly governance reviews should examine risk, financial benefits, regulatory changes, and strategic fit.

9. How to Present a Capstone Recommendation

A strong capstone presentation is an argument, not a catalogue of initiatives. It should contain:

1. Decision statement: what should be done, where, when, and why.
2. Evidence base: validated baseline, data sources, assumptions, and limitations.
3. Trade-off analysis: cost, quality, service, resilience, regulation, and sustainability.
4. Implementation plan: owners, resources, milestones, dependencies, and decision gates.
5. Risk register: failure modes, controls, triggers, contingency actions, and residual risk.
6. Benefits case: financial model, non-financial benefits, sensitivity analysis, and measurement plan.
7. Governance: accountability, auditability, escalation, and continuous improvement.

Students should distinguish facts, assumptions, estimates, and recommendations. A professional audience must be able to challenge the analysis and reproduce the central calculations.

10. Limitations and Critical Perspectives

Integrated models can create false precision. Temperature data may be dense while product-stability evidence is limited. Cost models may omit service failure, reputational harm, or patient impact. Emissions estimates vary with system boundaries and factors. Weighted scoring matrices can hide disagreement behind a single number. Digital systems can improve visibility without improving behavior.

Cold-chain strategy also involves ethical choices. A firm may prioritize high-margin customers over vulnerable populations, export products with inadequate local infrastructure, or use aggressive waste reduction targets that pressure employees to release questionable product. Ethical governance requires product safety, equitable access, worker protection, responsible data use, and transparent escalation to take precedence over short-term financial performance.

The capstone conclusion should therefore state not only what is recommended, but also what remains uncertain, what evidence is needed, and under what conditions the recommendation should be revised.

Chapter Summary

An effective cold chain is an integrated socio-technical system. Product requirements establish the quality boundary, while network design, packaging, transport, inventory, facilities, and human processes determine whether that boundary is maintained. Performance must be evaluated through balanced measures covering quality, service, operations, finance, compliance, sustainability, and resilience.

Temperature alerts require scientific interpretation and root-cause analysis; they cannot be managed responsibly through averages or isolated dashboards. Financial tools such as expected-loss analysis and NPV support investment decisions, but assumptions and sensitivity must be explicit. Regulation requires qualification, validation, traceability, data integrity, deviation management, supplier governance, and clear accountability.

Technology and AI are valuable when connected to defined decisions and controlled through validation, cybersecurity, human oversight, and fallback procedures. Sustainability and resilience should be designed together with product protection rather than treated as afterthoughts. The NorthStar case illustrates a staged roadmap: stabilize processes, integrate data, reduce concentration risk, and then optimize network structure. A capstone recommendation is credible when it links evidence to trade-offs, implementation, governance, and measurable outcomes.

Key Terms

Cold chain: A temperature-controlled supply network that protects time- and temperature-sensitive products.

Critical quality attribute (CQA): A product characteristic that must remain within an acceptable limit to ensure quality.

Critical process parameter (CPP): A process variable whose control affects a critical quality attribute.

Temperature excursion: Exposure outside an approved or validated temperature condition.

FEFO: First-expiry-first-out inventory rotation.

OTIF: On-time-in-full delivery performance measure.

Spoilage rate: The proportion of handled quantity discarded because of quality loss or expiry.

Safety stock: Inventory held to buffer uncertainty in demand or replenishment.

Passive packaging: Insulated packaging that controls temperature without continuous powered refrigeration.

Active container: A temperature-controlled container using powered refrigeration or heating.

Qualification: Demonstration that equipment, facilities, routes, or systems perform as specified.

Validation: Documented evidence that a process consistently produces the intended result.

CAPA: Corrective and preventive action used to address deviations and prevent recurrence.

Traceability: Ability to follow product, lot, custody, events, and records through the chain.

RACI: Responsibility framework identifying responsible, accountable, consulted, and informed parties.

Expected loss: Probability of an adverse event multiplied by its financial consequence.

NPV: Present value of incremental future cash flows less initial investment.

Resilience: Capacity to absorb disruption, continue critical operations, and recover effectively.

Data integrity: Completeness, consistency, accuracy, attribution, and availability of records.

Digital twin: A data-linked representation of a physical asset, process, or network used for monitoring or analysis.

Review Questions

Short Answer Questions

1. Why is temperature compliance necessary but not always sufficient to establish product quality?
2. Explain the difference between a critical quality attribute and a critical process parameter.
3. What are the principal limitations of using an FMEA risk-priority number mechanically?
4. Why should cold-chain KPIs be balanced across quality, service, finance, and sustainability?
5. Identify two governance controls needed before deploying AI for cold-chain decisions.

Long Answer Questions

1. Compare centralized and regionalized cold-chain networks, including their effects on cost, service, inventory, resilience, and emissions.
2. Explain how a company should investigate a recurring temperature excursion using both sensor and operational data.
3. Discuss how qualification, validation, traceability, deviation management, and supplier governance interact in a regulated cold chain.
4. Evaluate the benefits and limitations of passive packaging, active containers, and premium transport modes.
5. Develop a governance roadmap for a cold-chain transformation program and justify its decision gates.

Analytical / Application Questions

1. A proposed cold-room investment costs $750,000 and generates annual incremental cash savings of $240,000 for four years. Using a 10% discount rate and no residual value, calculate NPV and explain whether the decision should rely on NPV alone.
2. A network reports 98% OTIF but has rising product quarantine. Design a diagnostic analysis that determines whether the KPI definition, data integrity, or operating process is responsible.
3. Using the NorthStar case, construct a weighted decision matrix for the four strategic options. State your weights, scoring assumptions, sensitivity concerns, and recommended decision gate.

Multiple Choice Questions with Answers

Question 1

Which statement best describes an integrated cold-chain strategy?

A. Maximizing refrigeration capacity regardless of cost or service

B. Managing product, operations, information, finance, regulation, and sustainability as an interconnected system

C. Selecting the carrier with the lowest quoted freight rate

D. Measuring only whether recorded temperature stayed within range

Correct Answer: B. Managing product, operations, information, finance, regulation, and sustainability as an interconnected system

Question 2

What does FEFO primarily seek to achieve?

A. Use the oldest receipt date first regardless of expiry

B. Ship the product with the earliest expiry first

C. Prioritize the highest-value customer first

D. Load the largest pallet first

Correct Answer: B. Ship the product with the earliest expiry first

Question 3

A shipment has an expected failure probability of 0.04 and a financial consequence of $50,000. What is its expected loss?

A. $200

B. $1,250

C. $2,000

D. $20,000

Correct Answer: C. $2,000

Question 4

Which condition is required for the simple safety-stock expression SS = zσ_LT to be used appropriately?

A. Shelf life is irrelevant

B. Demand during lead time can be represented by an appropriate variability estimate

C. All demand is deterministic

D. The product has no temperature requirement

Correct Answer: B. Demand during lead time can be represented by an appropriate variability estimate

Question 5

In the NorthStar case, the largest share of alerts occurred during which activity?

A. Final customer delivery

B. Manufacturing release

C. Airport handoffs

D. Product labeling

Correct Answer: C. Airport handoffs

Question 6

What is a major limitation of an FMEA risk-priority number?

A. It cannot include severity

B. It is based on ordinal scores and should not mechanically determine all decisions

C. It requires no expert judgment

D. It measures financial return directly

Correct Answer: B. It is based on ordinal scores and should not mechanically determine all decisions

Question 7

Which statement about AI in cold-chain management is most appropriate?

A. AI eliminates the need for product-stability evidence

B. AI recommendations should operate without human review in regulated decisions

C. AI can support anomaly detection but requires validation, monitoring, and fallback controls

D. AI makes data quality and cybersecurity irrelevant

Correct Answer: C. AI can support anomaly detection but requires validation, monitoring, and fallback controls

Question 8

Using NPV = −I₀ + ∑ CF_t/(1+r)^t, what does a positive NPV generally indicate?

A. The project creates value relative to the selected discount rate, subject to assumptions

B. The project has no operational risk

C. The project will always meet regulatory requirements

D. The project has the lowest possible emissions

Correct Answer: A. The project creates value relative to the selected discount rate, subject to assumptions

Question 9

Which action most directly improves data integrity?

A. Displaying only successful shipments on a dashboard

B. Deleting anomalous records after investigation

C. Maintaining attributable, accurate, complete, and auditable records

D. Replacing all human review with automation

Correct Answer: C. Maintaining attributable, accurate, complete, and auditable records

Question 10

Why might a high OTIF score fail to demonstrate successful cold-chain performance?

A. OTIF always measures emissions instead of service

B. OTIF may count deliveries as successful even when products are damaged or temperature-excursed

C. OTIF cannot be calculated from orders

D. OTIF applies only to empty shipments

Correct Answer: B. OTIF may count deliveries as successful even when products are damaged or temperature-excursed