9. Omnichannel, Urban and Last-Mile Distribution

Introduction and Context

Distribution has traditionally been designed around relatively stable flows: manufacturers shipped consolidated quantities to wholesalers, retailers replenished stores, and customers travelled to purchase products. Retail digitalisation has altered this arrangement. Customers now expect to search, order, receive, return and exchange products through whichever channel is most convenient. A customer may discover an item through a mobile application, purchase it online, collect it from a store, return it through a parcel locker and contact a service centre for support. The physical distribution system must therefore coordinate several channels while preserving availability, speed, cost control and service quality.

Omnichannel distribution refers to the integrated management of inventory, orders, fulfilment and customer service across interacting sales and delivery channels. It differs from multichannel distribution, in which channels may coexist but operate with separate inventories, processes and performance measures. Urban and last-mile distribution are especially important within this system because the final movement to the customer is often the most variable, labour-intensive and visible part of the supply chain. In dense cities, delivery vehicles face congestion, parking restrictions, access limitations, emissions regulation and high customer expectations. In less dense areas, distance and low route density create different economic challenges.

The chapter examines how retailers, e-commerce businesses and service-parts providers design fulfilment and delivery systems. It considers parcel networks, micro-fulfilment, crowdsourced delivery, lockers, route density, failed deliveries, reverse logistics and customer experience. The central managerial question is not simply how to deliver faster. It is how to configure a system that delivers the right product, to the right place, within the promised time, at an economically and environmentally acceptable cost.

Learning Objectives

After studying this chapter, students should be able to:

1. Distinguish between multichannel and omnichannel distribution.

2. Explain the structure and economics of urban and last-mile delivery.

3. Design fulfilment alternatives involving stores, distribution centres, micro-fulfilment and parcel networks.

4. Evaluate lockers, crowdsourced delivery and delivery-time-window strategies.

5. Analyse route density, failed deliveries, returns and customer-experience measures.

6. Apply a structured approach to omnichannel distribution decisions.

7. Identify operational, technological, ethical, regulatory and environmental risks.

From Separate Channels to an Integrated Customer Journey

A channel is a route through which a customer discovers, orders, receives or returns a product. Common channels include physical stores, brand websites, mobile applications, marketplaces, call centres, social commerce and business-to-business sales teams. In a multichannel model, each channel may have separate inventory records, promotions, fulfilment rules and customer service processes. Omnichannel management attempts to make these channels appear coherent to the customer while coordinating the underlying operations.

The distinction is operational rather than merely promotional. Suppose a website shows a product as available because stock exists in a store, but the store inventory is inaccurate or the product cannot be picked before the promised cut-off time. The customer experiences a failed promise even though the organisation technically held inventory. Omnichannel capability therefore requires inventory visibility, order orchestration, common customer data, consistent service policies and the ability to allocate orders across nodes.

Several fulfilment options may be combined:

• Ship-from-distribution centre: the order is picked from a regional or national warehouse and sent through a parcel carrier.
• Ship-from-store: a retail store fulfils an online order, reducing delivery distance but adding work to store operations.
• Click-and-collect: the customer orders digitally and collects the item from a store, locker or collection point.
• Buy online, return in store: the physical store becomes part of the reverse-logistics network.
• Vendor-direct fulfilment: a supplier ships directly to the customer, reducing handling but complicating service control.
• Micro-fulfilment: a compact, often automated facility located near demand fulfils online orders rapidly.

The choice depends on product characteristics, demand density, inventory position, delivery promise, labour availability, transport rates and the strategic role of stores. A low-value item may not justify a dedicated same-day delivery, whereas an urgent service part may justify premium transport because the cost of equipment downtime is high.

The Last Mile as a System-Design Problem

The last mile is the final segment between a fulfilment point and the customer or designated collection location. It may be a short urban trip, a long rural route or a technically complex delivery to a business site. Although the physical distance is often small, the last mile contains considerable uncertainty. Customers may be absent, addresses may be incomplete, buildings may restrict access, and demand may be dispersed across many time windows.

Last-mile cost is shaped less by distance alone than by stops, service time and route productivity. A delivery vehicle incurs costs when it travels, but it also incurs costs when it parks, waits, searches for a recipient, obtains a signature or returns an undelivered parcel. For this reason, a route with many nearby deliveries can be more economical than a shorter route with scattered stops. Route density is commonly understood as the number of deliveries or delivery revenue achieved per route, kilometre, hour or geographic area.

A simplified delivery-cost expression is:

Total delivery cost = fixed vehicle and driver cost + distance cost + stop-service cost + failure cost + handling and technology cost.

The failure cost includes reattempts, customer-service contacts, returns to depot and possible product damage. A delivery system that minimises kilometres but creates many failed deliveries may perform worse than a slightly longer system with reliable first-attempt completion.

Urban delivery also involves externalities. Congestion, noise, curb occupation, packaging waste and emissions affect residents and public authorities. Consequently, service design must consider total social and environmental impact, not only the carrier’s direct cost. Consolidated delivery, electric vehicles, cargo bikes, lockers and collection points can improve vehicle utilisation, although each requires suitable infrastructure and customer acceptance.

Parcel Networks and Delivery Architecture

Parcel distribution normally involves collection from a shipper, consolidation at a local depot, movement through regional or national hubs, deconsolidation, final-mile dispatch and proof of delivery. Hub-and-spoke networks create economies of consolidation but add handling and transit time. Direct or zone-skipping models may reduce handling when demand is sufficiently dense. Cross-docking can move parcels through a facility with limited storage, while a traditional depot may hold parcels temporarily for route planning and dispatch.

Network design must balance centralisation and proximity. A highly centralised network can achieve inventory pooling and efficient line-haul transport, but delivery distances and response times may increase. A decentralised network offers faster local service but requires more inventory, facilities, labour and coordination. For service parts, the balance is particularly sensitive to criticality. A spare part required to restore a hospital device, industrial machine or utility asset may need forward stocking or emergency dispatch. Less critical parts can be consolidated into normal delivery cycles.

Important design decisions include:

1. Node location: where warehouses, depots, stores, lockers and collection points should be positioned.

2. Inventory ownership: whether stock is held by the retailer, marketplace seller, carrier or supplier.

3. Service segmentation: which customers and products qualify for standard, scheduled, same-day or emergency service.

4. Carrier portfolio: whether to use an integrated parcel carrier, several specialist carriers, a private fleet or a hybrid model.

5. Information integration: how orders, stock, tracking events, delivery instructions and returns are synchronised.

A carrier-selection decision should not be based only on price per parcel. Reliability, geographic coverage, claims performance, data quality, flexibility, capacity during peaks, labour practices and compatibility with customer promises are equally relevant.

Micro-Fulfilment and the Location of Inventory

Micro-fulfilment centres are small fulfilment facilities positioned close to concentrated demand. They may occupy part of a store, a dark store, a separate urban facility or a purpose-built automated site. Their purpose is to reduce order-cycle time and final-mile distance, particularly for fast-moving products.

Micro-fulfilment can use manual picking, goods-to-person systems, vertical storage, conveyors, robotic shuttles or combinations of these technologies. Automation is attractive where order volumes are high, the product range is manageable and labour or space is expensive. It is less attractive where demand is volatile, product dimensions vary greatly or the facility cannot achieve sufficient utilisation.

A sound design begins with demand analysis. Products selected for local stocking should generally have predictable demand, sufficient contribution margin and a meaningful service benefit from proximity. Inventory duplication creates working-capital and obsolescence risk. Therefore, the decision is not “central warehouse or micro-fulfilment” in absolute terms; a portfolio may use central stock for slow movers and local stock for high-frequency items.

Stores can function as fulfilment nodes, but this requires discipline. Picking online orders may disrupt customers, reduce shelf availability or compete with replenishment work. Clear zoning, dedicated picking periods, inventory accuracy controls and appropriate labour standards are necessary. A store that is physically close to the customer is not automatically an efficient fulfilment centre.

Delivery Choices: Home Delivery, Lockers and Crowdsourcing

Home delivery offers convenience and supports products that are bulky, urgent or difficult to collect. Its disadvantages include failed attempts, variable access conditions and high cost per individual stop. Delivery windows can improve customer convenience, but narrow windows increase routing complexity and reduce vehicle utilisation. A premium should often be attached to highly specific or urgent windows so that the price reflects the additional operational cost.

Parcel lockers and staffed collection points consolidate many deliveries into a single stop. They reduce failed home deliveries and can improve route density. Lockers are most effective where customers regularly pass the location, the site is secure and compartments match the product mix. Their limitations include installation cost, capacity constraints, accessibility concerns and the need to manage overflow during peak periods.

Crowdsourced delivery uses independent individuals or flexible delivery partners who accept jobs through a digital platform. It can provide capacity during peaks, support rapid delivery and avoid investment in a large permanent fleet. However, quality consistency, insurance, worker classification, safety, privacy and service accountability require careful governance. Crowdsourcing is not a substitute for system design; if orders are poorly sequenced or promises are unrealistic, additional drivers may simply increase cost without improving reliability.

A practical delivery portfolio may therefore combine standard parcel delivery, scheduled fleet delivery, lockers, store collection, crowdsourced capacity and premium emergency service. The design should match the product and customer segment rather than offering every option to every customer.

Route Density, Delivery Windows and Failed Deliveries

Route planning involves assigning stops to vehicles and sequencing them subject to vehicle capacity, time windows, driver hours, road restrictions and service requirements. The vehicle-routing problem is computationally difficult at scale, so organisations use optimisation software, heuristics, geographic clustering and real-time adjustments. Data quality is essential. Incorrect addresses, missing access codes and inaccurate delivery-time estimates can undermine even sophisticated algorithms.

Route density can be increased through geographic concentration, delivery-window design, collection points, subscription models and collaboration with other shippers. However, concentration should not be pursued by degrading customer access. A narrow delivery window may raise route density but inconvenience customers and increase missed deliveries. The appropriate performance target is profitable and reliable density.

Failed delivery is a symptom with several possible causes: recipient absence, incorrect address, restricted building access, damaged label, unsafe location, customer refusal or driver error. Preventive measures include address validation, customer reminders, safe-place instructions, recipient choice, delivery to lockers, building access integration and realistic promise dates. A failed delivery should be measured not only as a carrier event but also as a customer-experience failure and a source of additional emissions.

Relevant metrics include first-attempt delivery rate, on-time-in-full performance, cost per successful delivery, stops per route hour, kilometres per parcel, delivery-window adherence, customer contact rate and percentage delivered to an alternative location. Metrics should be segmented by geography, product, carrier, time of day and customer type. An average rate can conceal serious problems in particular neighbourhoods or service categories.

Reverse Logistics and the Complete Order Cycle

Omnichannel design is incomplete if it addresses outbound delivery but treats returns as an afterthought. Reverse logistics includes return authorisation, collection or drop-off, transport, inspection, grading, repair, repackaging, resale, recycling and disposal. Returns may arise from product defect, customer remorse, incorrect fulfilment, damage or regulatory requirements.

A convenient return policy can increase customer confidence and sales, but it also creates cost and fraud exposure. Organisations should distinguish between customer-friendly access and uncontrolled handling. Digital return authorisation, return consolidation, drop-off networks and return-to-store processes can reduce cost. Stores may provide immediate refunds and enable inspection, but staff require clear procedures and systems access.

Returned products should be routed according to economic value and condition. Possible dispositions include resale as new, refurbishment, resale as graded stock, repair, component recovery, donation, recycling and disposal. The decision should account for recovery value, processing cost, time sensitivity, product safety and data protection. For electronics and service parts, secure deletion and traceability may be essential.

Customer Experience as an Operational Outcome

Customer experience is produced by the entire fulfilment journey, not simply by delivery speed. Customers value accurate availability information, transparent promises, convenient options, reliable tracking, courteous handling, easy modification and fair resolution when failure occurs. A fast delivery that arrives damaged or at an inaccessible location is not a high-quality service.

Service promises should be based on actual system capability. Order-management systems should distinguish between inventory on hand, inventory available to promise and inventory already allocated elsewhere. Event-driven tracking can provide information when an order is picked, dispatched, delayed, out for delivery or completed. Excessive notifications, however, may confuse customers; communication should be timely and actionable.

Customer-experience measures can include delivery satisfaction, complaint rate, contact effort, repeat purchase, cancellation, return behaviour and resolution time. These should be interpreted alongside operational measures. For example, a high satisfaction score achieved through expensive same-day delivery may not be financially sustainable, while a low complaint rate may reflect customers abandoning the channel rather than accepting poor service.

Technology, Analytics and Automation

Omnichannel distribution depends on an integrated digital architecture. Core components may include an order-management system, warehouse-management system, transport-management system, inventory platform, customer relationship system, carrier interfaces and returns platform. Application programming interfaces and event-based data exchange allow order and tracking information to move between participants.

Analytics supports demand forecasting, inventory allocation, delivery-slot pricing, route optimisation, carrier evaluation and failure prediction. Machine-learning models may estimate the probability of failed delivery using historical address, time, weather and recipient data. Such models must be monitored for bias and should not use sensitive personal information without legitimate justification. Artificial intelligence can recommend routing or customer-service responses, but human oversight remains important where decisions affect access, refunds, employment or safety.

Automation should be evaluated through total economic value, not technical novelty. Relevant questions include: Does it improve throughput or accuracy? Can it operate under peak demand? What happens during system failure? Are maintenance, cybersecurity, training and integration costs included? A manual process with reliable controls may be superior to automation that is poorly utilised or difficult to recover.

Managerial Framework for Designing an Omnichannel System

A practical design process can be organised into seven connected decisions.

First, define the service promise. Specify delivery speed, accuracy, availability, time-window flexibility, collection options, returns and emergency requirements for each customer segment.

Second, segment products and orders. Consider value, size, perishability, demand volatility, urgency, handling requirements and return probability.

Third, map demand and inventory. Analyse order density, geographic clusters, peak periods, customer locations and current inventory accuracy.

Fourth, configure the fulfilment network. Compare central warehouses, stores, micro-fulfilment centres, suppliers, lockers and carrier depots.

Fifth, design transport and capacity. Select fleet, carriers, delivery windows, route policies and contingency capacity. Include peak scenarios rather than designing only for average demand.

Sixth, establish governance and measurement. Assign responsibility for promise accuracy, stock integrity, carrier performance, customer communication, returns and data protection.

Seventh, pilot and improve. Test one geography, product category or customer segment. Compare service, cost, carbon, employee workload and customer outcomes before scaling.

The framework highlights a central trade-off: service differentiation must be supported by operational capability. Offering unlimited delivery choices can fragment demand, reduce route density and create complexity. A smaller number of well-designed options may produce a better customer experience and stronger economics.

Illustrative Case: MetroMart’s Urban Omnichannel Redesign

Background

MetroMart is an illustrative mid-sized grocery and household retailer operating stores in a large metropolitan region. It has a national distribution centre, 40 stores and an online channel. Customers can order home delivery or collect from selected stores. Online sales have grown, but the company’s delivery costs and complaints have also increased.

Situation and Problem

The website displays store inventory, yet stock records are often inaccurate. Store employees receive online picking tasks alongside shelf-replenishment duties. Home deliveries are concentrated in evenings, producing congestion and driver overtime. Customers frequently miss deliveries because time windows are too broad or because apartment access information is incomplete. Returns and substitutions are handled inconsistently across stores.

Management initially proposes a dedicated automated micro-fulfilment centre. However, the investment would duplicate inventory and would not immediately solve address quality, failed deliveries or poor store processes.

Analysis

A four-week operational study identifies three customer segments: routine weekly shoppers, urgent top-up shoppers and customers who prefer collection. Demand is concentrated around six urban clusters. High-volume items are predictable, while long-tail products are ordered infrequently. The study also finds that lockers and staffed collection points are available near public transport stations. Approximately one-third of failed deliveries are associated with access or recipient availability rather than vehicle capacity.

The company compares alternatives using cost per successful order, first-attempt completion, picking productivity, inventory accuracy, customer satisfaction and estimated emissions. It concludes that the immediate constraint is not simply warehouse distance. The system suffers from poor order orchestration and an excessive number of individual home-delivery stops.

Approach and Solution

MetroMart adopts a staged design:

1. It introduces a single order-management layer that allocates orders using real-time available-to-promise inventory.

2. Six high-volume stores receive dedicated online-picking zones and separate performance targets.

3. Fast-moving products are locally positioned in those stores; slow-moving items remain primarily at the distribution centre.

4. Collection is expanded through lockers and staffed points near transport hubs.

5. Customers receive narrower, priced delivery windows, while standard windows remain available at lower cost.

6. Address validation and apartment access instructions are added at checkout.

7. A contracted carrier provides baseline capacity, while a screened flexible-delivery pool is used only for peaks.

8. Returns are accepted at stores and consolidated for inspection and redistribution.

Outcome

The illustrative pilot produces fewer home-delivery stops per order, improved first-attempt completion and better visibility of inventory. Store workload becomes more predictable because picking is separated from replenishment. Customers who choose collection receive reliable access without waiting at home. The company postpones major automation until demand density and process stability justify it.

Learning Points

The case demonstrates that omnichannel performance depends on coordinated decisions rather than on a single facility or technology. Inventory accuracy, customer choice, route density, collection infrastructure and returns must be designed together. It also shows why pilots should measure successful fulfilment and total system cost rather than online sales volume alone.

Challenges, Risks and Professional Considerations

Omnichannel distribution creates operational complexity. Inventory may be visible but unavailable, orders may be split across nodes, promotions may create unplanned peaks, and different channels may compete for the same stock. Clear allocation rules are necessary when supply is limited. Organisations should also avoid promising delivery speeds that depend on exceptional labour effort or unsafe driving practices.

Labour and social issues deserve explicit attention. Delivery workers may be employees, contractors or platform participants, and responsibilities for training, insurance, fair treatment and safety must be defined. Algorithmic performance monitoring can become intrusive if workers are assessed without considering traffic, building access or customer-caused delay.

Privacy and cybersecurity are significant because delivery systems process names, addresses, phone numbers, access codes, purchasing patterns and sometimes location data. Data should be collected for legitimate purposes, retained appropriately, protected from unauthorised access and shared only with necessary partners. Customers should understand how delivery instructions and tracking information are used.

Environmental evaluation should include packaging, failed attempts, vehicle manufacture, refrigeration, returns and facility energy consumption. Electric vehicles and cargo bikes can reduce local emissions, but their effectiveness depends on electricity sources, load factors, charging access and route design. A failed electric-vehicle delivery still consumes resources; prevention and consolidation remain important.

Common managerial mistakes include measuring speed without reliability, treating every customer as requiring home delivery, opening micro-fulfilment facilities before validating demand, ignoring returns, selecting carriers only by tariff, and allowing each channel to optimise its own results. Governance should instead use shared measures such as profitable on-time completion, inventory accuracy, customer effort, employee safety and environmental impact.

Current Developments and Best Practices

Several developments are shaping the field. Urban authorities are introducing low-emission zones, delivery-slot controls, curb-management systems and restrictions on vehicle access. Retailers are experimenting with shared urban consolidation centres, reusable packaging, autonomous technologies and dynamic delivery pricing. Parcel networks increasingly combine home delivery with lockers, shops and automated collection points.

Best practice is emerging around a few principles:

• Promise only what the network can reliably deliver.
• Use customer segmentation rather than one universal service level.
• Treat stores as operational nodes only when processes and incentives support fulfilment.
• Increase route density through consolidation without removing reasonable customer choice.
• Design reverse logistics at the same time as outbound fulfilment.
• Measure successful, sustainable delivery rather than kilometres or speed alone.
• Maintain human accountability for automated decisions affecting customers and workers.
• Pilot new technologies with operational, financial, social and environmental measures.

Chapter Summary

Omnichannel distribution integrates stores, websites, applications, marketplaces, fulfilment nodes, carriers and return channels into a coherent customer journey. Its success depends on accurate inventory, order orchestration, appropriate service promises and coordinated physical processes. Last-mile economics are shaped by stops, service time, route density, failed deliveries and customer requirements, not distance alone.

Parcel networks, micro-fulfilment, ship-from-store, lockers, collection points and crowdsourced delivery provide alternative ways to balance speed, cost and convenience. No option is universally superior. Network design must consider demand density, product characteristics, urgency, inventory duplication, labour, regulation and environmental impact. Reverse logistics and customer communication are integral to the order cycle. Technology and analytics can improve forecasting, allocation, routing and visibility, but they require reliable data, governance, cybersecurity and human oversight. The most effective systems promise realistic service, segment demand, consolidate flows, prevent failure and evaluate total system performance.

Key Terms

Omnichannel distribution: Integrated management of multiple customer and fulfilment channels so that the customer experiences a coordinated service.

Multichannel distribution: Use of multiple channels that may operate with separate processes, inventories or performance systems.

Last mile: The final movement of a product from a fulfilment or transport node to the customer or collection location.

Route density: Concentration of deliveries or revenue within a route, geographic area, distance or time period.

Micro-fulfilment centre: A compact facility located near demand to process online orders rapidly.

Ship-from-store: Fulfilment of a digital order using inventory and labour at a retail store.

Click-and-collect: Customer ordering through a digital channel and collecting the order from a designated location.

Parcel locker: Secure self-service infrastructure where parcels are deposited for customer collection.

Crowdsourced delivery: Delivery capacity supplied by flexible, digitally coordinated individuals or partners.

Order orchestration: Allocation and coordination of orders, inventory and fulfilment activities across a network.

Available to promise: Inventory that can realistically be committed to a customer after considering existing allocations and operational constraints.

First-attempt delivery rate: Percentage of delivery orders successfully completed on the initial attempt.

Delivery window: Promised period during which a delivery is scheduled to arrive.

Reverse logistics: Movement and processing of products from customers back through the supply chain for recovery, return or disposal.

Service parts: Components supplied to repair or maintain equipment and restore operational availability.

Urban consolidation: Combining shipments for a geographic area to reduce vehicle movements and improve utilisation.

Proof of delivery: Evidence that a shipment was delivered to the intended recipient or location.

Delivery externality: Cost imposed on other parties or society, such as congestion, noise, emissions or curb occupation.

Review Questions

Short Answer Questions

1. What is the principal operational difference between multichannel and omnichannel distribution?

2. Why is route density important in last-mile economics?

3. Identify two situations in which micro-fulfilment may be appropriate.

4. What are two causes of failed delivery?

5. Why must reverse logistics be included in omnichannel design?

Long Answer Questions

1. Explain how inventory visibility and order orchestration support an omnichannel customer promise.

2. Compare home delivery, parcel lockers and click-and-collect as last-mile alternatives.

3. Discuss the major decisions involved in designing an urban parcel network.

4. Explain the operational and managerial implications of ship-from-store fulfilment.

5. Analyse the role of technology and analytics in improving last-mile distribution while preserving governance and privacy.

Analytical / Application Questions

1. A retailer has high delivery costs, low route density and frequent evening delivery failures. Design a combination of service, network and customer-choice changes to address the problem.

2. A service-parts company must decide whether to hold a critical component in a regional depot or serve demand from a central warehouse. Develop criteria for making the decision.

3. Evaluate whether a retailer should invest in an automated micro-fulfilment centre when its inventory accuracy is poor and online demand is volatile. Justify your recommendation using total-system considerations.

22. Multiple Choice Questions with Answers

Question 1

Which feature most clearly distinguishes omnichannel distribution from a basic multichannel arrangement?

A. The organisation uses more than one sales channel

B. All products are delivered directly to customers’ homes

C. Channels are coordinated through shared inventory, fulfilment and customer-service processes

D. Customers receive the same price in every channel

Correct Answer: C. Channels are coordinated through shared inventory, fulfilment and customer-service processes

Question 2

Why can a route with more kilometres sometimes have a lower cost per successful delivery than a shorter route?

A. Longer routes always use less fuel

B. It may contain more concentrated stops and therefore higher route density

C. Customers on longer routes never require delivery windows

D. Distance has no effect on delivery cost

Correct Answer: B. It may contain more concentrated stops and therefore higher route density

Question 3

Which situation most strongly supports the use of a micro-fulfilment centre?

A. Highly volatile demand with very low order volume

B. Concentrated demand for predictable, fast-moving products near an urban market

C. Products requiring no inventory availability

D. A market in which all customers collect from suppliers

Correct Answer: B. Concentrated demand for predictable, fast-moving products near an urban market

Question 4

What is a major operational advantage of parcel lockers?

A. They eliminate the need for inventory planning

B. They guarantee same-day delivery for every product

C. They consolidate multiple customer deliveries at one location and reduce failed attempts

D. They remove all customer responsibility for collection

Correct Answer: C. They consolidate multiple customer deliveries at one location and reduce failed attempts

Question 5

A retailer measures only kilometres per parcel and reports improvement, but customer complaints and reattempts rise. Which conclusion is most appropriate?

A. The delivery system has definitely improved

B. Kilometres per parcel is sufficient as the only performance measure

C. The retailer should also examine successful delivery, reliability and failure costs

D. Customer complaints are unrelated to distribution performance

Correct Answer: C. The retailer should also examine successful delivery, reliability and failure costs

Question 6

Which action best addresses failed deliveries caused by apartment-building access problems?

A. Increase warehouse storage capacity only

B. Collect access instructions and integrate them into delivery planning

C. Remove all delivery time windows

D. Increase packaging size

Correct Answer: B. Collect access instructions and integrate them into delivery planning

Question 7

Why can ship-from-store create difficulties even when the store is close to the customer?

A. Stores cannot contain any inventory

B. Picking online orders may conflict with replenishment, customer service and inventory accuracy

C. Shorter distance always increases transport cost

D. Store employees are never involved in fulfilment

Correct Answer: B. Picking online orders may conflict with replenishment, customer service and inventory accuracy

Question 8

Which is an appropriate reverse-logistics disposition for a returned electronic product containing customer data?

A. Immediate resale without inspection

B. Disposal without considering regulation

C. Secure data deletion followed by inspection and an appropriate recovery decision

D. Automatic shipment to the original customer

Correct Answer: C. Secure data deletion followed by inspection and an appropriate recovery decision

Question 9

What is the principal governance concern when crowdsourced delivery is used?

A. Crowdsourcing always lowers capacity

B. There is no need to track deliveries

C. The organisation must manage issues such as safety, insurance, worker status and service accountability

D. Crowdsourced drivers cannot use digital systems

Correct Answer: C. The organisation must manage issues such as safety, insurance, worker status and service accountability

Question 10

A retailer has poor inventory accuracy and volatile online demand. What is the most defensible approach before investing heavily in automated micro-fulfilment?

A. Build the largest possible facility immediately

B. Improve data and process controls, then pilot and evaluate demand, utilisation and total cost

C. Ignore inventory accuracy because automation corrects all errors

D. Offer unlimited delivery windows to create demand

Correct Answer: B. Improve data and process controls, then pilot and evaluate demand, utilisation and total cost