In the realm of online shopping, stock-outs have become a significant concern, sparking frustration among customers. Significant growth in the global online retail market has been fuelled by the widespread adoption of internet technology, enhanced user proficiency and an increasingly fast-paced society (Islam 2021). Many online shopping customers are disappointed with the unreliability of online shopping because of stock-outs, which have resulted in several inconveniences and a waste of time on their part (Khairi 2021). Online retail is one of the biggest parts of the extensive digital transformation of the economy. E-commerce in South Africa is experiencing significant growth through mobile usage, and the capacity to shop using mobile devices has increased (Rita, Oliveira & Farisa 2019). It has surged especially after the coronavirus disease 2019 (COVID-19) pandemic, prompting many retailers to adapt their sales strategies and rethink their organisational culture to align with current shopping trends (Fabius et al. 2020; Hänninen, Kwan & Mitronen 2021).

Online shopping has gained excellent momentum with consumers, where currently most online stores have an app, which has become easily accessible (Benrqya 2021). In online shopping, retailers leverage lean practices, transforming their relationship with suppliers (Schonberger 2018). A good example is the global retailer Walmart, which employs lean principles in its online shopping to achieve substantial economies of scale, thereby supporting its distinctive business model centred on ‘daily price reductions’ (Retnowati & Mardikaningsih 2021:36).

The consumer product industry has undergone a significant transformation as a result of rapidly evolving technologies, changing demographics and shifting consumer preferences. In an increasingly competitive online retail marketplace, retailers must integrate innovative technologies with targeted digital marketing strategies to differentiate their offerings. This shift empowers consumers, enhancing their control over purchasing decisions and creating a diverse landscape of choices (Bozarth & Handfield 2019; Huang et al. 2019). Every organisation has a supply chain management (SCM) department that is vital. The SCM department regulates the organisation’s procurement, storage, production, distribution, inventory management and order fulfilment activities, as well as the planning, design, implementation and control of those activities (Attaran 2017). The typical supply chain functions as a network that connects several businesses to produce and distribute goods or services.

A 2023 South African e-commerce survey revealed that most online shoppers are woman aged 18–39, with most spending between R250 and R1000 on their purchases (Rafee 2024:88). Despite the growth of online shopping, stock-outs, where products are unavailable for sale on the platform, remain a significant challenge that led to over 1,000 complaints in the past 3 years (Zappone 2021). This article aims to delve into the underlying factors contributing to these stock-out occurrences and explores how lean retail strategies can be implemented to enhance dependability in online shopping by asking: What are the factors that contribute to stock-outs? How can lean retail reduce stock-outs in online shopping? It then proposes a dynamic fulfilment framework, grounded in lean principles, to eliminate stock-outs in online retail by transforming supply chains from static inventories into agile, networked ecosystems.

This article is divided into five sections. The first section started with the introduction. The second section discusses the factors that contribute to stock-outs in online shopping and how lean retail can reduce stock-outs in online shopping. The third section discusses the research methodology, sample size, and the data collection and analysis. The fourth section discusses the empirical data collection, which was collected through work observations and face-to-face semi-structured interviews. The fifth section discusses the research findings and conclusions.

Online shopping is greatly impacted by stock-outs, when a product is not available for purchase. It can result in missed sales, unhappy customers and possible harm to a brand’s reputation (MacCarthy et al. 2016). Because of the unpleasant experience of a stock-out, customers may abandon shopping carts, move to rival websites or refrain from visiting the business again (Mullins, Chase & Friend 2024). The following briefly discusses the factors contributing to stock-outs in online shopping.

Research consistently shows that stock-outs are a major cause of customer unhappiness with online shopping (Ahlstrom 2004; Martins et al. 2021; Womack & Jones 1996). Lean retail is an adaptation of lean principles to retailing, which can directly help reduce stock-outs by eliminating inefficiencies, improving flow and making inventory management more responsive. These will be discussed in this section.

A qualitative research methodology was adopted to explore and investigate the factors that contribute to stock-outs in online shopping using lean retail in South Africa. The qualitative methodology was appropriate because this research aimed to understand the views of participants rather than to make use of a numerical investigation of the problem (Blumberg et al., 2014:144; Saunders et al. 2016:168). The population studied was a major retailer in South Africa, the second-largest distributor of consumer goods in Africa, with four divisions across 423 stores in 13 sub-Saharan countries. This retailer holds significant market share in general merchandise, liquor, home improvement and wholesale food sectors.

Data were collected using qualitative work observations and semi-structured interviews. Twelve employees representing various levels of the merchandise and supply chain department were purposively selected based on specific criteria, as well as middle management and upper management. These individuals had 3 years of experience and were knowledgeable about the impact of stock-outs in online shopping. The interviews were transcribed using Microsoft 365’s dictate feature, with the researcher carefully reviewing the recordings to ensure accuracy. Employees provided operational insights, supervisors contributed operational and strategic viewpoints, and managers offered strategic information. The transcribed data were subsequently analysed using content analysis. This article was written by the authors with the assistance of ChatGPT-4 that was used solely for language polishing and editorial refinement of the authors’ original ideas and research findings. The authors have thoroughly reviewed, validated and substantiated all scholarly content and claims.

The data gathered from interviews and workplace observations clearly demonstrate that the organisation’s online shopping operations are characterised by significant waste and inefficiency, as defined by Liker & Hoseus (2004) framework. The core issue is a fundamental misalignment between the dynamic nature of e-commerce and the organisation’s rigid, siloed systems and processes.

A primary source of waste is the lack of real-time system synchronisation. The researcher’s own experience, alongside observational and interview data, confirms that the online system frequently indicates stock is available when it is not. Stock-outs thus occur because ‘System X’ updates stock levels on an overnight batch cycle, rather than reflecting transactions as they happen, in real time. Consequently, a walk-in customer can physically purchase an item, while an online customer simultaneously buys the same now-unavailable stock. This buying of the same product using different platforms leads directly to customer disappointment and constitutes a major form of waste, specifically waiting and delays, as identified by Liker & Hoseus (2004). Customers are forced to wait, often for a full day, to be notified that their order cannot be fulfilled, undermining the core promise of convenience that online shopping is meant to offer, a critical failure in system integration.

The organisation’s internal systems (for online sales, point-of-sale, distribution centres and inter-store transfers) operate in isolation. Furthermore, these systems are not integrated with those of key suppliers. This siloed infrastructure, operational inefficiency (Liker & Hoseus 2004), means that data regarding sales, orders and stock movements cannot flow seamlessly. The result is a perpetual state of inaccurate inventory records that forces staff to engage in non-value-adding motion waste, such as physically calling other stores to locate products, rather than serving customers effectively.

This systemic failure has a direct and damaging impact on information management. As online customers cannot physically inspect products, they are entirely dependent on the accuracy of the information presented. Inaccurate stock levels, product details or delivery estimates erode trust and risk losing sales to competitors. The data suggest that, while the organisation has dedicated roles such as buyers, planners, and merchandise controllers to manage inventory, their efforts are undermined by the poor quality of the data they receive. Without integrated systems that provide a single source of truth, achieving accurate demand forecasting and effective inventory management becomes nearly impossible. The lack of integrated systems leads to a costly paradox: the organisation simultaneously suffers from stock-outs (a form of waste through lost sales) and potentially from excess inventory (another of Liker’s wastes), as planners lack the reliable data needed to align stock with actual demand.

The manual and protracted nature of key processes, such as ordering stock from RDCs or executing inter-store transfers, creates further delays and administrative bottlenecks that shift staff’s focus from value-adding customer service and contribute to a long turnaround time for online deliveries. In a market where competitors offer 24-h delivery, these delays represent a significant competitive disadvantage.

Ultimately, the organisation appears to be neglecting the principles of continuous improvement, as embodied by the PDCA cycle. The current state of the online platform suggests a reactive approach to problems, rather than a proactive, planned effort to enhance processes. Complaints are addressed on an ad-hoc basis, but there is no evidence of a systematic review of the entire end-to-end online shopping value stream to identify and eliminate the root causes of waste. For genuine improvement, the organisation must initiate a PDCA cycle, beginning with a comprehensive plan to integrate its systems, streamline its supply chain digitisation, and re-engineer its processes around the core lean principle of delivering maximum value to the customer with minimal waste.

From a lean retail perspective, the entirety of these issues represents a fundamental deviation from its core philosophy of maximising customer value while minimising waste (muda). The current online shopping process is rife with waste. The organisation is not only suffering from the obvious waste of waiting (customer delays) and defects (incorrect orders), but also from the more insidious wastes of over-processing (manual administrative workarounds), motion (staff searching for stock), and most critically, the waste of unused talent (as staff are forced to fight systemic fires rather than contribute to improvement). The lack of real-time data creates a ‘push’ system based on flawed forecasts, rather than a customer-driven ‘pull’ system that responds to actual demand. A true lean approach would mandate a deep, value-stream mapping exercise to visualise this entire process, from customer order to delivery, and systematically eliminate every step that does not add value in the eyes of the customer, building a fluid, integrated and responsive system in its place.

The identified failures in real-time synchronisation and the resultant waste of waiting and customer dissatisfaction reveal the limitations of traditional, inventory-centric lean models in modern e-commerce. While improving internal data flow is a necessary first step, our findings suggest that a more profound application of lean thinking is required: the adoption of a dynamic fulfilment model. A dynamic fulfilment model is an agile logistics strategy that leverages real-time data and a networked ecosystem of fulfilment nodes to intelligently route customer orders to the optimal location, thereby enhancing service levels and operational resilience (Winkelhaus & Grosse 2020). This approach aligns with the concept of a physical internet and digital supply chain twins, where intelligent, real-time routing of customer demand is paramount (Ivanov 2023; Winkelhaus & Grosse 2020).

Instead of a stock-out representing a terminal failure in the value stream, a dynamic, pre-mapped network of alternatives, such as direct-to-customer shipping from a supplier or a peer-to-peer store transfer, can be instantly activated. This transforms a potential muda (waste) event into a continuous flow of value, ensuring the customer’s need is met without delay. This resilience is a core tenet of modern supply chain strategy, moving beyond mere leanness to achieve agile resilience by designing for adaptability in the face of disruption (Dubey et al. 2023). Consequently, dynamic fulfilment emerges not merely as a technical solution, but as the logical evolution of lean principles integrated with digital capabilities, creating a system where value is preserved even in the face of inventory uncertainty.

While traditional lean retailing and conventional fulfilment models effectively target internal waste and improve forecast accuracy, they exhibit a critical limitation in the context of modern, volatile e-commerce: they are fundamentally designed to prevent stock-outs within a static, linear supply chain. When prevention fails, as it inevitably does due to sudden demand surges, supply disruptions or systemic data latency, these models offer no embedded, proactive mechanism to preserve the customer order. The result is a terminal service failure, manifesting as a cancellation, backorder or lost sale, which directly contravenes the lean principle of continuous value flow.

This study’s findings reveal a pivotal gap between operational problem detection and resolution. The root cause of stock-outs was identified as systemic latency and information fragmentation. Merely fixing this data delay, while a necessary foundational step, constitutes an incomplete solution. The extant literature and prevailing practice lack a prescriptive framework that leverages real-time data visibility not just for better internal planning, but for the dynamic, intelligent fulfilment across a network of available inventory nodes. This gap represents a missed opportunity to apply lean thinking holistically to the entire, extended value stream.

To bridge this gap, we propose a dynamic fulfilment framework that represents an evolution of lean principles, integrating them with the capabilities of digital supply networks. Its core innovation lies in shifting the operational paradigm from inventory-centric prevention to networked resilience. Unlike static models, this framework pre-maps and integrates alternative fulfilment pathways into a cohesive ecosystem. When a stock-out occurs at one node, the system does not default to failure; instead, it uses real-time data to instantly reroute the customer order to the optimal available inventory source within the network.

Consequently, the proposed framework differs from and improves upon current approaches in three significant ways. Firstly, it transforms a potential waste event (a stock-out) into a managed process, thereby upholding the lean mandate of continuous flow. Secondly, it extends lean value stream mapping beyond the organisation’s boundaries to optimise the flow of goods and information across a multi-enterprise network. Finally, it elevates the strategic objective from mere operational efficiency to agile resilience, ensuring customer value is delivered despite localised disruptions. In essence, it moves beyond asking, ‘How do we avoid running out of stock?’ to answer the more critical question: ‘How do we guarantee fulfilment even when we run out of stock in a primary location?’

The framework’s core logic assumes that customer value is maximised by the seamless, uninterrupted fulfilment of demand. It posits that a stock-out in one network node need not cause a service failure if other nodes hold available inventory. This approach assumes the modern retail environment is inherently volatile, necessitating a design-for-resilience model. Successful implementation assumes the retailer possesses the internal coordination to manage a multi-node network. It requires key supply partners to have a basic level of digital connectivity and operational transparency. The framework is contingent upon technological readiness for real-time inventory synchronisation and intelligent order orchestration. It fundamentally depends on the availability of accurate, standardised, and timely data across the defined network. The model assumes the substantial initial cost of technology integration is justified by long-term gains in sales preservation. It also assumes network partners are willing to participate under mutually beneficial commercial terms. The framework is theoretically anchored in the core tenets of lean thinking. It represents an evolutionary application of lean principles to digitally connectable supply chain networks. The pull system principle dictates that replenishment should be triggered by actual consumption. In a digital network, a customer order can theoretically pull a product from the optimal available node across the entire ecosystem. Value stream mapping must be applied to the multi-path journey of a single order across organisational boundaries. This extended mapping identifies and eliminates waste in the hand-offs between network nodes, optimising for end-to-end flow. Lean’s aim for perfect flow theoretically re-conceptualises discrete, static inventories into a fluid, shared network resource. A dynamic network transforms potential waste from lost sales into a managed process that maintains continuous value delivery. The transition to a networked ecosystem is therefore the contextual evolution of lean theory. It applies lean’s fundamental axioms to the new reality of digitally connected supply chain actors.

The graphic framework in Figure 1 shows how lean thinking has developed in the context of e-commerce to solve the enduring issue of stock-outs. It starts with the discovery that stock-outs are the main problem in online retail, resulting in unhappy customers, lost sales and inefficient operations. The diagnosis, which is based on a lean-based root cause analysis, identifies systemic waste in the value stream, especially the waiting, correction, and flow failure wastes, which are made worse by batch processing delays. To restore process efficiency, the fundamental lean solution suggests implementing value stream mapping, data governance and real-time inventory synchronisation. Building on this foundation, the framework presents the dynamic fulfilment model, a noteworthy innovation that employs real-time data to dynamically manage demand across a network of connected devices rather than just preventing stock-outs. This model enables fulfilment through direct supplier dispatch, peer-to-peer store transfer or partner click-and-collect, ensuring that sales are preserved and customer value is enhanced. Ultimately, the framework culminates in an evolved, resilient lean system characterised by seamless flow, pull-based orchestration and agile adaptability to disruption.

The utility and configuration of the dynamic fulfilment framework are contingent on specific product and retail characteristics. The framework offers strong utility for high-value, low-frequency goods like electronics, where the cost of a lost sale justifies network orchestration. It is highly beneficial for fashion and trend-driven retail, which suffer acutely from forecast errors and demand volatility. It is also effective for managing slow-moving or long-tail items, increasing assortment breadth without proportional inventory cost.

For fast-moving consumer goods, the benefit of complex dynamic routing may not offset its cost, although real-time visibility remains crucial. Perishable goods require a network designed with strict rules governing shelf-life and compliance. Very high-value-density goods may necessitate a more limited, tightly controlled network due to security and authentication requirements. The framework’s core components are broadly applicable as a universal principle. Its specific instantiation, however, must be tailored to product characteristics such as value, variability, velocity and vulnerability.

This research confirms that stock-outs are a symptom of fragmented systems and batch-driven latency and argues that the ultimate solution lies not only in correcting these internal inefficiencies but also in architecting a fundamentally more resilient fulfilment model. Based on a lean perspective, this study identifies that stock-outs in online retail fundamentally represent a failure to deliver customer value and eliminate waste, primarily stemming from a lack of real-time system synchronisation. The key findings confirm that the core operational issue is the reliance on an overnight batch processing cycle within ‘System X’, which creates a critical lag. This latency allows in-store purchases to deplete inventory that remains listed as available online, leading directly to the dual sale of a single product and resulting in customer disappointment. This situation directly constitutes the lean wastes of waiting and unnecessary processing.

Furthermore, the accuracy of online product information is shown to be vital for value creation and closing sales; poor-quality information leads to abandoned purchases and demonstrates an incomplete implementation of lean principles. The underlying cause is that the organisation’s internal and external systems operate in isolation, creating a fragmented rather than a cohesive, flowing supply chain. The proposed dynamic fulfilment framework addresses a specific shortfall in existing models, which treat the supply chain as a linear sequence with single points of failure. By contrast, our framework reconceptualises the supply chain as an agile, networked ecosystem. It fills the gap between real-time problem awareness and automated, multi-option resolution. This represents a significant departure from conventional lean applications focused on internal process refinement; here, lean thinking is leveraged to design and manage flow across a dynamic network, ensuring that the end-customer’s value expectation of receiving the desired product is met with unprecedented consistency.

The managerial implications are severe, as these inefficiencies erode customer trust and brand equity by breaking the core promise of convenience, while also causing direct financial loss through cancelled orders and lost future sales. Strategically, this operational model leaves the organisation vulnerable to more agile competitors. To address this, practical recommendations include implementing a real-time inventory synchronisation platform to create one definitive and accurate record of all inventories. It is further advised to adopt a lean, iterative approach by piloting this system in a select group of top-performing stores before a wider rollout, allowing for refinement and validation. Finally, establishing a cross-functional data governance team is crucial for overseeing the quality and accuracy of all online product information.

The true evolution beyond a foundational fix lies in adopting a dynamic fulfilment model, which represents the next stage in the lean journey. This evolution entails a shift from simply creating an accurate, single source of truth for inventory to leveraging that data for building an agile, networked ecosystem. Within such an evolved model, a stock-out in one node no longer signifies a service failure; instead, intelligent systems instantly reroute demand to the optimal available inventory source across the network, whether a different warehouse, retail store or supplier. Such a capability transforms potential losses into preserved sales, thereby operationalising the lean principle of flow at a systemic level and creating unparalleled resilience against the inefficiencies of a fragmented supply chain. Therefore, this dynamic fulfilment framework does not merely seek to improve upon existing models incrementally; it proposes a paradigm shift towards a digitally enabled, lean-driven system where resilience is engineered into the very fabric of retail logistics, transforming inventory uncertainty from a liability into a manageable variable within a fluid network.

For future research, it is recommended to quantitatively investigate the return on investment of real-time integration to build a stronger business case. Subsequent studies should also explore effective models for integrating key suppliers into the retailer’s inventory management system to create an end-to-end supply chain. Further academic inquiry could productively examine the impact of advanced analytics and machine learning on enhancing lean retailing by moving from reactive problem-solving to proactive waste prevention and demand anticipation.