This study aims to explore how lean six sigma (LSS) may enhance demand management to improve customer value in South Africa’s automotive aftermarket. It addresses the need for structured, customer-centred strategies in volatile, resource-constrained supply chains.
A qualitative single-case study in a South African automotive aftermarket parts distributor. Data were collected via semi-structured interviews with staff across supply chain, planning and procurement. Analysis, guided by lean theory and the resource-based view, examined how LSS principles align with demand management practices and value delivery.
Customer value was defined by participants as availability, price and service reliability. Demand management was acknowledged as central but hindered by fragmented metrics, reactive practices and limited visibility. While LSS was not formally adopted, it was recognised as a relevant tool for improving consistency, responsiveness and problem-solving. Leadership, internal capabilities and cross-functional collaboration were identified as critical enablers.
Findings are limited to one organisation and are based on perceived rather than observed LSS use.
Managers can use LSS to improve demand processes if supported by leadership and capability building.
This paper contributes practice-grounded evidence from a South African, service-oriented aftermarket context, clarifying the capability conditions, leadership commitment, analytical competence and cross-functional integration, under which LSS-aligned demand management supports value-oriented planning and fulfilment.
1. Introduction
The volatility of global markets requires organisations to adapt to changing customer requirements and operational constraints. Demand management has therefore become a strategic capability for aligning supply chain operations with customer needs while maintaining cost efficiency (Madhani, 2017). Although technologies such as predictive analytics have improved service levels and inventory optimisation, demand variability, long lead times and limited forecasting accuracy continue to undermine performance, particularly in complex and fragmented supply chains (Christopher, 2016; Croxton et al., 2001; Jean, 2024). If left unaddressed, these conditions drive operational inefficiencies, increase costs and weaken customer value delivery. Lean six sigma (LSS) is often positioned as a response, combining structured process improvement with waste and variability reduction to support reliable, customer-focused outcomes (Oladipupo et al., 2023; Mapanga, 2024).
The South African automotive aftermarket is a vital sector that sustains national mobility, supports employment and contributes to GDP (Naude, 2013; Moshikaro-Amani and Mahlangu, 2024). The regulatory environment, shaped by the Competition Act, the Consumer Protection Act and Competition Commission guidelines, operates alongside persistent structural pressures, including OEM-imposed constraints, infrastructure deficits, labour cost pressures and counterfeit parts. Smaller independent service providers are especially exposed due to limited capital and market concentration (Majola, 2020; Competition Commission South Africa, 2015; TRACIT, 2023; Naude, 2013). These conditions heighten the need for operational agility and customer-centric performance.
Despite these pressures, many distributors remain constrained by siloed processes, limited integration and reactive planning (Simon-Kucher and Partners, 2024; Hassan, 2024). LSS offers a route to address these barriers through structured methodologies that promote flow, reliability and continuous improvement (Ali et al., 2020; Swarnakar et al., 2020). However, empirical evidence on LSS in this specific context remains limited, particularly regarding how LSS supports customer value creation within demand-driven service environments and the internal capabilities required for sustainable implementation (Meilani and Samat, 2024; De Silva et al., 2024).
A further gap is the misalignment between internal efficiency metrics and external service outcomes. Firms often prioritise gross margin or inventory turnover while underemphasising customer-facing measures such as on-time, in-full (OTIF) delivery or lead-time reliability, limiting the extent to which internal gains translate into customer-visible value (De Oliveira-Dias et al., 2023).
This article forms part of a broader qualitative study conducted within a South African automotive aftermarket parts distributor. While the full research explored multiple dimensions of LSS, demand management and customer value, this article narrows its focus to two core research objectives: (1) exploring the nature and interplay of LSS and demand management and (2) investigating how LSS contributes to customer value creation in a resource-constrained, high-variability environment. In doing so, the article examines how LSS-enabled demand management may improve operational efficiency, strengthen strategic alignment and enhance customer value in the aftermarket distribution context.
2. Theoretical framework and literature review
This study is grounded in two theoretical lenses: lean theory and the resource-based view (RBV). Lean provides the operational framework for eliminating waste and maximising customer value, while RBV offers a strategic perspective on leveraging internal capabilities to sustain competitive advantage. Together, these frameworks support an integrated understanding of how LSS practices could influence demand management and customer value creation in complex, high-variability sectors such as the South African automotive aftermarket.
By combining Lean’s process focus with RBV’s emphasis on human and organisational capabilities, this study explores how LSS can be strategically embedded into demand management systems to drive customer-focused outcomes. The following sections examine each construct in turn, LSS, demand management and customer value, framing them within the dual theoretical context to identify enablers, constraints and synergies critical to effective integration.
To strengthen the link between LSS and customer value, lean and RBV are complemented with a service-oriented lens in which value is realised in use through reliable, responsive, low-effort encounters across demand and fulfilment interfaces (Khadka and Maharjan, 2017; Gligor et al., 2020). Within this perspective, customer value increases when operations consistently deliver perfect orders, short fulfilment cycles and agility (ASCM, 2020; Morales et al., 2021).
LSS operationalises this linkage by structuring cross-functional problem-solving and measurement so that process control translates into perceived service quality and loyalty (Chau et al., 2021; Patti et al., 2020). Accordingly, demand management becomes the interface where firm capabilities (RBV) and waste and variation reduction (lean) co-create customer value in service encounters (Davis and Simpson, 2017; Ambrosio-Flores et al., 2022).
2.1 Lean six sigma
LSS provides an integrated framework to address dual organisational goals, enhancing operational efficiency and delivering customer value. The combined application of lean principles, of targeting waste and six sigma tools, focusing on reducing process variability, has proven effective in managing complexity across supply chain environments, particularly in industries facing volatile and uncertain demand (Ambrosio-Flores et al., 2022). This dual approach enables organisations to transform inefficiencies into opportunities for sustained competitive advantage (Barker et al., 2019; Gnoni et al., 2017). When supported by LSS, demand management serves as a foundation for inventory optimisation, improved responsiveness and enhanced customer experience, especially in sectors such as the automotive aftermarket that require flexible and resilient supply chain strategies.
While lean and six sigma originated as independent methodologies, their integration under the LSS framework combines the best of both: lean’s focus on waste elimination and flow and six sigma’s data-driven approach to variation reduction (Singh et al., 2023a; Madhani, 2020). The integration is typically operationalised through the define, measure, analyse, improve, control (DMAIC) framework, which provides a structured roadmap for identifying, diagnosing and resolving performance issues (Trubetskaya et al., 2023).
Importantly, LSS also aligns with RBV theory by enabling firms to leverage their internal strengths, such as analytical talent, process maturity and data quality, as differentiators. When implemented effectively, LSS delivers performance improvements and the strategic alignment of internal capabilities with external customer requirements (Murmura et al., 2021). This integration enables firms to achieve operational efficiency and customer-centricity simultaneously, a key requirement in competitive, service-sensitive markets such as automotive aftermarket distribution.
2.2 Demand management
Effective demand management synchronises supply and demand by balancing forecast accuracy, flexibility and inventory efficiency (Chartered Institute of Procurement and Supply (CIPS), 2019). It reduces uncertainty, enables timely product availability and supports profitable service delivery. However, mismatched supply and demand, inaccurate forecasting and fragmented stakeholder collaboration frequently result in inefficiencies, cost escalations and suboptimal customer outcomes (Pinheiro et al., 2018; Tulokas, 2015). Furthermore, order fulfilment rates, lead times and cost-to-serve metrics have become increasingly relevant in measuring customer value (Ganesan, 2015; Kumar, 2018; Zhuo, 2019). Because suppliers, distributors and logistics jointly shape availability and lead times, unsynchronised planning amplifies demand signals upstream, fuelling bullwhip effects and service risk, especially in import-reliant South African contexts (Christopher, 2016; Jena and Ghadge, 2023; Ahmed and Kim, 2023; Yang et al., 2021).
In the South African automotive aftermarket industry, these dynamics are especially pronounced. This sector, which encompasses vehicle parts distribution, repair services and maintenance, is characterised by a wide array of SKUs, fluctuating demand patterns and reliance on imported components (Jacyna and Semenov, 2020). Demand is often driven by vehicle age, usage patterns and maintenance behaviours, creating uncertainty in forecasting and replenishment. The strategic application of LSS in demand management offers a practical route to manage these complexities by improving forecast accuracy, reducing excess stock and enhancing service delivery (Weraikat et al., 2019; Yang et al., 2020).
2.3 Customer value for aftermarket parts distributors
Customer value sits at the intersection of Lean theory and RBV. From a Lean perspective, value is defined strictly by the customer, requiring organisations to design and improve processes that directly contribute to customer satisfaction. From an RBV standpoint, customer value results from how effectively an organisation uses its unique internal resources to meet market needs. In both frameworks, the customer is central, not just as a recipient of goods and services, but as a strategic driver of how operations should be structured and resourced (Salazar and Armando, 2017; Arfmann and Federico, 2014).
LSS contributes to customer value by improving reliability, reducing lead times and lowering costs, factors that are increasingly cited in customer satisfaction and retention literature (Chau et al., 2021). Lean principles promote agility and responsiveness, while Six Sigma reinforces precision and consistency. They allow organisations to deliver service excellence in highly variable, cost-sensitive environments such as the South African aftermarket sector.
Metrics such as perfect order fulfilment, on-time delivery and cost-to-serve are common indicators of customer value outcomes. These metrics link operational performance directly to service expectations and business impact (ASCM, 2020; Gligor et al., 2020). The emphasis on responsiveness, agility and supply chain reliability also highlights the broader implications of LSS, extending its relevance beyond internal efficiency to market competitiveness and customer satisfaction.
2.4 Research gaps identified
To define the research gap for this study, a literature search was conducted using Scopus with specific title, abstract and keyword filters covering terms such as “Lean Six Sigma”, “demand management”, “customer value” and related inventory control concepts. The final review included 20 peer-reviewed articles published between 2009 and 2023, spanning a range of industries and methodological. While these studies provided valuable insight into Lean warehousing, inventory optimisation, disruption resilience and hybrid inventory models, most focused on manufacturing or broad supply chain environments. Only one article addressed the automotive aftermarket and none examined the South African context.
Critically, the integration of LSS with demand management to drive customer value remains underdeveloped. Many studies centred on operational efficiency improvements but overlooked customer-centric outcomes such as service responsiveness or availability. Furthermore, the South African automotive aftermarket remains an empirical blind spot, despite its supply chain complexity, import reliance and customer service challenges. This gap limits the availability of context-specific frameworks to manage demand volatility, inventory control and process inefficiencies in this sector; accordingly, this article foregrounds transferable, practice-oriented insights from field work rather than claiming theoretical novelty.
Most reviewed studies adopted quantitative or mixed methods that emphasised performance metrics while neglecting the human and behavioural factors affecting LSS and demand management implementation. Few explored how frontline teams experience or influence process standardisation, root cause problem-solving or demand alignment practices. In response, this article uses a qualitative, single-embedded case study design to foreground perspectives and organisational context, examining how the potential for LSS-aligned demand management practices may shape customer value within a South African automotive aftermarket parts distributor.
While all 20 articles contributed to shaping the theoretical lens, only the five most relevant studies are presented in detail within this article, in Table 1. Empirical studies in non-automotive manufacturing, health care, pharmaceutical and education were not included in the empirical synthesis because their customer-requirement profiles differ from those in automotive, spare-parts, logistics and demand management contexts.
Selection criteria were direct applicability to the automotive aftermarket context, empirical use of LSS and their focus on operational improvements linked to customer value. Collectively, these five studies offer high-value insights into warehousing, inventory management and demand strategies within comparable distribution environments, making them suitable for direct comparison with the case findings.
3. Methodology
This study adopted a qualitative methodology to explore the interplay between LSS, demand management and customer value within the South African automotive aftermarket. Given the limited prior research in this context, a single-case study design was selected to enable in-depth exploration of complex organisational processes. This section outlines the philosophical stance, design rationale, data collection and analysis procedures and ethical and methodological considerations underpinning the study.
3.1 Research philosophy and approach
This study was grounded in an interpretivist paradigm, which assumes that social reality is constructed through human experience and interaction and that knowledge is shaped by context and meaning (Creswell, 2014). This aligns with the study’s objective to explore how LSS principles and demand management practices are experienced and enacted within a specific organisational setting. Interpretivism allows for a deeper understanding of phenomena through the perspectives of those directly involved, making it suitable for unpacking complex supply chain interactions.
An exploratory, inductive approach was adopted to enable themes to emerge from the data, without relying on predefined categories, reflecting the limited prior work that integrates LSS and demand management in the South African automotive aftermarket. The study followed a qualitative logic of inquiry to gather rich descriptions from participant narratives and interpret organisational realities in situ (Creswell, 2014). Lean theory and the RBV were used as interpretive lenses to guide analysis without constraining coding, ensuring findings remained contextually grounded while critically engaging with relevant theory.
3.2 Research design
A qualitative case study design was selected to investigate the interrelationship between LSS, demand management and customer value in a bounded, real-world context. This approach enabled an in-depth exploration of organisational practices and underlying complexities that could not be captured through quantitative or experimental designs. The case study method was appropriate for generating rich, context-specific insights in a setting without prior research (Yin, 2014).
A single organisation operating in the South African automotive aftermarket parts distribution sector was purposefully selected. This setting was chosen for its relevance to the study objectives and complex supply chain processes requiring efficiency and customer responsiveness. The case was bounded by organisational, operational and geographic parameters, ensuring that data collection remained focused and manageable. The embedded case design allowed for multiple units of analysis across departments involved in supply chain, inventory, demand planning and customer service functions.
3.3 Introduction to the case study
This study adopts a single-case study design focused on Company X, one of South Africa’s largest privately owned automotive aftermarket parts distributors. Operating across both wholesale and retail markets with an extensive national footprint, the company provides a rich and relevant context for examining demand management complexities in a sector facing intensified pressures from an ageing vehicle parc, volatile customer demand and fragmented inventory dynamics. The South African automotive aftermarket sector, marked by rising vehicle maintenance needs and distribution challenges, requires adaptive strategies to balance availability, lead times and cost efficiency.
Company X embodies these sectoral tensions, as it contends with fluctuating demand, supplier disruptions and procurement inefficiencies despite a centralised supply chain model. Notably, the company has yet to implement structured continuous improvement methodologies such as LSS, presenting a critical gap in operational strategy. This research explores the potential for integrating LSS principles with existing demand management practices can support strategic optimisation, enhance supply chain resilience and deliver greater customer value within this complex and under-researched context.
3.4 Data collection methods
Semi-structured interviews were used to collect primary qualitative data from 12 participants across key supply chain, operations and customer-facing roles. This method enabled the exploration of lived experiences and contextual practices relating to LSS, demand management and customer value delivery. Participants were selected through purposive sampling, guided by maximum variation to ensure a broad representation of strategic and operational perspectives, including roles in inventory planning, shipping, S&OP, customer service and executive leadership. This sampling approach strengthened the transferability of findings across the case context.
Interviews were conducted via Microsoft Teams and lasted approximately 75 min each. A semi-structured interview guide ensured consistency across sessions while allowing flexibility for in-depth probing (Creswell, 2014). All interviews were audio-recorded with participant consent, transcribed verbatim and returned to participants for verification. Field notes were also maintained to support contextual interpretation and capture non-verbal cues. The data collection process concluded once thematic saturation was achieved, with no new insights emerging. This ensured the richness and sufficiency of the data set to support robust qualitative analysis.
3.5 Data analysis
Thematic analysis was used to examine the qualitative interview data, allowing for systematic identification of patterns across participants’ accounts related to LSS, demand management and customer value. Drawing on Braun and Clarke’s multi-stage analytical process, the analysis began with transcription and familiarisation, followed by inductive and deductive coding based on the study’s conceptual framework. Themes were then developed and refined to align with six analytical propositions that explored the interrelationships among firm capabilities, LSS practices, demand management processes and customer value outcomes. This structured yet flexible approach supported deep engagement with the data while maintaining coherence with the study’s theoretical constructs.
The coding process was supported by ATLAS.ti software, which enabled efficient organisation, visualisation and retrieval of data segments. Themes were developed in line with six theoretical propositions addressing the interplay of firm capabilities, LSS, demand management and customer value. While the interview guide had been designed to align with research objectives, the open-ended format allowed for the emergence of unexpected insights. An iterative coding process refined theme boundaries and verbatim quotes were retained to enhance authenticity and illustrate the operational context. The resulting thematic framework reflected both convergent and divergent perspectives and was sufficiently saturated to support rigorous interpretation. Triangulation was achieved through insights gathered across multiple participant roles, which strengthened empirical grounding and supporting theory-led explanations of LSS’s role in demand management.
3.6 Study validity and reliability
In qualitative research, validity and reliability are framed collectively as indicators of trustworthiness, encompassing credibility, dependability, confirmability and transferability. To address these dimensions, the study incorporated multiple safeguards across the research process. These included purposeful sampling of diverse roles in demand management, a standardised semi-structured interview guide and iterative questioning techniques. These approaches ensured consistency and contextual relevance in capturing participant insights. Triangulation of perspectives across functional areas such as planning, procurement, logistics and customer service enhanced the credibility of findings by validating themes through multiple data sources. Reliability was further supported through accurate transcription, audit trails and systematic use of Atlas.ti for transparent coding and thematic development.
To enhance confirmability, member checking was conducted during and after interviews to ensure responses were correctly interpreted and recorded. A summary of each transcribed interview was shared with participants for review, allowing them to confirm or clarify their statements. Verbatim quotes were retained to ground interpretations in participants’ voices. In addition, peer debriefing with the research supervisor provided independent validation of emerging themes, reducing potential researcher bias. Comprehensive record-keeping, including securely stored consent forms, transcripts and audit documentation, ensured traceability and rigour. Collectively, these strategies reinforced the trustworthiness of the study, supporting robust, credible and replicable insights into the interplay of LSS, demand management and customer value within the case organisation.
3.7 Ethical considerations
Ethical rigour was maintained throughout the study to ensure participant confidentiality and organisational data protection. Ethical clearance was granted by the Research Ethics Committee at the University of Johannesburg and written consent was secured from the organisation’s chief financial officer and merchandise executive prior to data collection. The case organisation operates in a competitive aftermarket environment, and therefore, all findings were reviewed and approved internally to safeguard commercial sensitivity.
Each participant was informed of the purpose, scope and voluntary nature of the study and signed a consent form confirming their rights to confidentiality and anonymity. No identifiable information or role-specific references were included in the analysis. Participation took place during working hours with minimal disruption and respondents were assured that their input would be used solely for academic purposes. The final research output was submitted to the approving executives for organisational validation and ethical alignment.
4. Findings
This section presents the empirical findings from the semi-structured interviews conducted at the case organisation. Using thematic analysis, the study explored how LSS, demand management and customer value are understood to interact within a South African automotive aftermarket parts distributor. Data from 12 participants, all employees of Company X, were analysed to understand how operational practices and perceptions align with or diverge from strategic objectives. Guided by the two focal research questions selected for this article, the analysis highlights the fragmented nature of demand management, the absence of formalised LSS practices and the implications for customer value. The findings are organised into six interrelated themes, each illustrating key operational dynamics and strategic gaps that influence performance outcomes in the case setting.
4.1 Profile of participants
A total of 12 participants employed at Company X were included in this study, each selected for their active involvement in demand management functions. The sample encompassed a diverse cross-section of roles, combining seven executive or senior managers (coded SM1 to SM7) with five experienced staff (coded ES1 to ES5), such as buyers and planners. These anonymised codes are referenced throughout the findings to preserve confidentiality while ensuring traceability of insights. This mix of strategic and operational roles enabled a multi-tiered view of how demand management operates within the organisation.
As summarised in Table 2, participants brought significant expertise in procurement, demand planning, inventory control, product and pricing strategy and supplier relationship management. Their working experience ranged from 12 to 40 years, with nearly all participants having deep exposure to both the automotive aftermarket sector and the case study organisation. This ensured that the data captured through the semi-structured interviews was contextually rich and reflective of both high-level strategy and day-to-day operational realities.
4.1 Emerging themes
This section presents the findings from 12 semi-structured interviews conducted at a South African automotive aftermarket parts distributor. Using thematic analysis, the study explored the interplay between LSS, demand management and customer value. Guided by research questions one and two, the analysis identified six interrelated themes that provide insight into current practices, perceptions and opportunities for LSS to support customer value through demand management.
The themes were developed inductively from the interview data and aligned deductively to the study’s theoretical propositions. Each theme is supported by participant quotations and contextualised through academic interpretation. The section is structured according to the two research questions, with three themes discussed under each. Table 3 summarises the relationship between the research questions, propositions, key findings and the thematic structure that follows.
4.1.1 Relationship between demand management and customer value.
The study revealed that demand management plays a critical role in shaping customer value by ensuring product availability, pricing competitiveness and service reliability. Participants highlighted that value is defined by customers as having access to the right products, at the right time and at a competitive price. While stock availability and pricing were consistently cited as top priorities, there was less emphasis on dimensions such as timeliness, product condition or targeting the right customer. Nonetheless, trust and fulfilment reliability were repeatedly mentioned as key drivers of loyalty and satisfaction.
Through the lens of the 7Rs framework, the findings illustrated that demand management at the case organisation is heavily oriented towards product placement and availability. Strategic inventory positioning, responsive procurement and accurate forecasting emerged as vital practices, although challenges such as limited pricing transparency and supply chain agility persist. Some participants expressed difficulty in adjusting prices due to gaps in cost visibility, which constrained responsiveness to market fluctuations and undermined value delivery.
The combined role of category management, procurement and planning was identified as essential to operationalising customer value. However, participants acknowledged that existing capability constraints, particularly in inventory planning and agile sourcing, limited the organisation’s ability to consistently meet expectations. Strengthening demand management processes, especially those related to responsiveness, stock reliability and cost efficiency, was viewed as a strategic necessity to maintain competitiveness and build lasting customer trust in the South African automotive aftermarket sector.
Taken together, these patterns align with service operations evidence that demand management practices translate directly into customer-visible reliability, responsiveness and price consistency, the drivers of loyalty and repeat purchase in services (Khadka and Maharjan, 2017; Patti et al., 2020).
4.1.2 Relationship between demand management and LSS.
Although LSS was not in practice at the case organisation, participants saw clear potential for its application within demand management. Once introduced to LSS concepts, they recognised how the methodology could streamline category management, procurement and inventory planning to improve stock availability and reduce inefficiencies. Participants suggested that LSS could enhance existing processes by introducing structure, data-driven decision-making and a focus on eliminating waste across planning and fulfilment workflows.
The feedback highlighted a strong alignment between LSS principles and the organisation’s operational pain points. Several participants noted that LSS could improve performance by reducing redundant tasks, enhancing interdepartmental collaboration and improving stock planning accuracy. Senior managers and experienced staff agreed that LSS would support more consistent order fulfilment, cost savings and better prioritisation of workload, all contributing to a more responsive and agile demand management approach.
The findings provide strong support for the view that LSS can influence demand management by enhancing process control, flow efficiency and resource utilisation. Participants also acknowledged that effective implementation would require investment in training and change management, yet viewed LSS as a viable enabler of improved demand planning and customer value. By integrating LSS, the organisation could reduce waste, improve responsiveness and align more closely with customer expectations, establishing a foundation for long-term operational excellence.
This potential maps onto established mechanisms whereby variation reduction and flow control improve planning accuracy and fulfilment stability, suggesting LSS would operate as a moderator that tightens the link between planning routines and outcomes such as on time and in full (OTIF) and cycle time (Kritsotakis et al., 2014; Morales et al., 2021).
4.1.3 Linking LSS, demand management and customer value.
Participants consistently emphasised that LSS could enhance customer value by refining demand management processes. Integrating LSS was seen as a way to improve product availability, responsiveness and cost-efficiency, key contributors to customer satisfaction. Building on prior insights, participants highlighted that aligning LSS principles with demand planning and execution would reduce inefficiencies and improve service reliability.
Senior managers such as SM1 and SM3 linked LSS to improved stock availability and pricing, with SM1 noting that customer satisfaction directly drives sales. Similarly, SM2 and SM4 highlighted that improved stock turnover and distribution workflows would lead to better service quality. Operational staff, including ES1, ES2, ES4 and ES5, pointed to faster turnaround times, leaner workflows and greater responsiveness as critical improvements enabled by LSS, with ES1 stating, “Being effective benefits the customer… it then ultimately becomes valuable.”
These findings indicate that in this context, LSS can drive operational excellence in demand management by reducing waste and enhancing agility. This, in turn, may strengthen the organisation’s capacity to deliver consistent, high-quality service at competitive prices, ultimately increasing customer value.
This potential maps onto established mechanisms whereby variation reduction and flow control improve planning accuracy and fulfilment stability, suggesting LSS would operate as a moderator that tightens the link between planning routines and outcomes such as OTIF and cycle time (Kritsotakis et al., 2014; Morales et al., 2021).
4.1.4 Metrics relating to customer value, demand management and LSS.
Customer value was primarily assessed through fulfilment and service reliability. Participants highlighted fill rate, stock availability and responsiveness as critical indicators. SM1 stressed the need to “fill that order immediately”, while SM2 and ES3 linked lost sales and repeat purchases to incomplete fulfilment. Loyalty and trust were seen as outcomes of consistent product availability and competitive pricing.
Demand management metrics focused on product availability, sales performance and supplier reliability. Sales data, both volume and value, were widely used to assess planning accuracy. Participants such as SM2 and SM4 pointed to sales as “telling the story”, while supplier OTIF performance and over/under-delivery trends were linked to inventory imbalances that undermined customer service.
LSS-related metrics included defect rates, returns, stock turnover and cycle times. SM5 and SM7 highlighted reduced claims and faster turnaround as signs of LSS success. Inventory turnover and resource efficiency were also tracked, with SM4 asking, “How much time is it freed up?” Participants agreed that while each area had unique KPIs, alignment through structured measurement could reconcile tensions between availability, waste and profitability.
Positioning these indicators within an LSS logic clarifies the mechanism: standardised measurement reduces process variability, which stabilises lead times and raises OTIF, outcomes associated with stronger perceived reliability and repeat purchase (Morales et al., 2021; Kritsotakis et al., 2014; Patti et al., 2020).
4.1.5 Capabilities relating to customer value, demand management and LSS.
Participants identified analytical thinking, communication and relationship management as core capabilities enabling customer value, demand management and LSS. Skills in data analysis were seen as foundational for forecasting, inventory alignment and identifying waste. Equally, transparent communication and cross-functional trust were considered vital to coordinating internal efforts and engaging customers effectively.
Technical knowledge and systems proficiency were also emphasised. Participants highlighted the need for strong product knowledge, ERP skills and literacy in planning tools to support efficient operations and accurate demand response. Collaboration with suppliers and cross-industry understanding were seen as essential for improving availability and streamlining processes.
LSS-relevant capabilities centred on process design, structured problem-solving and adaptability. Participants emphasised the need for formal training to enable LSS implementation and overcome change resistance. Leadership, proactive follow-up and strategic alignment were viewed as critical enablers of sustained customer value and operational excellence.
This capability configuration is consistent with service supply-chain accounts that link cross-functional coordination and disciplined problem-solving to improved planning fidelity and customer outcomes (Dreyer et al., 2018; Singh et al., 2023b).
4.1.6 Issues and challenges to achieve customer value.
Participants highlighted widespread resistance to change as a cultural and operational constraint impeding progress across customer value, demand management and a potential LSS deployment. Senior leadership reluctance, outdated mindsets and limited adaptability were noted as core obstacles to embedding process improvements and structured problem-solving initiatives. Change fatigue and scepticism regarding a new continuous improvement programme like LSS created hesitation, especially within demand management, further weakening alignment and responsiveness.
Stock availability, collaboration and leadership gaps were also cited as persistent barriers. Participants described how poor internal communication, siloed teams and delayed decision-making contributed to reactive operations and missed opportunities to resolve customer-facing issues. Weak accountability, lack of ownership and underdeveloped cross-functional coordination were seen to limit the organisation’s ability to respond quickly and deliver consistent value.
Structural and financial limitations added further complexity. Cash flow constraints, ineffective distribution centre processes and limited planning capability disrupted stock availability. They damaged customer trust: pricing inconsistencies and a lack of understanding of total cost to serve compounded these issues. The findings suggest that sustainable customer value creation requires integrated action across leadership, systems and culture to address these deeply rooted operational and strategic weaknesses.
Framed theoretically, these deficits represent missed opportunities to deploy LSS routines for variation control and coordinated flow, routines associated with improved OTIF, cycle time and planning accuracy in service settings (Morales et al., 2021; Kritsotakis et al., 2014).
The standardisation and variation-reduction opportunities highlighted in the case mirror service-sector evidence linking LSS routines to improved OTIF, cycle time and planning accuracy (Morales et al., 2021; Kritsotakis et al., 2014). These operational gains are associated with higher perceived reliability, responsiveness and price consistency, which underpin loyalty and repeat purchase in services (Khadka and Maharjan, 2017; Patti et al., 2020). LSS-enabled demand routines connect process control and cross-functional coordination to customer outcomes, as emphasised in service operations scholarship (Dreyer et al., 2018; Singh et al., 2023b). Accordingly, although the empirical setting is aftermarket distribution, the mechanism is transferable to other service contexts, including logistics, retail and financial services, where timeliness, accuracy and trust define value (Singh et al., 2023b; Khadka and Maharjan, 2017; Dreyer et al., 2018).
Accordingly, while the empirical setting is aftermarket distribution, the underlying mechanism, demand routines disciplined by LSS to deliver timeliness, accuracy and trust, accords with service contexts where these attributes define value (Singh et al., 2023b; Khadka and Maharjan, 2017; Dreyer et al., 2018).
5. Discussion
This study set out to examine whether, and in what ways, LSS could enable demand management and enhance customer value within a South African automotive aftermarket parts distributor. The findings corroborate and refine propositions in the literature by situating them in a real-world, under-researched context. The organisation studied operates in a fragmented, high-variability environment, with legacy systems and siloed functions contributing to poor demand visibility, reactive problem-solving and inconsistent customer value delivery. Through thematic analysis of 12 in-depth interviews, the research demonstrates that integrating LSS principles into demand management processes can transform these inefficiencies into structured, customer-centric capabilities.
This study is consistent with established accounts of Lean’s waste removal, Six Sigma’s variation reduction and LSS as a combined discipline aimed at improving reliability and responsiveness in supply chains (Found and Harrison, 2012; Hung Lau, 2012a, 2012b). In a distribution-intensive, service setting, the analysis suggests that demand management functions as the operational conduit through which LSS could translate into customer-visible outcomes, aligning with, while specifying, the mechanisms implied in prior work on demand planning and fulfilment (Dreyer et al., 2018; Jehan, 2021). The evidence from this case indicates LSS may operate primarily as a moderator: by standardising problem-solving and feedback routines, it can tighten the link between planning metrics and customer results, such as OTIF, claims/returns and repeat purchase, thereby complementing internal efficiency measures (Kritsotakis et al., 2014; Morales et al., 2021; Singh et al., 2023b; Patti et al., 2020). Finally, the prominence of agility under volatility extends prevailing LSS accounts by positioning adaptive response as a companion capability that may be necessary for sustaining value in aftermarket distribution (Castro and Jaimes, 2017; Soinangun and Asrol, 2022).
Regarding research question one, the data revealed a strong conceptual alignment between demand management and customer value. Participants consistently described customer value in terms of availability, pricing and fulfilment reliability, factors directly impacted by demand management performance. However, these functions were historically fragmented across departments, leading to poor execution and limited root cause visibility. The findings support existing literature that positions demand management as a strategic coordination process (Jehan, 2021; Dreyer et al., 2018), but contribute new insights by showing how its success is contingent on integrated practices and leadership engagement in the automotive aftermarket sector.
LSS emerged in participants’ accounts as a latent but potentially powerful enabler. Although not formally deployed, the principles of standardisation, root cause analysis and process visibility were recognised as necessary preconditions for meeting the service levels customers expect. Taken together, the case evidence suggests that when applied in a demand-centric context, LSS may operate as more than a cost-reduction toolkit. It can support agility, service consistency and value-based differentiation. Agility in particular was viewed as critical for responsiveness to volatile demand and frequent disruptions, a need well documented in the literature (Castro and Jaimes, 2017; Soinangun and Asrol, 2022), but rarely explored in this specific industry setting.
Research question two extended this understanding by evaluating how LSS could enhance customer value via demand management performance. The study findings indicate that, when introduced, LSS formalises metrics, routines and behaviours that improve planning accuracy, reduce fulfilment variability and align supply and demand. The participants highlighted quantitative indicators, such as forecast accuracy, OTIF, product availability and sales volumes, as key signals of customer value. These were reinforced by qualitative markers such as customer trust, relationship strength and internal accountability. Accordingly, LSS is positioned not only as a set of process tools but as a problem-solving discipline that can embed accountability and translate operational control into customer-facing benefits.
Importantly, this study addresses three major research gaps. Firstly, it contributes a demand-management–focused case study from the underexplored South African automotive aftermarket. Secondly, it provides empirical insight into how LSS could be integrated with demand management in a service-intensive distribution context, extending the discussion beyond manufacturing. Thirdly, it highlights leadership and cross-functional coordination as necessary enablers for translating operational improvements into customer-visible value.
For practitioners, this research offers practical guidance on applying LSS principles to address fragmentation, inefficiency and reactive culture, emphasising standardisation, feedback loops and cross-functional coordination. For scholars, it positions LSS as operating in conjunction with demand management as a capability set that can support competitive advantage through customer value while inviting further empirical testing in service-sector settings.
6. Conclusion
This study investigated the interplay between LSS, demand management and customer value in a South African automotive aftermarket parts distributor. Motivated by persistent misalignment between internal processes and fluctuating customer demand, the research used qualitative case study methodology to examine how demand management activities support customer value and how LSS may enhance this support through structured process improvement. Anchored on Lean Theory and the RBV, the study considered how firm capabilities, such as data literacy, cross-functional coordination and leadership, enable the integration of continuous improvement into customer-oriented service delivery.
The findings show that customer value is predominantly defined by product availability, competitive pricing and fulfilment reliability. Demand management emerged as central to these outcomes through its influence on forecasting, procurement and inventory control. However, execution is hindered by fragmented processes, inconsistent metrics and limited visibility across functions. Although LSS had not yet been formally implemented at the case organisation, participants recognised its potential to address these barriers. LSS principles, notably waste reduction, process standardisation and continuous improvement, were viewed as compatible with demand planning and fulfilment functions, with the potential to strengthen consistency, responsiveness and decision-making.
Notably, the study found that effective LSS integration requires more than tool deployment; it demands enabling conditions such as leadership commitment, analytical competence and cross-functional collaboration. These findings support the RBV’s assertion that internal resources must be embedded in organisational routines to deliver sustainable performance gains. The relationship between LSS, demand management and customer value is therefore best understood as synergistic rather than sequential, with aligned processes, capabilities and performance goals reinforcing one another.
This research is applied and exploratory rather than theory-building. It does not claim novelty; instead, it situates established perspectives in context. Firstly, rather than extending Lean Theory, the case illustrates how flow-based principles may be interpreted in a volatile, customer-driven service environment. Secondly, rather than operationalising RBV as a new contribution, the analysis maps RBV constructs onto observed capabilities such as structured problem-solving, data utilisation and departmental integration, which appear relevant to LSS within demand functions. Thirdly, instead of claiming to fill a gap, the article offers case-based reflections from a developing-market service supply chain, highlighting how contextual realities, legacy systems, cultural inertia and financial pressures shape LSS readiness and potential impact.
For practitioners, the study underscores the importance of consistently defining customer value across departments and tracking it through shared metrics such as OTIF, inventory availability, pricing agility and sales conversion. Managers should treat LSS not only as a cost-reduction initiative, but as a customer-focused improvement approach. Embedding tools like value stream mapping and root cause analysis into routine planning and procurement processes may foster discipline and accelerate issue resolution. Leadership must also address behavioural barriers through structured change management, capability building and role modelling of continuous improvement behaviours. Finally, financial constraints must be managed through integrated planning that balances working capital with service continuity, potentially through vendor-managed inventory or collaborative supplier models.
Despite its contributions, the study has limitations. It is based on a single case in a single organisation, which limits generalisability. Future research should address this by conducting comparative case studies across sectors and regions to test the consistency of the findings. Secondly, participants’ insights into LSS were based on perception rather than lived experience. Longitudinal research that tracks actual LSS implementation over time would enable empirical validation of anticipated outcomes. Thirdly, the study only captured internal views; future work should include suppliers and customers to provide a fuller understanding of value creation across the supply chain. Finally, the study offers a static view of a dynamic operational context. Future research could examine how performance evolves post-LSS adoption and how technological enablers, such as predictive analytics and AI forecasting, integrate with LSS in real-time decision-making environments. These avenues would enrich our understanding of LSS applicability and adaptation in demand-driven, resource-constrained industries.
Overall, the study underscores the potential of structured improvement methodologies to enhance demand management and customer value in the automotive aftermarket. In competitive and cost-sensitive environments, integrating LSS into planning and fulfilment processes may be a strategic consideration rather than a proven imperative. When supported by leadership and embedded in organisational routines, LSS offers a plausible pathway to greater responsiveness, efficiency and customer satisfaction, ultimately enabling organisations to deliver sustainable value in complex service ecosystems.
