The management of supply chains has long relied on reference frameworks to provide a shared language, structural coherence, and standardized performance measures. Among these, the Supply Chain Operations Reference (SCOR) model, developed in the mid-1990s, has established itself as the most widely applied and enduring standard in both academic research and managerial practice (Association for Supply Chain Management, 2025a). Over successive versions, SCOR has provided process definitions, performance metrics, and best practices that support supply chain design, benchmarking, and continuous improvement (Association for Supply Chain Management, 2025c; Bolstorff and Rosenbaum, 2003, 2012; Wang et al., 2016).

However, the accelerating pace of digital transformation, the integration of sustainability and Environmental, Social, and Governance (ESG) considerations, and the increasing complexity of global supply networks have placed growing pressure on SCOR to evolve beyond its traditional process-oriented focus (Ageron et al., 2020; Association for Supply Chain Management, 2025b,d; Huan et al., 2004; van Engelenhoven et al., 2023). These developments challenge established performance measurement systems (Santos et al., 2021) and call for frameworks capable of capturing digital enablement, orchestration, and multidimensional value creation across supply networks.

In response, ASCM introduced the SCOR Digital Standard (SCOR-DS) in 2019 as a substantial revision of the original model. SCOR-DS extends the framework by incorporating digital enablers, sustainability considerations, orchestration processes, and expanded performance management dimensions.

This review is structured around two complementary matters, discussed in Sections 1.2 and 1.3, namely an identified conceptual gap in the literature and practical challenges in operationalizing SCOR-DS.

Despite its relevance, academic engagement with SCOR-DS remains limited. The majority of existing SCOR-related studies focus on earlier model versions and emphasize sector-specific applications, such as healthcare, construction, and manufacturing, often through descriptive or case-based analyses. Moreover, prior research has essentially treated SCOR as an operational process-mapping tool, offering limited critical examination of its conceptual foundations or its integration with alternative frameworks, including the Global Supply Chain Forum model (GSCF; Lambert, 2008), the Design Chain Operations Reference model (DCOR; Yinbin and Hongbo, 2009), the Customer Chain Operations Reference model (CCOR; Chen and Pai, 2014), the Value Chain Operations Reference model (VCOR; Ouzrout et al., 2009), as well as Lean, Six Sigma, and digital twin-based approaches (Guo and Mantravadi, 2025).

As a result, in the literature, SCOR-DS has not yet been comprehensively examined as a distinct, conceptually and governance-oriented framework, despite its growing relevance in digitally enabled, sustainability-oriented supply chains.

Recent ASCM releases describe SCOR-DS as an evolution of the SCOR framework intended to support digitally enabled, resilient, and sustainability-oriented supply chains through expanded performance attributes, orchestration processes, and ESG considerations (Association for Supply Chain Management, 2025a,b,c,d,e,f). However, it appears challenging for practitioners to operationalize and measure SCOR-DS across different levels using these documents. In particular, while high-level performance attributes and selected benchmark metrics are outlined, the translation of orchestration, digital capabilities, and ESG dimensions into coherent operational and process-level performance indicators remains largely implicit. As a result, practitioners face practical challenges in implementing SCOR-DS as a comprehensive performance management framework.

This review makes distinct contributions that clearly differentiate it from prior SCOR-related reviews. Beyond consolidation, the conceptual novelty of this review lies in reconsidering SCOR-DS as a governance-oriented and digitally native framework and in focusing on the Orchestrate processes and KPI frameworks as a coordination and translation layer between strategic intent, ESG integration, and operational performance, an aspect not explicitly addressed in prior SCOR reviews. Unlike existing studies that mostly examine SCOR as a tool for analyzing and improving supply chain performance, this paper provides the first critical-conceptual synthesis explicitly focused on its digital successor, SCOR-DS. In doing so, SCOR-DS is treated as a framework fundamentally concerned with digitalization, sustainability, and ESG integration, rather than as an extension of SCOR 11/12, thereby explaining why SCOR-DS requires a distinct scholarly treatment separate from earlier SCOR versions. The review examines the novel structural elements introduced in SCOR-DS, most notably the Orchestrate processes, expanded performance attributes, and embedded ESG dimensions, which have not been explicitly analyzed in prior SCOR reviews. The paper advances the literature by proposing illustrative key performance indicators (KPI) frameworks that identify and discuss areas of SCOR-DS requiring further conceptual extension, thereby addressing a critical gap: while SCOR-DS introduces high-level performance attributes and selected benchmark-oriented metrics, it is not clear how its new digital, ESG, and orchestration dimensions should be translated into operational or process-level KPIs, a gap this study explicitly addresses. By articulating these contributions, the study positions SCOR-DS as a distinct scholarly object of inquiry and provides a foundation for future theoretical and empirical research on digital, resilient, and sustainability-driven supply chain performance management. By linking performance management theory with SCOR-DS, the review consolidates existing knowledge while extending it conceptually (Taticchi et al., 2015). Given the limited number of academic studies currently dedicated to SCOR-DS compared with earlier SCOR versions, this review makes a timely and substantive contribution to the literature. Table 1 provides a structured overview of how the proposed KPIs relate to the SCOR-DS, thereby highlighting one of the key novelties and contributions of this paper.

Considering both the conceptual gap and the practical challenges discussed in Sections 1.2 and 1.3, this review is guided by the following research questions:

To achieve these objectives, the study adopts a critical–conceptual review approach, integrating descriptive synthesis, critical evaluation, and conceptual development. This approach is particularly suited to SCOR-DS, where the academic literature is fragmented and practitioner-oriented sources play a central role in the development and adoption of the framework. Rather than relying on rigid protocols characteristic of systematic reviews, the review emphasizes conceptual coherence, theoretical positioning, and practical relevance, while explicitly recognizing expert judgment as part of the synthesis process (Baumeister and Leary, 1997; Grant and Booth, 2009; Jaakkola, 2020; Paré and Kitsiou, 2017; Snyder, 2019). Such an approach is appropriate for emerging domains where bibliometric or meta-analytic techniques remain premature.

The remainder of the article is organized as follows. Section 2 describes the methodology adopted for the review. Section 3 presents the results and discussion, structured into thematic subsections that synthesize and critically evaluate the SCOR and SCOR-DS literature, including comparisons with alternative frameworks and the identification of key gaps. Finally, Section 4 concludes the article by integrating the main findings, outlining implications for both research and practice, and highlighting directions for future research.

The literature search covered English-language sources published between 1996, corresponding to the initial release of the SCOR model, and 2025, reflecting the most recent ASCM updates. Keyword inclusion criteria encompassed four categories (Antony et al., 2003; Association for Supply Chain Management, 2025a,b,c,d,e,f; Bhandal et al., 2022; Chen and Pai, 2014; Chen et al., 2020; Di Domenico et al., 2007; Grubic et al., 2010; Mantje et al., 2016):

By contrast, the present review combines narrative synthesis, critical evaluation, and conceptual enrichment, positioning it as a critical-conceptual review (Teymourifar, 2025a).

Table 2 summarizes how this study's methodology compares to other review types.

This critical-conceptual approach offers several advantages (Jaakkola, 2020; Paré and Kitsiou, 2017; Snyder, 2019):

As mentioned earlier, while the SCOR-DS introduces new dimensions related to sustainability and orchestration, many associated performance measures remain underspecified. Thus, this paper conceptually extends SCOR-DS by proposing illustrative KPIs aligned with its process and performance dimensions.

As with all critical–conceptual reviews, the synthesis involves interpretive judgment, and selection bias can happen. Thus, alternative readings or KPI mappings may emerge as the SCOR-DS framework evolves and as empirical validation becomes available.

While SCOR-DS represents the most comprehensive and modern standard for supply chain operations, it nonetheless has notable limitations. Key areas that remain insufficiently addressed include demand management, product design and development, the broader value chain, value creation, continuous improvement, waste reduction, productivity and quality, benchmarking, and fully data-driven approaches. These dimensions are critical for achieving long-term competitiveness: for instance, product design and development directly shape supply chain performance by determining sourcing requirements, production complexity, and sustainability outcomes, while demand management links operational capabilities with customer expectations to reduce mismatches and inefficiencies. Similarly, practices such as continuous improvement, waste reduction, and benchmarking are essential for embedding learning, driving efficiency, and maintaining industry relevance in a rapidly evolving environment. To cover these gaps, alternative frameworks can be applied in practice, many of which emphasize areas that SCOR-DS only indirectly touches upon, such as product design, customer relationships, or end-to-end value chain integration. The most prominent examples are outlined below (Association for Supply Chain Management, 2025a,b,c).

Table 7 provides a structured comparison of how GSCF, DCOR, CCOR, VCOR, and Lean/Six Sigma address specific conceptual gaps identified in SCOR-DS.

The comparison of complementary frameworks highlights that SCOR-DS, while SCOR-DS provides a comprehensive framework for orchestration, performance attributes, and digital enablement, it does not fully address all supply chain dimensions; complementary frameworks such as GSCF, DCOR, CCOR, VCOR, and Lean/Six Sigma help fill gaps in demand management, design, customer-facing processes, and continuous improvement.

Another gap is that, despite its prominence, academic research has been slow to engage with SCOR-DS, and unlike its predecessors, it has not yet received systematic scholarly validation. Launched in 2019 and updated in 2022, the framework is still too recent to have generated a substantial body of peer-reviewed studies, particularly given publishing lags. Its proprietary origins under APICS/ASCM and practitioner-oriented design have further constrained scholarly uptake. Moreover, much of the literature on Industry 4.0, IoT, blockchain, and the digital twins conceptually overlaps with SCOR-DS but rarely cites the framework directly, limiting its visibility in academic discourse. In contrast, SCOR 12.0 remains the dominant reference point for traditional linear supply chains, thereby reinforcing the imbalance between established and emerging standards (Association for Supply Chain Management, 2025a,b,c).

As a result, most studies on performance measurement still focus on SCOR 11 or 12, framing KPIs around the traditional dimensions of reliability, responsiveness, agility, cost, and asset management. Only a limited number of peer-reviewed contributions explicitly map SCOR-DS processes to KPIs, leaving ASCM documentation and industry case reports as the primary sources of insight. This gap highlights a significant opportunity for scholars to theorize, validate, and advance SCOR-DS as a distinct framework for digital, resilient, and sustainable supply chains (Association for Supply Chain Management, 2025a,b,c).

This research gap is particularly salient with respect to KPIs. While SCOR-DS defines processes across Orchestrate, Transform, Order, Fulfill, and Return, it does not prescribe corresponding performance measures. As a result, organizations encounter uncertainty when selecting appropriate metrics for emerging domains such as ESG compliance, digitalization, and resilience. Addressing this limitation is both novel and timely. Developing a systematic, academically grounded KPI framework aligned with SCOR-DS processes would not only advance the model beyond the boundaries of SCOR 12 but also reinforce its position as a standard that embeds resilience and sustainability at the core of supply chain management. Such a contribution is not intended to modify the SCOR-DS model itself, which remains under ASCM's custodianship, but rather to generate new insights that enhance its academic interpretation and practical applicability (Association for Supply Chain Management, 2025a,b,c).

Although some researchers have questioned the effectiveness of KPIs in contexts such as healthcare management, this critique often arises from the complexity of healthcare delivery, where outcomes are shaped by diverse clinical, social, and humanitarian dimensions that are difficult to standardize or quantify. In such settings, KPIs may risk oversimplifying performance by emphasizing what is easily measurable rather than what is most meaningful, thereby neglecting patient-centered or qualitative aspects of care. By contrast, in supply chain management, the literature affirms the central role of KPIs, where they function as indispensable tools for performance assessment, benchmarking, and continuous improvement (Association for Supply Chain Management, 2025a,c). Accordingly, the development of clearly defined KPIs for SCOR-DS would represent a valuable contribution, bridging a gap in the academic literature while also offering practical guidance for organizations seeking to operationalize the framework. For such KPIs to be effective, they must adhere to several essential criteria, as summarized in Table 8.

In the following sections, we examine the key new elements introduced in SCOR-DS, illustrate their application with concrete examples, and propose potential KPIs to guide their effective implementation. The use of examples is intended to enhance clarity for both scholars and practitioners, addressing what we consider a weakness in the original SCOR-DS sources, where limited illustrative material reduces accessibility and practical understanding.

As noted earlier, SCOR-DS introduces several structural innovations that extend the model beyond SCOR 120′s linear architecture. Chief among these are the Orchestrate (OE), Transform (T), Order (O), Fulfill (F), and Expanded Return (R) process categories, which are critically examined in the following sections.

One of the most significant innovations in SCOR-DS is the introduction of Orchestrate. This new top-level process family focuses on governance and oversight of the entire supply chain system. Governance establishes rules, policies, and accountability, and oversight ensures monitoring for compliance and performance. Unlike SCOR 12.0, where these aspects were only loosely embedded within the “Enable” process, SCOR-DS elevates them into discrete capabilities. The Orchestrate category spans a broad set of activities. The following section reviews the Orchestrate elements, identified as OE1-OE13 (Association for Supply Chain Management, 2025c).

In the official SCOR-DS documentation, this element is described as the “Alignment of Supply Chain Strategy with Corporate Objectives,” reflecting a traditional top-down planning view in which corporate objectives set the direction for functional strategies. However, from a strategic management perspective, this phrasing is problematic, since strategy is generally considered the higher-level construct that guides the formulation of objectives. Objectives are typically understood as specific, measurable outcomes derived from and subordinated to strategy. For this reason, we adopt the alternative phrasing “Alignment of Corporate Objectives with Supply Chain Strategy,” which is more consistent with established strategy theory and emphasizes the supply chain's role as a driver of organizational direction rather than a purely derivative function. As indicated in the section on KPI suggestions, the objective is not to modify the SCOR-DS model, which remains under ASCM copyright, but to contribute new theoretical insights that enrich its interpretation and application (Association for Supply Chain Management, 2025c).

Supply chain strategy encompasses the long-term choices related to network design, sourcing, inventory policies, production modes, service levels, and technologies that collectively determine how the supply chain competes (Chopra and Meindl, 2019; Stadtler et al., 2015). The specific strategy pursued may vary according to the organization's competitive priorities (Skinner, 1969; Slack and Lewis, 2002). For instance, a strategy of service differentiation emphasizes superior customer service and tailored offerings; a sustainability strategy, defined here in the ESG sense and used consistently throughout this study, integrates environmental responsibility, social accountability, and governance practices into operations; while a resilience strategy focuses on ensuring adaptability and continuity in the face of disruptions (Porter, 1980; Carter and Rogers, 2008; Ponomarov and Holcomb, 2009). In contrast, corporate objectives denote broader enterprise-level goals that are typically time-bound and measurable.

In SCOR-DS, OE1 highlights the importance of aligning corporate objectives with supply chain strategies, thereby ensuring that operational decisions directly support the enterprise's long-term priorities. As an example, we suppose that the objectives of a corporation are growth, profitability, and market share. Growth can be aligned with service differentiation when superior customization and premium services expand demand, with sustainability when green products and responsible sourcing enable entry into new markets, and with resilience when continuity during disruptions sustains long-term expansion. Profitability aligns with Service Differentiation through higher-margin offerings, with Sustainability through the avoidance of compliance-related costs, and with Resilience through reduced disruption-related losses. Similarly, market share aligns with service differentiation by building competitive advantage, with sustainability by strengthening reputation and customer preference, and with resilience by maintaining reliable delivery when competitors falter (Association for Supply Chain Management, 2025b,c; Cavusoglu et al., 2001).

Based on the preceding discussion, one of this paper's focal points is to present examples of KPIs that measure the alignment between corporate objectives and supply chain strategies, as outlined in Table 9.

In SCOR-DS, OE2 ensures that supply chain strategies are translated into operational policies that guide consistent decision-making. Business rules can take various forms, including sourcing, inventory, production, fulfillment, sustainability, resilience, and financial rules. As an illustration, we present sourcing and procurement rules, showing how they can be aligned with organizational strategies and evaluated through relevant KPIs. These rules govern the selection, management, and evaluation of suppliers, thereby operationalizing the link between corporate and supply chain strategies.

Table 10 presents illustrative examples of how such alignment can be assessed (Association for Supply Chain Management, 2025c).

Improvement activities involve monitoring performance, conducting benchmarking, and implementing continuous improvement methodologies. In SCOR-DS, OE3 ensures that these activities are defined in accordance with supply chain strategies. For example, benchmarking and adopting best practices enable organizations to compare their performance against industry standards, identify capability gaps, and integrate emerging SCOR-DS practices into their operations to achieve superior outcomes. Table 11 presents illustrative examples showing how performance oversight and continuous improvement can be aligned with supply chain strategies and evaluated through relevant KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, Data, Information, and Technology Governance should not be treated as a purely technical or back-office function but as a strategic enabler. Its primary role is to support the realization of the organization's chosen supply chain strategies by ensuring that data structures, information flows, and technology systems are designed to reinforce strategic priorities. Table 12 presents illustrative examples of potential alignments with corporate strategies and the associated KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE5 emphasizes the integration of recruitment, training, workforce planning, and performance management with supply chain strategy. Employee capabilities are thus positioned not as supporting functions but as direct enablers of competitiveness. Table 13 presents illustrative examples of potential alignments with organizational strategies and the corresponding KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE6 emphasizes structuring contractual arrangements so that external relationships are aligned with, and directly reinforce, supply chain strategies. While not all agreements are external, for example, organizations may establish internal service-level agreements, our focus here is on external contracts (Teymourifar, 2019; Teymourifar and Trindade, 2023; Teymourifar, 2025b). By embedding strategic objectives into legally binding commitments, organizations ensure that suppliers, partners, and service providers actively contribute to differentiation, sustainability, and resilience. Table 14 presents illustrative examples of potential alignments and the associated KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE7 emphasizes that supply chain networks should be continuously designed, optimized, and stress-tested to ensure alignment with strategic priorities. Table 14 outlines how network design and scenario modeling reinforce different organizational strategies and how these alignments can be evaluated through relevant KPIs (Association for Supply Chain Management, 2025c).

Regulations set mandatory standards that organizations must meet. In SCOR-DS, OE8 highlights the importance of ensuring that supply chain strategies are aligned with external regulatory requirements. Table 14 summarizes how supply chain strategies can be aligned with regulatory obligations and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE9 emphasizes aligning risk management practices with supply chain strategy to ensure strategic objectives are achieved even under conditions of uncertainty. Risk management spans supply, demand, operational, financial, and cybersecurity domains, enabling organizations to proactively identify, mitigate, and monitor vulnerabilities in line with strategic priorities. Table 14 illustrates how risk management can be aligned with different supply chain strategies and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE10 emphasizes embedding ESG principles into supply chain strategy. ESG integration moves beyond compliance to become a source of resilience, differentiation, and long-term value creation. By incorporating ESG practices into supply chain design and execution, organizations ensure that sustainability is not treated as a marginal consideration but as a central driver of strategic performance. Table 14 outlines how ESG integration can be aligned with organizational strategies and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE11 emphasizes aligning enterprise-level planning processes with supply chain strategy. Enterprise-level planning encompasses frameworks such as Enterprise Business Planning (EBP), Integrated Business Planning (IBP), and Sales and Operations Planning (S&OP), which connect strategic, financial, and operational objectives across the organization. EBP provides an overarching structure that links corporate strategy with operational execution; IBP extends traditional S&OP by integrating financial and strategic perspectives; while S&OP itself focuses on balancing supply and demand at the tactical level. Within these frameworks, scenario planning and what-if analysis play a critical role by evaluating alternative futures and testing decision outcomes, thereby enhancing agility and resilience. Together, these processes ensure that corporate strategy is systematically embedded into daily decision-making across the value chain. Table 14 summarizes how enterprise business planning can be aligned with organizational strategies and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE12 highlights the importance of tailoring supply chain design and execution to the distinct requirements of customers, products, geographies, and channels. Rather than adopting a one-size-fits-all approach, segmentation enables the creation of differentiated supply chain models that directly support strategic objectives such as service differentiation, sustainability, and resilience. While segmentation and differentiated supply chain management are closely related concepts, segmentation is the analytical process of identifying distinct groups, whereas differentiated supply chain management involves operationalizing those segments through tailored strategies and structures. Table 14 summarizes how segmentation can be aligned with organizational strategies and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

In SCOR-DS, OE13 emphasizes integrating circular economy principles into supply chain strategy. By extending product life cycles, recovering resources, and designing for reuse, circular practices directly support sustainability goals, enhance resilience against resource scarcity, and differentiate firms in markets that value responsible production and consumption. Table 14 outlines how circular supply chain management can be aligned with organizational strategies and evaluated through illustrative KPIs (Association for Supply Chain Management, 2025c).

Replacing and expanding the former Make process, Transform broadens applicability to products, services, and maintenance contexts. It is subdivided into three categories: product transformation (T1), encompassing engineering, production, packaging, and asset management; service transformation (T2), which extends the model into service industries such as IT, consulting, and field services; and maintenance, repair, and overhaul (MRO), transformation (T3), supporting asset lifecycle management in industries such as aerospace and energy. This reconfiguration extends the SCOR framework beyond manufacturing, making it relevant for hybrid and service-oriented supply chains (Association for Supply Chain Management, 2025b).

We present an example from smart manufacturing and the automotive industry's after-sales ecosystem. In this case, a global automotive manufacturer illustrates how all three transformation categories (T1-T3) intersect within a single, integrated supply chain system.

This example illustrates how T1, as production efficiency, T2 as service responsiveness, and T3 as asset reliability are mutually reinforcing dimensions within a modern supply chain. Monitoring KPIs such as production cycle time, MTBF, and MTTR in parallel provides a holistic view of value creation across the full product-service lifecycle continuum.

The SCOR-DS model further divides the former Deliver process into two complementary streams. Order covers the receipt, validation, and processing of orders across business-to-business (B2B), business-to-consumer (B2C), and intra-company contexts, including functions such as quotes, payments, and cancellations. Fulfill, in contrast, addresses the execution of logistics activities: inventory picking, packing, scheduling, shipment, installation, proof of delivery, and invoicing. By separating these domains, SCOR-DS acknowledges the need to manage digital order management systems independently from physical fulfillment systems, especially in complex omnichannel environments (Association for Supply Chain Management, 2025c,e,f).

We present an example from order and fulfillment processes in omnichannel retailing. The division of the former Deliver process into distinct Order and Fulfill streams is particularly significant in this context, where coordinating digital and physical flows is essential for seamless execution.

By separating Order and Fulfill, SCOR-DS enables retailers to manage digital order management systems independently from physical logistics systems. This separation is especially critical in omnichannel environments, where customer experience depends equally on the accuracy and speed of order processing and the reliability of last-mile fulfillment. For instance, a retailer may achieve low order cycle times through advanced digital platforms yet still encounter challenges in on-time delivery if fulfillment capacity is constrained. Monitoring KPIs from both domains provides a comprehensive view of performance and customer satisfaction in omnichannel supply chains (Association for Supply Chain Management, 2025c,e,f).

The return process is also broadened significantly in SCOR-DS. While SCOR 12.0 treated returns primarily as the handling of defective products, SCOR-DS introduces more granular categories: product returns, service returns (e.g., service cancellations or adjustments), and MRO returns, which cover asset refurbishments and lifecycle extension. This expansion reflects the growing importance of reverse logistics and service flows, which are central to sustainability initiatives and to enhancing customer experience (Association for Supply Chain Management, 2025c,e).

Below, we present an example from the return processes of omnichannel retailing. As noted earlier, SCOR-DS broadens the scope of the Return process beyond the narrow focus on defective products in SCOR 12.0. It now differentiates among product returns, service returns, and MRO returns (Kamili and Nurcahyo, 2020), thereby recognizing the importance of reverse logistics and after-sales services for both customer experience and sustainability. Omnichannel retailing offers a pertinent context in which to illustrate these categories.

By distinguishing among product, service, and MRO returns, SCOR-DS captures the full complexity of reverse logistics in omnichannel retailing. This approach highlights returns not only as a cost factor but as a strategic enabler of customer satisfaction, sustainability, and value recovery. Organizations that manage returns effectively can strengthen customer trust, reduce waste, and unlock secondary revenue streams (Association for Supply Chain Management, 2025a,c,e).

Another gap in the literature concerns the lack of empirical validation of SCOR-DS performance measurement. Future studies should systematically assess the framework by surveying organizations that are currently adopting or experimenting with it to establish its practical effectiveness and reliability. In addition, applications of SCOR-DS in the literature mostly overlook logistics. Nevertheless, it should also be considered that, while logistics is undeniably an integral component of the supply chain, an exclusive focus on it risks undermining the core intent of SCOR-DS, which is to provide a holistic framework for end-to-end supply chain design and evaluation. Consequently, research should incorporate logistics within the broader supply chain perspective, consistent with the systemic orientation embedded in the SCOR-DS model.

As a final point, it should be noted that, as mentioned earlier, both the SCOR and SCOR-DS models have been developed as open frameworks, shaped by voluntary contributions from practitioners and academics across industries. This collaborative foundation strengthens the credibility, cross-industry applicability, and responsiveness to evolving managerial practices. However, openness in development does not equate to unrestricted reuse.

The ASCM, as the governing body of SCOR, distributes the SCOR-DS under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). Under this license, the model can be freely read, downloaded, and shared, provided that ASCM is properly credited; however, modifications or commercial redistributions are not permitted. This approach preserves the integrity and reliability of the SCOR-DS while maintaining it as a stable and authoritative reference for global supply chain management practice (Association for Supply Chain Management, 2025c,d).

It should also be noted that the official SCOR and SCOR-DS frameworks include visual schematics that illustrate their structural features and process hierarchies. Because these visuals are proprietary to ASCM and distributed under the license as mentioned earlier, they are not reproduced here. Nonetheless, the conceptual features they depict are discussed and analyzed in this review (Association for Supply Chain Management, 2025a,c,d).

Notwithstanding the aforementioned copyright and licensing restrictions, academic research remains free to critique, extend, or integrate the SCOR and SCOR-DS models with complementary analytical or decision-making methods, provided that proper attribution is given to ASCM as the copyright holder. Several studies have demonstrated such hybridizations (Majumder et al., 2020). Table 15 summarizes selected examples of merging SCOR with other analytical approaches. In the table, the acronyms are defined as follows: VSM (Value Stream Mapping), ABM (Agent-Based Modeling), MCDM (Multi-Criteria Decision-Making), AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), AHP (Analytic Hierarchy Process), BWM (Best-Worst Method), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), SWARA (Stepwise Weight Assessment Ratio Analysis), VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje), LARG (Lean-Agile-Resilient-Green paradigm), DEMATEL (Decision-Making Trial and Evaluation Laboratory), BSC (Balanced Scorecard), DEA (Data Envelopment Analysis), FDH (Free Disposal Hull efficiency method), PESTEL (Political, Economic, Social, Technological, Environmental, and Legal framework) and RFID (Radio-frequency identification).

For the SCOR-DS model, hybridizations have also been reported, such as SCOR-DS integrated with ANP (Naziro, 2025) and SCOR-DS combined with qualitative frameworks and expert interviews (Esposito, 2023).

For practitioners, this review highlights both the value and the limitations of adopting the SCOR-DS. On the one hand, SCOR-DS provides a structured framework that incorporates digitalization, sustainability, and orchestration processes, offering a more contemporary view of supply chain management than earlier SCOR versions. It helps organizations align processes, identify performance gaps, and communicate with stakeholders using a common language.

On the other hand, the findings suggest that SCOR-DS should not be applied in isolation. Its incomplete coverage of demand management, product design, and KPI specification means that organizations may need to supplement SCOR-DS with additional frameworks, such as GSCF for collaboration, Lean/Six Sigma for process improvement, or digital twin models for advanced simulation. Furthermore, because SCOR-DS remains largely practitioner-driven and undervalidated academically, managers should use it as a flexible reference rather than a prescriptive standard.

In practice, the most effective approach will involve adapting SCOR-DS to the organizational context, integrating it with complementary methodologies, and developing tailored KPI systems that reflect strategic priorities. By doing so, practitioners can leverage SCOR-DS as a platform for digital transformation and sustainability initiatives while mitigating its current conceptual and operational gaps.

In summary, the synthesis of the reviewed literature reveals that SCOR-DS represents a substantive conceptual shift toward digitally enabled, sustainability-oriented, and governance-driven supply chain management; however, its academic operationalization, particularly in performance measurement and KPIs, remains underdeveloped.

This review entails several limitations. First, the analysis includes practitioner-oriented and gray literature, such as ASCM documentation, which reflects the practitioner-driven nature of SCOR-DS but may introduce selection bias. Second, the study lacks empirical validation; accordingly, the proposed KPI frameworks, particularly those associated with the Orchestrate elements (OE1–OE13), are intended as illustrative and exploratory rather than as theory-derived or empirically validated measures. The author's interpretive judgments link SCOR-DS to the proposed KPI framework, which could be further strengthened through future theory-driven or empirical research. Third, although the review is intended to be critical–conceptual, it inevitably incorporates descriptive elements to outline framework structures and terminology. Finally, SCOR-DS itself is an evolving framework subject to future revisions, meaning that some observations reflect its current stage of development rather than definitive or stable characteristics.

The main conclusions of this review are grounded in several recurring patterns identified across academic and practitioner-oriented sources. The limited number of peer-reviewed studies explicitly addressing SCOR-DS, compared with the extensive literature on earlier SCOR versions, highlights a clear gap in scholarly engagement. The analysis of existing applications indicates that SCOR-based studies continue to rely predominantly on SCOR 11/12 constructs, reinforcing the limited exploration of SCOR-DS in academic research. While SCOR-DS, compared with SCOR, introduces expanded processes, performance attributes, and dimensions, these elements are largely specified at a conceptual level, with limited guidance on operational or process-level performance measurement. Together, these observations provide a clear evidentiary basis for the study's forward-looking conclusions regarding the need for empirical testing of SCOR-DS and further KPI operationalization.

The KPI structures proposed in this study are illustrative, which also inform future empirical and operational research. Building on the evidence synthesized and the limitations identified in the preceding section, future studies should empirically test the applicability of SCOR-DS across different industries and establish formal traceability and validation for the proposed KPI structures. Future works should also examine how SCOR-DS supports resilience, sustainability, and digitalization as supply chains continue to evolve toward network-based models. Beyond the supply chain literature, these directions are also relevant to research on sustainability governance, digital transformation, and performance management in several fields, such as healthcare management. In this regard, the discussions presented in this review may serve as a structured reference for integrating ESG and digital considerations into broader organizational decision-making.