Supply chain control tower implementation: overcoming challenges and driving success in large multinational companiesAbstract
Paper aims To provide a framework for Supply Chain Control Tower (SCCT) implementation, based on socio-technical systems, innovation adoption, and organizational information processing theories. The framework outlines seven key implementation phases, associated with eleven challenges and fifteen critical success factors (CSF).
Originality There are few studies to support SCCT implementation. This work proposes the integration of challenges faced by large multinational companies with the recent literature to develop a framework for the accomplishment of Control Towers (CT).
Research method Convergent Mixed Methods research is deployed. A scoping literature review and the content analysis of qualitative interviews in three large multinational companies are gathered to perform the analyses.
Main findings There are gaps between theory and practice, particularly regarding objectives, capabilities, and organizational areas involved in SCCT projects. The study identifies information misalignment across departments as a primary driver of Control Tower adoption. Also, the end-to-end SC monitoring and machine learning tools often emerge as a secondary initiative within SCCT projects.
Implications for theory and practice SCCT definition, capabilities and implementation steps are presented. The proposed framework can be used by practitioners to assess their internal readiness, identify and mitigate common adoption barriers, and strategically align SCCT with the CSFs goals.
Keywords:
Control tower; Socio-technical systems; Technology implementation; Digital transformation; Logistics 4.0
1. Introduction
Global supply chains are increasingly subject to challenges, including demand volatility, geopolitical tensions, and weather-related disruptions (Nadar et al., 2026). As technology's capabilities expand, new solutions have emerged to address these complexities in supply chains. Among these advancements, Supply Chain Control Towers (SCCTs) stand out as a cutting-edge approach, leveraging real-time data and Industry 4.0 technologies to provide visibility and proactive management across supply chains (Maheshwari et al., 2024).
Today, the expected SCCT capabilities include centralized solution that provides real-time visibility (Saurav, 2023; Trzuskawska-Grzesińska, 2017) with rapid response across supply chains (Dwiyana et al., 2022). These capabilities are achieved through the use of Industry 4.0 technologies such as IoT (Internet of Things), Cloud Computing, Big Data, Blockchain, Artificial Intelligence (AI), and machine learning (ML) (Correa et al., 2020; Wyciślak & Pourhejazy, 2023; Li et al, 2024; Bhoite & Buktar, 2025). Despite this progress, the literature about SCCT remains limited and dispersed (Chaffin et al., 2024; Nadar et al., 2026).
Technology is critical to unlocking SCCTs’ full potential, but it is insufficient without organizational structures and processes in place to ensure synchronization (Chaffin et al., 2024). Most companies are still in the early stages of their efforts to connect the entire value chain with a seamless flow of data (Malmstedt & Bäckstrand, 2022; Wyciślak & Pourhejazy, 2023).
Some companies outsource SCCTs, but others are motivated to proceed with their own SCCT implementation project due to the high costs of outsourcing and the potential benefits from optimizing supply chain processes (Vlachos, 2023). In a SCCT implementation process, it is essential to acknowledge the challenges (barriers) companies can face (Liotine, 2019; Maheshwari et al., 2024) since it must be carefully managed to ensure the success factor (SF) of the project. Chaffin et al. (2024) propose Critical Success Factors (CSFs) for SCCTs based on the literature, but it was not evaluated during the implementation process.
Some studies regarding SCCT implementation have been discussed in academic literature, but few provide details about the challenges and success factors in each step, especially considering practical applications. Several authors ask for more research on this topic. Vlachos (2023) affirms that there is a lack of empirical evidence on how companies should design and implement a SCCT; the development and implementation of SCCT remain in their early stages. Wycislak (2023) confirms that there is evidence of gaps between the theory and practice of SCCT applications in real-world companies, creating the need for further investigation. To the best of our knowledge, no previous study has examined SCCT project implementation in several companies. Previous studies often focus on case studies and on specific aspects, such as the structure of control towers (Ye et al., 2022) or tactical and operational decision-making (Topan et al., 2020), without presenting all the necessary interfaces and capabilities for a complete implementation.
In this perspective, this work proposes a framework for SCCT implementation, associating the challenges and critical success factors with each SCCT implementation step. The framework provides managers with a broad view of challenges to overcome and success factors to seek in SCCT implementation projects. Theoretically, the framework contributes to the discussion of the interaction among Organizational, Process, and Technology challenges/success factors.
This research is organized through four objectives that are the direct sequel to this goal:
RQ1- What is the current definition of SCCT and the associated capabilities? The SCCT definition aims to help managers to target the best CT scope and develop the right capabilities to achieve the results (critical success factors – CSF).
RQ2 -What are the main areas that should be involved in SCCT projects? Large multinational companies frequently face "functional silos," i.e. vertical and horizontal structures that can act as communication barriers and hinder internal collaboration (Kanyepe et al., 2025). Building a CT requires engaging the right skilled expertise team and designing interfaces to all partners in the supply chain (Trzuskawska-Grzesińska, 2017). Thus, it is important to understand which company areas should be included in the project.
RQ3 - How should the SCCT implementation process be designed? Due to the failure rate of digital transformation projects, a structured roadmap for complex systems such as SCCT is suggested (Agrawal et al., 2021). The objective is to propose, from the literature and case studies, the main phases of SCCT implementation.
RQ4 - What challenges and success factors are present in each phase of SCCT implementation? The association can provide managers with historical information, which can help them manage risks and avoid project failure.
To achieve the above research goals, the work first performs a scoping literature review using the PRISMA Protocol. The idea is to gather: (i) characteristics (definitions), (ii) capabilities (competences), (iii) areas involved in SCCT projects, (iv) barriers/success factors, and (v) previous frameworks for SCCT implementation. Second, qualitative interviews were carried out with three SCCT projects in large companies, and the same five variables have emerged from practitioners. Third, the confrontation between theory and practice allowed the development of the framework.
The main theories used in prior work also support the development of the framework proposed in this research. The Socio-technical system (STS) theory, since organizations and supply chains are complex systems, and their performance emerges from interactions among technology and people (Appelbaum, 1997; Vlachos, 2023). The Innovation Adoption (IA) theory is recognized as the theoretical ground for new technological innovation implementation in SCM (Vu et al., 2023). The Organizational-Information Processing theory (OIPT) is used as a theoretical lens, since the companies must know how to organize and use their information effectively to enable decisions involving a high level of uncertainty and risk (Gupta et al., 2019; Srinivasan & Swink, 2018).
The rest of the paper unfolds as follows. Section 2 presents the methodology employed in this work, while Section 3 presents the literature review analysis. Section 4 addresses the practical SCCT applications in companies, and Section 5 proposes the SCCT framework with a discussion of the main findings from the literature and practice. Finally, Section 6 addresses the concluding remarks and future research suggestions.
2. Methodology
This work used Convergent Mixed Methods research designs, which consist of a “quantitative and qualitative stage conducted independently of each other but come together at the end for interpretation (point of integration), with the aim of providing a “holistic view” of the research phenomenon” (Grant et al., 2023). In this work, the RQs require a clearer understanding of five main variables: SCCT definitions, capabilities, areas involved, barriers/success factors, and implementation steps. Based on these variables, the scoping literature review and qualitative interviews are conducted independently (Stages 1 and 2 of Figure 1). In Stage 3 (Figure 1), theory and practice are compared (Stage 5) and the insights from Stages 2, 4 and 5 are integrated into the development of the conceptual framework for SCCT implementation (Stage 6). Each of the six steps is detailed in the following sections.
2.1. Stage 1 – Scoping review
In the first stage, the methodological principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review (PRISMA-ScR) were applied, following the guidelines outlined by Tricco et al. (2018). This methodology, an extension of the PRISMA guidelines for systematic reviews, allows the synthesis of evidence on a specific topic, identification of research gaps, and assessment of the scope of literature.
The PRISMA protocol was operationalized in Scopus and Web of Science databases in May 2025 through the steps shown in Figure 2. The scoping review in this study focuses on the term "Control Tower", resulting in a raw portfolio of 234 articles. After the usual procedures of applying filters and removing duplicates, the main criterion used for article inclusion was the context of "Supply Chain". The final portfolio consisted of 32 articles for analysis, which highlight the novelty of the subject in literature. The systematic analysis of BP articles is performed to extract the five variables related to RQs. Sections 3.1 and 3.2 detail the findings related to SCCT (i) definitions, (ii) capabilities, and (iii) areas involved. Given the limited number of studies addressing the variables (iv) critical success factors and (v) implementation steps, the relevant findings were incorporated directly into the development of the framework. The research directions found in the BP and related to the study are included in the conclusions section.
2.2. Stage 2 – Qualitative interviews
The second stage of the study performed semi-structured qualitative interviews (Castka & Searcy, 2021), an approach that combined guided questions with opportunities for open discussion. In this work, the five variables (SCCT definitions, capabilities, areas involved, barriers/success factors, and implementation steps) are used as topics to guide the open-ended questionnaire construction. Two researchers were present during the interviews to clarify misunderstandings and to reduce bias in information interpretation. Each answer was documented, and the content analysis of the interviews employed a qualitative method with an inductive approach. Appendix 1 presents the rationale for the coding procedures adopted.
Interviews were conducted in Brazil with representatives from three large multinational companies, anonymized as Companies A, B, and C, to maintain confidentiality. These companies were selected based on the following criteria: (i) a large multinational company (>250 employees) (Organisation for Economic Co-operation and Development, 2024), (ii) to have a CT project implemented or underway; (iii) willingness to share their experience with this supply chain transformation; (iv) involvement in diverse sectors (mining, refrigeration and engine markets, and civil construction), offering a broad view of SCCT implementation across different industries. Table 1 shows the characteristics of these companies and the interviewees.
The interviewees are from company departments related to the SCCT scope. Thus, the interviews were conducted with professionals who: (i) work inside the control tower or in departments that use the control tower outcomes; (ii) have participated in or have information to share about control tower project implementation. The interviews aimed to identify as much information as possible about the process of CT implementation and use in the company.
The interviews had a one-hour duration, approximately. Employee 1 underwent two interviews: one conducted online and the other in person. This approach afforded the authors a real-time observation of the control tower. The interview with Company B was conducted online with one of the SCCT focal points, identified as Employee 2, who also allowed the viewing of the tower. Employees 3 and 4 were interviewed at different times, and each shared insight into their respective interactions with CT.
2.3. Stage 3 – Framework development
In step 5 of Figure 1, a comparative analysis between literature and practice is performed, as detailed in Section 4. This analysis takes into account the independent findings from the scoping review and the qualitative interviews. First, empirical data are categorized according to the SCCT implementation phases. Second, the reported capabilities and organization areas (variables ii and iii) are contrasted with the bibliographic portfolio to identify gaps between academic theory and industrial reality.
In Step 6, the results are integrated to support the development of the SCCT implementation framework presented in Section 5. While the comparative analysis focuses on the first three variables, this stage synthesizes all five variables by qualitatively connecting (iv) barriers/challenges and (v) critical success factors (CSFs) with each specific implementation phase. As shown in Appendix 1, this construction follows a rationale that establishes the relationship between the Research Questions (RQs), interview questions, and the resulting framework components.
3. Literature Review Results
3.1. Control tower types and definition
Due to the increasing heterogeneity in terminology and scope of control towers observed across academic publications, Table 2 consolidates current CT definitions. It highlights how monitoring scopes vary from specialized models (e.g., SCT for after-sales) to comprehensive Supply Chain Control Towers (SCCT). However, there is a consensus in the literature that Control Towers perform two fundamental functions: monitoring and control (Ye et al., 2022).
Originally derived from aviation, CTs have evolved from logistics-focused tracking (LCT) to sophisticated Digital and Supply Chain Control Towers (DCT/SCCT). Modern definitions incorporate end-to-end (E2E) visibility, big data analytics, risk management, and digital twin architectures to mirror physical flows and support complex planning (Patsavellas et al., 2021; Malmstedt & Bäckstrand, 2022, Vlachos, 2023, Chaffin et al., 2024).
This progressive conceptual expansion suggests that terms such as Digital Control Tower (DCT) and SCCT may be used interchangeably. The convergence of SCCT capabilities with those of Intelligent SCCTs and Supply Chain Digital Twins also reflects this alignment.
Given the terminological variety and conceptual fragmentation observed in the literature, there is a clear need to consolidate a comprehensive definition of Supply Chain Control Towers. Synthesizing these insights from existing literature, this study proposes the following conceptualization:
A Supply Chain Control Tower is a digital and intelligent technology-enabled platform that integrates real-time data, advanced analytics, and organizational knowledge to provide end-to-end visibility, automate decision-making, resilience and coordination planning and execution across supply chain functions.
This definition integrates foundational characteristics such as enable proactive management and dynamic alignment among multiple stakeholders (Wyciślak & Pourhejazy, 2023); improve operational efficiency (Stroumpoulis & Kopanaki, 2022), strengthening resilience in supply chains (Hida Syahchari et al., 2022) real-time monitoring and visibility (Yan et al., 2012), orchestration of data-driven decision-making processes (Liotine, 2019; Vlachos, 2023), adoption of digital twin architectures (Maheshwari et al., 2024), and responsiveness to supply chain risks and disruptions (Malmstedt & Bäckstrand, 2022; Chaffin et al., 2024). The proposed definition provides a consistent conceptual basis for the subsequent framework presented in Section 5 and serves as a reference for future academic and practical applications.
3.2. Supply chain control tower capabilities and areas involved
To evaluate Supply Chain Control Tower (SCCT) implementation in large multinational companies, it is important to identify the key capabilities that characterize control towers and the main organizational areas involved in SCCT projects. The term capability has been used in literature to denote competencies (Chaffin et al., 2024). The portfolio synthesis, detailed in Appendix 2, identified 13 competencies and 10 areas involved as stakeholders in SCCT projects.
The analysis of the bibliographic portfolio revealed that the most frequently cited capabilities include integrated technology (83.9%), real-time visibility (80.6%), monitoring (67.7%), and collaboration (64.5%). The integration of systems is still one of the bottlenecks in technology implementations in companies (Liotine, 2019). For SCCT, data exchange and system interoperability are necessary to support real-time decision-making and process optimization (Sharabati et al., 2022).
Traditional performance evaluations tend to be replaced by real-time monitoring of KPIs in Logistics 4.0 environments (Götz et al., 2023). Real-time visibility stands out as a strategic capability, as it underpins other capabilities, such as notifications/alerts, tracking and real-time decision-making (Verma et al., 2020). Product traceability is usually associated with Bar Codes, QR codes, and RFID (Kersten et al., 2024). It reflects the increasing demand for dynamic, data-driven control mechanisms that enable agile responses to disruptions and variability across the supply chain (Yan et al., 2012).
Regarding the business areas involved in SCCT implementations, they are less cited in the literature. Appendix 2 demonstrates a focus on Transportation (54.8%), Planning (38.7%), and Warehousing, Order Processing and E2E (32.5%). The focus on transportation likely derives from its high operational cost and strategic relevance for logistics efficiency (Vlachos, 2023). However, a comprehensive SCCT deployment requires significant investment in infrastructure and capabilities across the supply chain ecosystem (Malmstedt & Bäckstrand, 2022). This relatively uneven distribution might suggest that SCCTs are still being developed with a partial scope and limited integration across supply chain domains (Topan et al., 2020).
Thus, the literature supports that technological integration, real-time visibility and monitoring are critical capabilities in SCCT implementation projects, that should come associated with the involvement of multiple business functions to realize full SCCT potential. While this section focuses on variables (i) definitions, (ii) capabilities, and (iii) areas, the variables (iv) barriers/success factors and (v) previous frameworks found in the literature review were integrated directly into the development of the framework in Section 5 due to the dispersed nature of existing studies on these specific points.
4. SCCT projects in companies – Comparison between theory and practice
This section analyzes how SCCT projects have been designed and implemented in three companies, comparing practical applications with the definitions and capabilities identified in the literature. The comparison highlights how each company has operationalized SCCT concepts, revealing patterns, divergences, and context-specific adaptations. Table 3 associates the five variables of RQs with the context of the questions deployed in interviews. Appendix 1 presents the established connection reported in Table 3. Moreover, Table 3 classifies the empirical findings according to the SCCT implementation phases issued from Vu et al. (2023), Vlachos (2023) and Chaffin et al. (2024). These phases are also used in the proposed framework (Section 5). The corresponding project phase for each company was based on the theoretical phases and the status of CT provided in interviews. Additionally, the type of control tower adopted by each organization was determined based on its alignment with the typologies previously described in Table 2.
Control Tower application in companies – Interviews’ content classified according to each SCCT implementation phase.
The control tower implemented by Company A is classified as a Logistics Control Tower (TCT), in accordance with the characteristics defined by Alias et al. (2014b) and Alacam & Sencer (2021). In contrast, Companies B and C display features consistent with Digital Control Towers (DCTs), particularly in their data-driven orientation, as discussed by Sharabati et al. (2022). However, neither company has yet incorporated real-time tracking capabilities or visibility layers, which are considered essential for responsive and agile decision-making (Yan et al., 2012). This gap reveals a partial implementation of SCCT principles, limiting the scope and functionality of the systems in practice.
These findings suggest that, despite being large multinational companies, they still face substantial challenges in aligning their SCCT projects with the conceptual and technological standards identified in the literature. This observation is consistent with the arguments presented by Malmstedt & Bäckstrand (2022), who emphasize the need for significant investment and structural readiness to achieve comprehensive, end-to-end SCCT implementations.
Table 4 presents a comparative analysis between the SCCT capabilities and organizational areas identified in the literature, (summarized in Appendix 2), and the practices observed in the companies studied. In terms of capabilities classifications, the notifications/alerts of Table 4 means that information is given in case of problems occurred during the process. However, this classification is separated from real-time monitors because the alerts could not be received on-time, they can be updated after delivery, for example, or just when the system is update. It means that the company can have a real time monitor, for example, but no alerts are generated in case of irregularities. Also, the company can track the products (for example via QR code) but the information is updated 2 times per day, which means that the monitor is not real time. Table 4 also synthesizes the levels of decision-making supported by each SCCT project and the extent to which digital technologies have been adopted. This comparison supports a deeper understanding of how theoretical expectations are being translated into operational realities across different organizational contexts.
Table 4 reveals some gaps between theoretical expectations and current practices observed in the companies analyzed. Regarding SCCT capabilities identified in companies, no evidence was found of notifications/alerts, inventory-level control, or forecasting functionality. The absence of inventory-related features may be justified by the fact that warehouses were not included in the scope of the projects. Notifications and forecasting capabilities are typically present in more mature SCCTs, particularly those that incorporate big data analytics (BDA), machine learning, and artificial intelligence. In case of Companies B and C, there is a lack of robust tracking systems and risk management mechanisms, limiting their ability to support proactive and agile responses.
In terms of organizational areas involved, functions such as warehousing and end-to-end (E2E) supply chain management were not identified in the cases examined. Conversely, Companies B and C, both operating Digital Control Towers (DCTs), reported the inclusion of departments such as Human Resources, Information Technology, Safety, Maintenance, and Finance. These findings suggest that depending on the control tower’s strategic focus, different departments may become key stakeholders.
Regarding decision-making levels, Company B stands out for integrating strategic, tactical, and operational dimensions, while Companies A and C concentrate primarily on tactical operations. From a technological standpoint, Company A demonstrates a more advanced level of integration, employing tools such as ERP systems and smart monitoring cameras, which contribute to higher SCCT maturity. In contrast, Companies B and C exhibit more limited technological adoption, restricting their capacity for real-time visibility and comprehensive risk assessment.
Overall, the analysis indicates that while all three companies have established initial SCCT frameworks, their implementations differ significantly in scope, depth, and technological sophistication. Company A appears more aligned with SCCT models of the recent literature, whereas Companies B and C remain in earlier stages of development.
5. Framework for implementing a supply chain control tower
The implementation of a SCCT demands a structured, phased, and systemic approach that considers not only the technological aspects but also the organizational and process-related complexities involved. Drawing from the theoretical foundations of Innovation Adoption (Vu et al., 2023), Organizational Information Processing Theory (Chaffin et al., 2024), and Socio-Technical Systems Theory (Vlachos, 2023), a comprehensive framework is proposed.
The framework (Figure 3) synthesizes insights from literature and empirical evidence into three main stages: Initiation, Adoption Decision, and Implementation, following Vu et al. (2023). The proposed sub-steps combined propositions from Vu et al. (2023), Vlachos (2023) and Chaffin et al. (2024).The framework associates CSFs and challenges with each implementation phase for a more precise diagnosis of organizational readiness and enables managerial interventions. This logic follows Chaffin et al. (2024), who emphasize that the success of SCCTs depends on the alignment between technological capability and organizational maturity at each stage of deployment.
Supply Chain Control Tower implementation steps and relations to challenges and success factors.
The proposed framework incorporates 15 Critical Success Factors (CSFs), which are defined as conditions that must be effectively established and maintained to ensure successful SCCT implementation and sustained performance (Bambrick et al., 2025). While the original 14 CSFs are based on the work of Chaffin et al. (2024), this study adds a 15th factor (Technology Integration) reflecting both its theoretical relevance (Vlachos, 2023) and its prominence in the empirical findings. Notably, the companies studied highlighted the integration of digital technologies as one of the key drivers for initiating SCCT projects.
It also identifies 11 implementation challenges, derived from interviews (Maheshwari et al., 2024; Vlachos, 2023; Chaffin et al., 2024). The relations among challenges and CSFs used a cause-and-effect rationale. For example, challenges such as “V – Precise process representation” and “VI – Data quality” must be overcome to achieve success factors such as “F – Process standardization” and “G – Data Quality. The association of challenges and CSFs with implementation steps is based on literature and practical information from companies. The association between challenges and CSFs in each phase helps organizations to anticipate risks and structure responsive strategies. The CSFs are categorized into three dimensions: organizational, process, and technological (OPT), as proposed by Chaffin et al. (2024). The challenges that have been associated with a CSF are classified in the same group. Appendix 3 shows the CSFs and Challenges associations.
The SCCT implementation plan is operationalized through the following stages and sub-steps:
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Initiation
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1.1 Requirements: This pre-project phase involves mapping the organization’s current supply chain processes and identifying performance gaps. It also includes determining the most appropriate control tower model (Vlachos, 2023; Yan et al., 2012). Common challenges at this stage include a lack of regulatory support, limited budgets, skill shortages, unclear critical processes, and IT/business misalignment.
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1.2 Define Objectives: Here, the SCCT’s objectives and KPIs are defined, along with the identification of core organizational areas that must be involved. Strong coordination between IT/BI teams and operational units is crucial to ensure goal alignment (Vlachos, 2023). Failure to establish this integration may result in fragmentation during execution.
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Adoption Decision
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2.1 SCCT Network and Technologies: This step defines the internal areas and external partners to be included. It involves collecting data from logistics providers and third parties (e.g., geolocation, cargo status, route planning, and workforce data), as well as specifying technologies for data integration and visualization (Alacam & Sencer, 2021; Cedillo-Campos et al., 2024; Liotine, 2019). Technologies such as ERP (Vlachos, 2022), WMS (Vlachos, 2023), TMS (Wyciślak & Pourhejazy, 2023), and cloud-based systems (Verma et al., 2020) serve as enablers of real-time data integration. The Internet of Things (IoT) allows granular asset tracking, while big data analytics and machine learning provide predictive support for scenario planning and agile response (Maheshwari et al., 2024). Artificial intelligence contributes to route optimization, supplier management, and demand forecasting, further improving SCCT performance (Liotine, 2019; Tavana et al., 2022).
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2.2 Implementation Phases: This sub-step focuses on the technological infrastructure. It involves configuring cloud databases, building dashboards for real-time visualization, and conducting functional testing (Syahchari et al., 2022). Without this groundwork, efforts to automate or scale up the SCCT are likely to fail.
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Implementation
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3.1 Pilot: In this phase, core SCCT functionalities are tested, including data flow, user access, and control mechanisms. Feedback from system users is critical for adjustment and validation.
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3.2 Monitoring: Continuous monitoring begins after the pilot. An IT team must ensure system stability and intervene in case of disruptions or inconsistencies (Alias et al., 2014b; Saurav, 2023).
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3.3 Expansion: This final phase supports the continuous evolution of the SCCT, including the incorporation of machine learning and artificial intelligence to improve predictive capacity and overall performance (Maheshwari et al., 2024).
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The framework (Figure 3), also demonstrates that challenges are not isolated but distributed across the full implementation cycle. Addressing them in a timely and structured manner is essential for realizing the proposed CSFs. Decisions made in the early stages – whether strategic, tactical, or operational – directly influence the SCCT’s ability to provide real-time visibility, coordination, and value generation (Dwiyana et al., 2022; Verma et al., 2020; Vlachos, 2022).
Ultimately, this framework enables the diagnosis of maturity, identification of phase-specific challenges, and prioritization of interventions. By integrating theoretical constructs with field-based evidence, it advances both academic understanding and applied knowledge in supply chain intelligence and digital transformation.
6. Discussions and theoretical-practical implications
The comparative analysis between literature and empirical evidence from the three case studies reveals substantial gaps in technological maturity, organizational alignment, and strategic planning. These findings reinforce that SCCTs are not merely technological tools, but socio-technical systems that require coordinated planning, progressive development, and engagement from multiple organizational layers.
From a theoretical perspective, this work advances SCCT literature by offering a structured framework that articulates the implementation process across clearly defined stages. In each stage is possible to understand how specific barriers tend to emerge at certain points in the project and how their mitigation is directly linked to the fulfillment of Critical Success Factors (CSFs). The relations emerged in the framework corroborate with the works of Maheshwari et al. (2024), Vlachos (2023) and Chaffin et al. (2024).
Analyzing the presence of challenges in the implementation steps, the emergence of internal resistance and lack of cross-departmental coordination was observed primarily in the initiation and planning phases. The internal information fragmentation and functional silos common in large enterprises create a critical need for centralized visibility, which, when coupled with their broader budgetary capacity and greater control over supply chain networks, makes them the primary adopters of Control Tower solutions (Li et al., 2024). These difficulties, more evident in Companies B and C, justify the inclusion of CSFs such as stakeholder alignment, the establishment of governance structures, and clarity in project objectives. This validates the inclusion of organizational alignment and interdepartmental integration as prerequisites for a successful SCCT (Chaffin et al., 2024).
On average, the Brazilian industry is in the implementation stage and initial digital development of some technologies compared to other countries in the OECD, and the reality of the Brazilian scenario shows a deficiency in the aspect of professional qualification that may be considered critical in the digitalization journey of Brazilian companies (Stradioto & Frazzon, 2023).
The framework also reveals that technological barriers, such as fragmented systems, the absence of real-time data processing, and limited infrastructure for machine learning and predictive analytics, tend to surface during the implementation and expansion phases. In Company A, for example, although technical integration was more advanced, challenges related to strategic alignment and the use of data for higher-level decision-making persisted. This supports the idea of Vlachos (2023) that technological deployment alone is not sufficient and must be complemented by structural adjustments, investment in skills, and cultural readiness for data-driven operations.
Practically, the framework provides a roadmap for companies seeking to assess their level of preparedness and prioritize actions according to project maturity. It clarifies that SCCTs are not equivalent to business intelligence dashboards. While dashboards are part of the user interface, the SCCT must go beyond data aggregation and deliver integrated visibility, automation of responses, and support for strategic coordination. This distinction is particularly relevant for Companies B and C, whose focus remained limited to internal data centralization, without progressing to predictive functionalities or external integration.
The analysis also underscores that areas such as Human Resources, Information Technology, Maintenance, Safety, and Finance were identified as actors in SCCT initiatives in Companies B and C. This observation extends the theoretical scope of the literature, which has traditionally emphasized logistics, planning, and supply operations. A broader view of functional participation is essential for understanding SCCTs as platforms that integrate decision-making across the organization.
Moreover, the inclusion of a new critical success factor, “Technology Integration”, proposed in this study, is justified both by the literature (85% of the works from BP) and the field evidence. All three companies highlighted the integration of systems as a core motivation for starting SCCT projects. However, limitations in legacy systems, data quality, and interoperability reveal that full integration remains a distant goal. These difficulties reinforce the need to address digital maturity and data governance early in the implementation process.
The findings also suggest that SCCT initiatives should not view as isolated IT projects, but as strategic efforts that require executive sponsorship, governance mechanisms, and performance monitoring structures of SCCT projects. Projects led solely by IT departments face higher risks of failure. In all cases studied, the absence of a multidisciplinary project team was cited as a limitation. Multidisciplinary leadership and decisions taken at all levels (operational, tactical, strategical) contributes to broader engagement, aligns expectations, and facilitates change management, especially when SCCTs are introduced in environments resistant to process innovation.
Finally, this study highlights that SCCT implementation is typically restricted to large companies due to high costs and infrastructure requirements. These companies often operate as focal firms within their supply chain networks. As such, the SCCT becomes a coordination mechanism capable of enhancing information flow, synchronizing decisions, and promoting integration across the network. This role is comparable to that of a governance node, echoing the function of a distributed ledger in blockchain environments.
7. Conclusions
Driven by Industry 4.0 and the increasing complexity of global supply chains, the adoption of intelligent, integrated solutions has become a strategic priority for organizations seeking greater resilience, responsiveness, and competitiveness. Among these solutions, the Supply Chain Control Tower (SCCT) stands out as a promising approach for achieving real-time visibility, cross-functional coordination, and data-driven decision-making. However, research on SCCTs remains limited and fragmented (Chaffin et al., 2024). Addressing the conceptual fragmentation in the literature, this work proposes a comprehensive definition for the Supply Chain Control Tower (SCCT) that integrates modern digital technologies and the operational requirements of large multinational companies.
Moreover, it is developed a structured framework for SCCT implementation, grounded in a scoping literature review based on 32 selected publications and empirical evidence from three large multinational companies. The results revealed that although the interviewed companies recognize the potential of SCCTs and share similar objectives regarding integration and visibility in literature (Vlachos, 2023), none of them fully aligned with the actual SCCT model. Company A showed greater technological maturity and organizational alignment with supply chain partners, while Companies B and C remained focused on internal data consolidation, lacking external integration and advanced analytics capabilities.
Based on the motivations and difficulties reported by companies, a framework is proposed that organizes SCCT implementation into three stages (initiation, adoption decision, and implementation) (Vu et al., 2023) with seven associated sub-steps from Vu et al. (2023), Vlachos (2023) and Chaffin et al. (2024). For each phase, challenges and critical success factors (CSFs) were identified and interrelated, based on Organizational Information Processing Theory (Chaffin et al., 2024) and Socio-Technical Systems Theory (Vlachos, 2023) as theoretical lenses. The assumption is that implementation obstacles are dynamic and phase-dependent. This decision-making logic allows organizations to assess their readiness, anticipate potential barriers, and prioritize actions in alignment with strategic objectives. Among the fifteen CSFs adopted, this study proposes the inclusion of “technology integration” as a new factor, given its prominence in both the literature (Patsavellas et al., 2021) and the empirical data.
From a theoretical standpoint, this research contributes by clarifying the interdependencies among decision-making levels, technological enablers, and organizational functions in SCCT deployment, advancing the work of Vlachos (2023) and Chaffin et al. (2024). Practically, the model offers managers a diagnostic and planning tool to guide implementation strategies based on company maturity, supply chain complexity, and strategic goals.
The study also highlights important implementation challenges. The lack of interdisciplinary leadership, low digital maturity, misalignment between IT and operational areas, and limited access to real-time data were identified as recurrent barriers in the companies analyzed. These difficulties justify the phased structure of the framework and reinforce the need for cross-functional collaboration, standardization, and progressive technological evolution. Moreover, the empirical evidence indicates that SCCTs should not be equated with dashboards or isolated business intelligence initiatives. Their value lies in their capacity to orchestrate integrated end-to-end processes, enabling strategic coordination and agility throughout the supply chain.
Finally, the areas involved in SCCT initiatives in literature were traditionally logistics, planning, and transport functions (Sharabati et al., 2022), however, the interviews indicated the participation of departments such as Information Technology, Finance, Human Resources, Safety, and Maintenance. This insight broadens the functional scope of SCCTs and opens new directions for both theoretical discussion and applied research.
Despite the contributions presented, the study has limitations. The framework was designed using data from three large multinational companies. However, organizational or regional characteristics of Brazilian workers/companies were not considered. Future studies should explore the applicability and scalability of the framework in organizations of different sizes, sectors, and levels of digital maturity. Further research should apply quantitative methods to confirm the relationships among challenges, CSFs, and implementation phases proposed in this model.
Future studies could also explore emerging directions related to SCCT across different markets, sectors, levels of maturity, and organizational structures. Given the increasing adoption of outsourced solutions, research may examine the implications of a Software as a Service (SaaS) platform for control tower functionalities, considering aspects such as scalability, data integration, and governance structures. Additionally, sector-specific investigations, particularly in fields such as transportation, warehousing, and after-sales services, may contribute to understanding how control towers can be tailored to distinct operational needs and strategic priorities across different segments of the supply chain. Finally, it is also important to investigate the impacts of AI and ML application tools in SCCTs.
In conclusion, by bridging academic knowledge and organizational practice, the proposed framework offers a foundation for developing more intelligent, integrated, and adaptive supply chains capable of responding effectively to the challenges of a rapidly evolving business environment.
Appendix 1
| RQ Variables (Themes) | Interview Open-Ended Question - Related to RQ Variables | Objective of the Question - Relation between RQ and Questions | Question Keywords (Included in Column 2 of Table 4 ) | Main Related Implementation Step (Included in Table 4 and Framework) |
|---|---|---|---|---|
| Characteristics (definitions) | What is the main motivation to implement SCCT? | To investigate the underlying business inefficiencies that prompt the adoption of control tower frameworks. Analyze if these inefficiencies can impact on the choice of CT type | Company Motivation | 1.1 Requirements |
| Capabilities (functionalities) | What were the main functionalities considered in the SCCT project? | To identify the general capabilities the company has planned to implement | Goals with the tower implementation | 1.2 Define objectives |
| Which Key Performance Indicators (KPIs) are monitored within the tower? | To identify by KPIs which functionalities are implemented. To verify what is monitored | Key Performance Indicators (KPIs) | ||
| Which systems and technologies are utilized in the Control Tower? | To identify the systems and associated technologies involved in CT implementation | Technologies implementation in the SCCT | 2.1 Network and Integrated Technologies | |
| Areas involved in SCCT projects | Which operational areas are monitored within the tower? | Verify the involved areas in CT implementation projects | Areas that comprise the Control Tower | |
| Implementation steps | How was the SCCT implementation process executed? | Identify which kind of project process and steps have been deployed during the project | SCCT implementation process | 2.2 Implementation phases |
| Barriers/success factors | How is the tower tracked, and who takes decision? | Verify the relationships stablished among partners and Identify if the "CT users" are the same included during implementation | Decision Making Authority | 3.1 Pilot |
| Are there any limitations or constraints associated with the control tower utilization? For instance, updates, gaps, or manual inputs? | Verify the barriers that have not been addressed in any step during implementation | Limitations of the Control Tower | 3.2 Monitoring | |
| What are the key advantages or positive outcomes of its usage? | Identify the Success Factors attained with the implementations | Key advantages of the Tower | ||
| Which future potential opportunities does the company envisage with the SCCT? | To investigate other Success Factors that have not been achieved yet | Potential Opportunities for the Tower | 3.3 Expansion |
Appendix 2
The table presents the synthesis of the portfolio findings, showing those cited in more than 5 studies. The classification of company areas was based on the scope of the articles and the details of the case studies.
| SCCT Capabilities | Company areas involved in the SCCT | |||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author | Decision Making | Tracking - Products/Employees | Monitoring | Real time | Notification/ Alerts | Forecasting | Visibility | Cost Control | Integrated Technology | Inventory Level | Key performance Indicator | Collaboration | Risk Management | % capabilities cited in the paper | Planning | Procurement | Inbound | Order Processing | Manufacturing / Production | Transportation | Warehousing | Outbound | Customer Service | E2E | % areas involved in the study | |
| Total | 15 | 14 | 21 | 13 | 15 | 10 | 25 | 14 | 26 | 14 | 11 | 20 | 16 | - | 12 | 9 | 4 | 10 | 9 | 17 | 10 | 3 | 5 | 10 | - | |
| N. | % paper that cited the capability/company area | 48.4% | 45.2% | 67.7% | 41.9% | 48.4% | 32.3% | 80.6% | 45.2% | 83.9% | 45.2% | 35.5% | 64.5% | 51.6% | - | 38.7% | 29.0% | 12.9% | 32.3% | 29.0% | 54.8% | 32.3% | 9.7% | 16.1% | 32.3% | - |
| 1 | Alacam & Sencer (2021) | x | x | 15.4% | 0.0% | |||||||||||||||||||||
| 2 | Alias et al. (2014b) | x | x | x | x | 30.8% | 0.0% | |||||||||||||||||||
| 3 | Alias, Ozgur, et al. (2014) | x | x | x | x | x | x | x | x | x | 69.2% | x | x | 20.0% | ||||||||||||
| 4 | Alias et al. (2014a) | x | x | x | x | x | 38.5% | 0.0% | ||||||||||||||||||
| 5 | Alias et al. (2015) | x | x | x | x | x | x | x | 53.8% | x | 10.0% | |||||||||||||||
| 6 | Cedillo-Campos et al. (2024) | x | x | x | 23.1% | x | 10.0% | |||||||||||||||||||
| 7 | Chaffin et al. (2024) | x | x | x | x | x | x | x | x | x | x | 76.9% | x | x | x | x | 40.0% | |||||||||
| 8 | Dwiyana et al. (2022) | x | x | x | x | x | 38.5% | x | x | x | x | x | x | 60.0% | ||||||||||||
| 9 | Gerrits et al. (2022) | x | x | x | x | 30.8% | 0.0% | |||||||||||||||||||
| 10 | Hofman (2014) | x | x | x | x | x | x | 46.2% | x | x | 20.0% | |||||||||||||||
| 11 | Kulkarni (2023) | x | x | x | x | x | 38.5% | x | x | x | 30.0% | |||||||||||||||
| 12 | Le Roch et al. (2015) | x | x | x | 23.1% | x | 10.0% | |||||||||||||||||||
| 13 | Liotine (2019) | x | x | x | x | x | x | x | x | x | x | x | x | x | 100.0% | x | x | x | 30.0% | |||||||
| 14 | Ma et al. (2023) | x | x | x | x | x | 38.5% | x | x | x | 30.0% | |||||||||||||||
| 15 | Maheshwari et al. (2024) | x | x | x | x | x | x | x | x | x | x | x | 84.6% | x | x | x | x | 40.0% | ||||||||
| 16 | Malmstedt & Bäckstrand (2022) | x | x | x | x | x | x | x | x | x | x | 76.9% | 0.0% | |||||||||||||
| 17 | Patsavellas et al. (2021) | x | x | x | x | x | x | x | x | x | x | x | x | 92.3% | x | x | 20.0% | |||||||||
| 18 | Saurav (2023) | x | x | x | x | x | 38.5% | x | x | x | x | 40.0% | ||||||||||||||
| 19 | Sharabati et al. (2022) | x | x | x | x | x | x | x | x | x | 69.2% | x | x | x | x | x | x | x | x | 80.0% | ||||||
| 20 | Shou-Wen et al. (2013a) | x | x | x | x | x | x | 46.2% | x | x | x | x | 40.0% | |||||||||||||
| 21 | Shou-Wen et al. (2013b) | x | x | x | x | x | x | 46.2% | x | x | x | x | x | x | x | x | x | x | 100.0% | |||||||
| 22 | Souza & Zhou (2015) | x | x | x | x | x | x | x | 53.8% | x | x | x | x | x | x | x | 70.0% | |||||||||
| 23 | Topan et al. (2020) | x | x | x | x | x | x | x | 53.8% | x | 10.0% | |||||||||||||||
| 24 | Trzuskawska-Grzesińska (2017) | x | x | x | x | x | x | 46.2% | x | x | x | x | x | x | 60.0% | |||||||||||
| 25 | Verma et al. (2020) | x | x | x | x | x | x | 46.2% | x | 10.0% | ||||||||||||||||
| 26 | Vlachos (2023) | x | x | x | x | x | x | x | x | 61.5% | 0.0% | |||||||||||||||
| 27 | Vlachos (2022) | x | x | x | x | x | x | 46.2% | x | x | x | 30.0% | ||||||||||||||
| 28 | Wycislak (2023) | x | x | x | x | x | 38.5% | x | x | 20.0% | ||||||||||||||||
| 29 | Wyciślak & Pourhejazy (2023) | x | x | x | x | x | x | 46.2% | x | x | x | x | x | 50.0% | ||||||||||||
| 30 | Yan et al. (2012) | x | x | x | x | x | x | x | x | x | 69.2% | x | x | x | 30.0% | |||||||||||
| 31 | Ye et al. (2022) | x | x | x | x | x | x | x | 53.8% | x | 10.0% | |||||||||||||||
| 32 | Zhang & Xiao (2023) | x | x | x | x | x | x | x | 53.8% | x | x | 20.0% | ||||||||||||||
Appendix 3
| OPT category | CSFs | OPT category | Challenges associated |
|---|---|---|---|
| Organizational | A-Top Management Commitment | Organizational | I - Lack of government regulations |
| B - Organization Readiness | II - Budgetary constraints | ||
| C - Human Capital | III - Skill requirement | ||
| D - Partner Trust | IV - Goals conflict / Trust Inversion | ||
| E - Relationship management | |||
| Process | F- Standardization | Process | V - Precise representation |
| G - Data Quality | VI - Data quality | ||
| H - Alert Generation | VII - Identify Critical Processes | ||
| I - Supply Chain Integration | |||
| J - Information sharing | |||
| Technology | K- Technology infrastructure | Technology | VIII - Interoperability |
| L - Digitalization | IX - IP protection | ||
| M - Data security | X - Cybersecurity | ||
| N - Advanced analytics | XI - IT/IS-business misalignment | ||
| O - Technology integration |
Data availability
Research data is available in the body of the article.
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References
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