The COVID-19 pandemic and other global disruptions have exposed critical vulnerabilities in healthcare supply chains (HSCs), prompting a shift in focus towards resilience and proactive management. A key enabler in this transformation is the deployment of big data analytics capabilities (BDAC), which empower healthcare organisations to process large volumes of diverse data for improved decision-making and operational flexibility. In light of the limited research addressing BDAC's role in enhancing HSC resilience, a study was conducted using an integrated multi-criteria decision-making (MCDM) framework, combining Decision-Making Trial and Evaluation Laboratory (DANP) and Multi-Attributive Border Approximation Area Comparison (MABAC) methods. This approach was tested in a major Thai hospital, offering valuable insights for similar organisations across emerging healthcare markets.
Theoretical Foundations and Framework Design
The research builds on two complementary theoretical lenses—Organisational Information Processing (OIP) and Knowledge-Based Dynamic Capability (KBDC) theories. OIP underscores the need for organisations to align their information processing capacity with the dynamic demands of their environment. In the context of healthcare, where disruptions are frequent and stakes are high, this alignment is vital for maintaining operational continuity and patient care standards. BDAC plays a central role in this alignment by enabling data collection, storage and analysis across interconnected healthcare systems. The KBDC theory extends this perspective by framing BDAC as a dynamic organisational capability that incorporates knowledge acquisition, generation and integration. Together, these theories support a model where BDAC not only helps navigate immediate challenges but also cultivates organisational learning and adaptability over time.
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To operationalise this theoretical construct, the study identifies three core BDAC components: big data managerial capability, advanced data analytics capability and organisational knowledge and culture. These components form the basis for evaluating how healthcare organisations process and use data to enhance supply chain resilience. The hybrid MCDM approach enables a nuanced assessment of the interdependencies among these BDAC factors and their collective impact on resilience capacity.
Methodology and Case Application
The proposed evaluation framework unfolds in four phases. Phase I involves identifying and validating relevant BDAC and resilience capacity (RC) criteria through expert consultation and literature review. In Phase II, the Fuzzy DEMATEL technique is applied to map cause-and-effect relationships among BDAC criteria, accounting for both direct and indirect influences. This is followed by Phase III, where the DANP method is used to determine the relative weight of each criterion, reflecting its significance within the broader system. Phase IV applies the MABAC method to prioritise RC factors based on their relationship with BDAC dimensions, enabling targeted decision-making.
This framework was implemented in a case study involving Thailand's largest private hospital network, which manages over 50 hospitals with a combined capacity of more than 8,400 beds. The hospital has invested significantly in digital transformation, aiming to become a data-driven leader in Southeast Asia’s healthcare sector. Interviews were conducted with seven experts from the organisation, each possessing over a decade of experience in big data applications across various industries. Their input informed the evaluation of BDAC impact on the hospital’s ability to anticipate, absorb and recover from supply chain disruptions.
The case study revealed strong interconnections among the BDAC components, with advanced data analytics capability emerging as a central driver of resilience. Notably, the combination of DANP and MABAC facilitated the identification of high-priority interventions, such as improving predictive analytics for inventory management and fostering a data-oriented organisational culture. These insights underscore the value of the framework in guiding healthcare leaders through complex digital transformation initiatives.
Implications for Resilience in Healthcare Supply Chains
The study highlights several critical pathways through which BDAC enhances resilience in healthcare supply chains. First, it enables real-time visibility across the supply network, allowing early detection of disruptions and facilitating agile responses. This capability is particularly vital in crisis scenarios, where rapid resource allocation can directly influence patient outcomes. Second, BDAC supports inventory optimisation by leveraging historical consumption data and predictive modelling to maintain appropriate stock levels. This reduces both the risk of shortages and the financial burden of overstocking.
Third, the integration of BDAC with organisational knowledge and culture fosters continuous improvement and system learning. By institutionalising data-driven decision-making, healthcare organisations can evolve their supply chain practices to better withstand future uncertainties. Furthermore, the study's methodological contribution lies in demonstrating how the synergy between DANP and MABAC provides a robust basis for analysing multi-dimensional challenges, ensuring that decision-makers can prioritise interventions with the greatest impact on resilience.
The Thailand case study also offers broader lessons for developing countries aiming to leverage digital tools for healthcare improvement. It illustrates how tailored BDAC frameworks, grounded in context-specific challenges and organisational goals, can drive both operational efficiency and strategic resilience. These findings are particularly relevant for healthcare systems grappling with resource constraints and evolving health threats.
In today’s uncertain world, resilience in healthcare supply chains is essential. The study has introduced a framework for evaluating how big data analytics capabilities impact healthcare supply chain resilience. By combining OIP and KBDC theories with a hybrid MCDM approach, the research demonstrates the value of BDAC in improving visibility, agility and knowledge integration at a leading private hospital in Thailand. Healthcare leaders must recognise that investing in big data capabilities is a strategic imperative for creating robust supply chains able to withstand future disruptions.
Source: Healthcare Analytics
Image Credit: Freepik
