Optimizing last-mile delivery through data-driven transformation: an action research approach

Purpose This study aims to design a systematic process framework to guide the development, implementation and continuous improvement of data-driven tools in logistics operations. In addition, it seeks to understand how this transformation process enhances operational agility and flexibility, particularly within last-mile delivery contexts. Design/methodology/approach The research adopts an Action Research methodology, applied in collaboration with a logistics service provider. The study follows an iterative and participatory process involving the co-design, testing, validation and deployment of data-driven solutions, with a focus on the decision-making perspective. Findings The study demonstrates that a structured approach to data-driven transformation not only improves logistics efficiency but also enhances flexibility and agility in last-mile operations. Furthermore, it contributes to mitigating key organizational barriers – most notably cultural resistance – by involving decision-makers throughout the design and implementation process. Practical implications The proposed framework provides logistics managers and practitioners with a clear roadmap for initiating and sustaining data-driven transformation. Focusing on structured implementation and continuous improvement of organizations can enhance responsiveness, adaptability and operational performance in dynamic delivery environments. Originality/value This research contributes a novel, validated process framework for the development of data-driven tools in logistics. It offers a practical, experience-based approach that integrates technological, organizational and cultural dimensions of digital transformation, addressing a gap between theoretical models and real-world applications.