KEY PERFORMANCE INDICATORS TO INCREASE LOGISTICS PERFORMANCE IN THE DAIRY INDUSTRY : A CASE STUDY IN THE DAIRY INDUSTRY

Abstract: The dairy industry is a complex system that involves many stakeholders and processes, from production to distribution. To measure and improve the performance of this system, a comprehensive and reliable Performance Measurement System (PMS) is needed. A PMS is a tool that helps to evaluate the efficiency and effectiveness of supply chain operations. One of the components of a PMS is the key performance indicators (KPIs), which reflect the performance of specific aspects of the supply chain. This thesis explores how KPIs can be used to enhance logistics performance in the dairy industry. The research is based on a single case study of a global company that operates in the dairy sector, which faces challenges such as high competition, customer demand variability, and food waste. The research uses a mix of literature review, interviews, and data analysis to identify and evaluate the relevant KPIs for logistics performance, as well as their interrelationships and impacts. The research applies the interpretive structural modeling (ISM) method to develop a hierarchical model of the KPIs and their causal relationships. The interpretive structural model of the indicators shows that the current indicators commonly used in the dairy industry today are not suitable for measuring performance, the indicators do not affect the current performance significantly but rather reflect the. This paper proposes a methodology for qualitatively evaluating performance measures, based on the integration of the ISM approach, the MICMAC analysis, and the seven criteria of a KPI. The ISM approach is a technique for identifying and analyzing the interrelationships among elements of a complex system. By applying this methodology, organizations and researchers can assess the suitability and importance of a set of KPIs.