Benchmarking the interactions among performance indicators in dairy supply chain

Abstract

Purpose The purpose of this paper is to explore the key performance indicators (PIs) that serve as a decision support tool in case of dairy supply chain practices and to analyze their interactions in the context of Indian dairy industry sector. A total of 11 PIs have been identified through the literature review and the opinions of an expert team consisting of managerial and technical experts from dairy industry and academics. Design/methodology/approach A solution methodology based on the interpretive structure modeling (ISM) technique is used to analyze the interactions among PIs and to propose a structural model. The developed model not only helps in understanding the contextual relationship among the PIs, but also in determining their interdependence to assess the supply chain performance in dairy industry. Further, the importance of PIs has been determined based on their driving and dependence power by using MICMAC analysis. Findings The ISM-based model suggests four PIs at first level, three PIs at second level, one PI at third level as well as one PI at fourth level and two PIs at fifth level. Model allocates to the effective information technology, brand management, responsiveness in shipment and accuracy and a control over wastages as the key PIs in the dairy industry sector. The effective traceability systems, cold chain infrastructure, quality management and the support for technological innovations are the next major PIs. There exists no autonomous PI in MICMAC analysis which proves the importance of identified PIs in the case study. Research limitations/implications The proposed model is an attempt to capture the dynamics of milk processing sector and to incorporate all relevant constraints related to internal and external environments that would significantly improve the supply chain performance in the dairy industry. Practical implications The model developed in this study has been tested in the cooperative milk processing units based in India and also discussed with the experts from academics. This work may help practitioners, regulators and dairy industry professionals to focus their efforts toward achieving high performance by the effective implementation of the identified PIs. Originality/value In this study, 11 PIs are considered. Interactions among PIs are evaluated with the help of the ISM matrix. Out of the 11 PIs, six demonstrate both strong driving and dependence power as explained in the MICMAC analysis.

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