August 2022 09 A ROADMAP FOR IMPLEMENTATION OF BIG DATA ANALYTICS IN SUSTAINABLE SUPPLY CHAIN MANAGEMENT Prashant Jain Dr. Dhanraj P. Tambuskar Abstract The objective of this research is to suggest a roadmap for implementation of Big Data Analytics (BDA) in sustainable supply chain management (SSCM) in Indian manufacturing sector. Through an extensive literature survey the factors that are crucial to the application of BDA technologies to SSCM are identified. A comprehensive PESTEL framework is used for classification and analysis of these factors. The acronym PESTEL covers a variety of factors namely political, economic, social, technological, environmental and legal. This paper provides managers with an implementation framework comprising of four stages viz. identification of PESTEL factors, ascertainment of the critical success factors, selection of appropriate BDA technologies, and application of BDA technologies for SSCM. The implications of the study have been discussed at length. Theoretical implications highlight the importance of data generation, BDA infrastructure, data rationalization, BDA expertise and the BDA management capabilities. The managerial implications underline the competence and the dynamic capabilities that are required on the part of managers for organization of resources and effective selection and integration of BDA technologies. The factors identified, as a future work, may be evaluated and validated through suitable techniques. Also, the research may be extended to small and medium scale industries, which is currently its limitation. Keywords: Big data analytics (BDA); Sustainable supply chain management (SSCM); Sustainable manufacturing; PESTEL analysis 1. INTRODUCTION This is the age of data generation at unprecedented speed due to advent of advances in the ICT technologies and widespread use of mobile devices, sensors, and IoT etc. [1]. This has caused a sea change in the operations and management of the manufacturing supply chains by making the integration and coordination of the various links of the supply chain much more effective than the conventional systems. Currently almost all the industry sectors have adopted these latest ICT technologies [2]. These massive data sets are called Big Data and they have a high potential to influence the growth and competitive edge of business organizations by empowering them with innovations and enhanced productivity [3]. This has become possible due to the sophisticated Big Data Analytics (BDA) technologies that have initiated a new era in the field of SSCM [4]. The BDA markets in India are predicted to grow up to $16 billion in 2025 which was just $1 billion in 2013 [5]. The BDA has transformed the SSCM decisions from raw material purchasing to the product delivery to the customer [6]. The BDA also plays a vital role in strengthening the performance of the SME’s and their agility [7]. The BDA provoids an analytical know-how for business intelligence and efficient decision making [8] by identifying the trends and patterns that are hidden in the data sets. BDA, in other words may be said to be a means for the diffusion of knowledge [9]. Currently the BDA is being applied for the decision making in all the operations and at all the levels of the supply chain. The objective of this paper is the exploration of the possibilities of applying BDA for enhancement of quality of manufacturing decisions. The current literature discusses the BDA as applied to the supply chain operations in the field of project performance [10], lean, agile, resilient and green practices [11], Sustainability and Financial Performance [12], operational excellence for sustainable supply chain [13], sustainable performance in agriculture supply chain [14], supply chain agility [15], supply chain modelling [16], FMCG industries [17] etc. For maintaining the competitive edge of the supply chain all the stakeholders have to constantly improve the performance of the supply chain. this being an intricate task, includes numerous management processes e.g. identifying performance indicators, setting targets, exhaustive planning, continuous monitoring, effective communication, regular reporting and comprehensive feedback etc. due to this reason, there is no standard measure for performance and the measuring tools for enhancing the supply chain decisions vary from company to company [18]. In spite of the potential possessed by BDA for enhancing the corporate and supply chain decisions, companies still face lack of clarity as to how should they build BDA capabilities, implement the BDA program and overcome the organizational barriers [19]. Fewer researchers have taken up an all-inclusive investigation on the major factors that affect an organization’s willingness to implement big data [20]. Quite limited work has been done for underlining the enablers and barriers of successful adoption of BDA in SSCM [21]. To the best of author’s knowledge, PESTEL-BDA in SSCM is not discussed in current literature. This study attempts to address this by identifying these PESTEL factors that cover a variety of factors namely political, economic, social, technological, environmental and legal. These are identified by an extensive literature survey. Also, a framework is suggested for the implementation of BDA Vol. XV & Issue No. 09 September - 2022