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Top1. Introduction
In the Automotive industry, there is a major requirement to make precise and efficient decisions due to the rising complexity of logistics operations. There are a number of analytical techniques (ATs) that can be used to make appropriate judgments that maximize resource utilization in the production process. (Semini, 2011). In general, the automobile sector is known for being vigorously process oriented manufacturing (Costa et al, 2017). So, the investments in advanced technologies which contribute to the digital transformation through objects such as monitoring sensors or transmission units akin to platforms such as Enterprise Resource Planning (ERP) system is required (GMIS, 2016). Information integration in the supply chain refers to the sharing of information and expertise across supply chain partners to integrate their efforts are key tactics to optimizing operations. (Susan et al, 2005). Logistics is a key functionality for automotive manufacturers. Automotive component logistics, warehouse, picking, packing, material handling and distribution, data processing, and other operational level activities are some of the key functional areas for an automotive manufacturer. (Liu and Sun,2012). An effective action plan which are strategically developed will be required to facilitate the application of the Internet of Things for the performance improvement. The technological development in the IOT comprises of many shop floor objects to GPS systems, given it Radio frequency identification (RFID) or information sensing devices (Tasmin, 2020). Internet of Things (IoT) devices are in charge of all devices and systems, as well as the network that connects them to the central control system. IoT devices can create high impact in terms value generation when optimized with analytics ability to address the business requirement (Meyer, 2013). Organizations can gain a competitive advantage by successfully implementing Enterprise Resource Planning (ERP) solutions in highly competitive marketplaces. ERP integrates a variety of technologies, including the Internet of Things (IoT), to help them compete in today's highly competitive marketplace (Tavana, 2020). For supply chain visibility, IoT technologies transform untapped raw data which are viewed as simple connection infrastructure to unlock the potential over and beyond to create value using intelligent and information sensing infrastructure. IoT applications assist businesses in making decisions by giving real-time intelligence (Pundir et al, 2019). Supply chain visibility is the ability for each stakeholder within the supply chain to utilize fresh and precise information without discrepancies. Increased SC visibility on key information such as the customer insights and real time tracking for the stock in the inventory improves accuracy and time taken for replanning the entire or adjusting production plans (Barratt and Barratt, 2011). Supply chain visibility correspond the improved agility within an organization. The uncertainty in the demand and supply may impact the firms that are expanding its operation and greater the visibility for the organization they can exercise better operation efficiency across the supply chain (Cecere, 2014). Supply chain agility is the ability to convert threats and uncertainties caused due to disruption in the market into opportunities by through strategic execution of calculated response measures (Ngai et al., 2011; Dhaigude and Kapoor, 2013). To ensure intelligent supply chain through efficient data processing methods that add potential benefit to the overall SCM agile performance will require focus on the optimum implementation strategies of disruptive technology. The analytics capabilities are key component in any multinational corporations to leverage analytical capabilities or collaborate with analytics service providers (Gupta, 2019). The intelligence through analytics can enable companies to rapidly reconfigure their supply chain to respond to customer demand from across the value chain (Ranjan 2016). The study aims to understand the potential influence of IOT Analytics interoperability with ERP and its further effect on the supply chain agile performance. It emphasizes on IOT and ERP interoperability in SCM practice, especially on its potential to optimize performance was motivated by the fact that the large group decision making method in the tradition context assign weight to the indicator are pre assigned in the evaluation process which add challenge in the agile performance which is dependent of response to disruption dynamically in the supply chain network (Zuo et al., 2019).