Vendor-managed inventory for a more agile supply chain: an application in the industrial sector

Over the last years, industrial companies are looking for solutions to innovate their products and processes because of the high market demand. In the VUCA world, characterized by volatility, uncertainty, complexity, and ambiguity of the market demand, having an agile and collaborative supply chain is crucial to maximize customer satisfaction and achieve cost efficiency. In this context, companies must build strong partnerships and synchronize their processes by sharing information in real time. This project resulted from the need of improving the Vendor-Managed Inventory (VMI) system, an online platform of electronic data interchange for inventory management, at Bosch Thermotechnology in Aveiro. Although Bosch Aveiro has been working with the VMI tool for 3 years, no guide is available about the operation of the tool, which means that the VMI tool is parameterized according to the know-how of the VMI users: material planners and suppliers. Furthermore, VMI users are aware of the possibility of excess or stock out of components in this type of planning. Working closer to VMI users, a problem-solving activity was done through an Ishikawa Diagram where the root causes of failure were identified. Then, those causes were prioritized and it was decided to analyse in detail VMI parameters (lead-time, period, minimum and maximum limits) since they were considered the main cause of failure. After several experiences and studies to improve the inventory management in the VMI tool, a new approach was developed. The proposed model for defining VMI parameters considers not only the annual value of consumption and the replenishment time (as done in the current model), but also the fluctuation in demand of those components. As a result of this work, the components were divided into four categories (runners, repeaters, low-cost items, and exotics) according to their behaviour (annual consumption value versus fluctuation) and, for each group, the coverage limits of stock were calculated. This study provided transparency about the importance of each component for the organization which enables quicker decisions. For Bosch Aveiro, this project results in a standard to parameterize the VMI tool and five best practices. In addition, it is expected that the implementation of the proposed model will reduce the risk of stock out and the time spend on managing components in the VMI tool as well as control the components with an excess of stock. In addition, this study highlighted the importance of clustering the components in inventory management, so the next step will be the analysis of components managed by the other two material planning systems (push and pull) according to the four categories (runners, repeaters, low-cost items, and exotics).