Remanufacturing is a viable option to extend the useful life of an end-of-use product or its parts, ensuring sustainable competitive advantages under the current global economic climate. Challenges typical to remanufacturing still persist, despite its many benefits. According to the European Remanufacturing Network, a key challenge is the lack of accurate, timely and consistent product knowledge as highlighted in a 2015 survey of 188 European remanufacturers. With more data being produced by electric and hybrid vehicles, this adds to the information complexity challenge already experienced in remanufacturing. Therefore, it is difficult to implement real-time and accurate remanufacturing for the shop floor; there are no papers that focus on this within an electric and hybrid vehicle environment. To address this problem, this paper attempts to: (1) identify the required parameters/variables needed for fuel cell remanufacturing by means of interviews; (2) rank the variables by Pareto analysis; (3) develop a casual loop diagram for the identified parameters/variables to visualise their impact on remanufacturing; and (4) model a simple stock and flow diagram to simulate and understand data and information-driven schemes in remanufacturing.