Overcoming data gaps for an efficient circular economy: A case study on the battery materials ecosystem

Data exchange and utilization are considered fundamental for the efficient development of industrial ecosystems. However, there are significant data gaps that currently prevent the implementation of circular economy models in practice. The present work is a first attempt to identify the sources of such barriers, using the battery materials industrial ecosystem in Finland as case study. A visual grounded theory model was created to formally analyze the collected interview answers from representatives of companies along the value chain. In summary, it was found that: i) companies gather information relevant for other stakeholders; ii) there are no incentives to openly share data, which is considered a valuable asset; iii) actors lack clarity on which data is relevant at a system-level; and iv) there is no consensus on which format can data be shared to efficiently promote circular economy strategies. To address the identified barriers, it is hereby proposed for the first time that parametrization is a strategy to promote data exchange between stakeholders. As an illustrative example, statistical entropy is presented as a mean to exchange data of battery material composition. Properly designed parameters could be used to codify relevant data without a negative impact on the confidentiality of companies, while at the same time providing clarity of purpose for the circular economy. Thus, this article introduces a novel perspective for the implementation of bottom-up data exchange practices in industry.