## 2 Challenges
The implementation of CE practices, including the exchange of resources intra- and inter-companies, sharing of knowledge, energy demand, and response optimization, as well as of the assessment of companies' sustainability performances, requires sharing data and information that are often private and sensitive (i.e., primary and foreground inventory data). The proper management of data and decoupling of sensitive information would result in the elicitation of circular opportunities for companies and in the possibility to \"externalize\" the management of such data, enabling an effective decision-making process and assuring trust and rewarding circular behaviors. Challenge 4--No effective and reliable LCA data sources[14]The measurement of the sustainability performances of products and companies has been largely recognized as a pre-requisite for the actual translation of sustainability-driven strategies into operations, towards the implementation of the triple bottom line concept in everyday industrial practices. For these reasons, proper metrics must be adopted enabling the standardized calculation of appropriate indicators measuring the economic, environmental, and social performances at product and company levels. This notwithstanding, the application of LCA, LCC, and S-LCA meets several barriers for businesses due to their high degree of complexity and demand for high-quality and high-quantity data. Data gathering from the different entities along the supply chain is probably the most critical issue to be solved, also considering that the completeness and quality of data are fundamental for the reliability and repeatability of the calculated impacts. If the use of primary data enhances the quality of the results, since they address specific products flowing through the manufacturing network, the collection of this kind of data requires extraordinary effort, especially when real-time assessment or the traceability of a specific production lot is needed, or when the data in analysis have to be collected from suppliers and, especially, from (n-tier) suppliers of suppliers. Current LCA tools are not integrable with the already existing data management platforms and, in most cases, information is retrieved manually and then replicated in a different environment with the risk of decoupling the descriptors of a single item. In the CE context, two main aspects related to Life-Cycle Assessment methodologies have to be considered: LCA metrics for CE and a framework to support the implementation of CE based on LCA evaluations. The criteria for the evaluation of circular practices adoption by organizations are still linked to local initiatives, or are in their embryonic stage so they are not already acknowledged in the industrial and academic contexts. Advancements are also required to properly integrate LCA in CE practices, thus enabling company decision-making processes related to circularity to be structurally based on a standardized set of circular metrics. Challenge 5--Poor use and exploitation of IoT-enabled data streams[15]More and more companies are realizing that the large amounts of information that they accumulate can play a critical role in the decision-making and creation of new business. However, there are some challenges ahead, as almost any organization that wants to implement Big Data exploitation encounters technology gaps. Conventional approaches are not designed to extract the most out of the large volumes of information; thus, challengesinclude mass data storage, integration of multiple formats and multiple sources, and processing and obtaining results in real time. CE approaches ask to trace products along their whole lifecycle to (1) recover in the production phase valuable components and materials that, in a linear vision, were considered as scraps, (2) monitor during the use phase the optimal use of consumables and maintenance needs, and (3) map the product in its end-of-life in order to enable its possible reuse and/or recycling of components and materials.