To enable a more sustainable future and achieve the United Nations Sustainable Development Goals (SDGs), it is important to quantify the impacts of processes, products, and services. Life cycle assessment (LCA) has become a widespread tool for assessing environmental impacts. The role of LCA is acknowledged by various decision-makers and is, thus, included as an important part of policies that aim to contribute to the achievement of the SDGs. Although LCA is a long-standing research topic and both the quality of obtained LCA results and the overall process of conducting LCAs have improved significantly over time, many challenges remain. LCA data collection is often time-consuming, the availability of robust data in the inventory analysis phase can be limited, and the assumptions made by producers and service providers for the subsequent life cycle phases (i.e., use and end-of-life) can be problematic. To overcome data-related LCA challenges, an emerging circular economy policy instrument, the digital product passport (DPP), offers a potential solution. Depending on its final design, a DPP can contain LCA-specific data relevant to all life cycle stages of a product. For example, a DPP may entail specific materials (comprising a share of secondary raw materials), may include information about manufacturers and suppliers of a product, and may anonymously track data related to the use phase or specific emissions and waste streams during the end-of-life phase. These data points are necessary for detailed LCA studies and constitutive policies; however, they are at present mostly available only as generic secondary data. To address this issue, this study focuses on the potential combination of DPPs and LCA by examining which data points may be incorporated into dynamic DPPs, and how this could directly provide the complete life cycle inventory (LCI; the calculation basis) to achieve more accurate LCAs. Differentiation between generic and potentially instance-specific data points (i.e., primary data of the specific product unit mostly stemming from automated tracking) for the LCA enables highlighting of some structural consequences for the DPP. Two use cases from the automotive industry are investigated, namely traction batteries of electric vehicles and turbochargers of combustion engines, to demonstrate possible configurations of DPP data points, their different LCA system models, and the implications of the results obtained. The automotive industry was considered an interesting use case, given the challenges it faces in becoming more sustainable and contributing to the SDGs. The results show the data mapping of the data points of the potential DPPs of both use cases to the corresponding life cycle inventories necessary for the calculation of an LCA. Consequently, this research serves as a starting point to further investigate the possibility of DPPs as data providers for LCIs and LCAs. Implementing this possible combination would facilitate the development of LCA as a reliable instrument to measure the environmental performance and progress of specific products towards the SDGs.