Companies collect terabytes of data about their products in the field, but research shows that R&D makes little use of this data, i.e., it is an untapped resource. In this paper, we explore collection and usage of post-deployment product data. We highlight the existing limitations in post-deployment data usage and the untapped resource that post-deployment product data remains. Based on a multiple case study at three software development companies, we collected three main findings. First, post-deployment data is used as input to the next pre-development phase, but not for improvement of existing product versions. Second, post-deployment data is used for troubleshooting and support activities, but not for innovation of new features. Third, post-deployment data provides a system-level understanding of operation and performance, but does not provide insight in individual feature usage. Finally, we propose a framework in which we outline what development practices and organizational mechanisms that need to be in place for advancing the usage of post-deployment data and advance the development of software-intensive embedded products.