Effective data sharing plays a pivotal role in optimizing supply chain management and driving the operational excellence of businesses. However, certain barriers and challenges exist among the supply chain partners in communication and data exchange. This thesis investigates these barriers and proposes potential solutions, referred to as instruments, for data sharing in supply chains. The objective is to develop and validate a framework that addresses feasible barriers in high-tech supply chain organizations. Single case study interviews in a high-tech supply chain firm assess the framework's applicability, followed by a validation phase to test its generalizability. Infrastructural instruments include ICT, Blockchain, AI, ML, data standardization, and data security measures. Institutional instruments encompass cultural factors, trust-building techniques, contractual agreements, education and training programs, leadership practices, and ethical data sharing. The research contribution extends to a strategic deployment plan for these instruments, offering valuable insights to supply chain professionals. Additionally, the research emphasizes the significance of viewing risk as a comprehensive concept in relation to trust, technology, privacy, and governance-related barriers.