A core principle of privacy protection is to minimize the amount of personal data in data sets to the level needed for the intended usage. The rapid growth of data and data-driven applications demands for using efficient software tools to minimize personal data to the needed level. However, applying Personal Data Minimization (PDM) tools into practice and embedding PDM technology within organizations are challenging tasks. These challenges stem from PDM complexity, context-dependency, multi-disciplinary nature, as well as liability and accountability burdens. This paper aims at enhancing the use of PDM technology within public organizations. To realize this enhancement, we identify three directions – namely, improving usability (efficiency and ease of use), improving trust in PDM tools, and identifying the other influential PDM technology adoption factors. These directions are based amongst others on a literature study and expert interviews. We conducted a questionnaire-based survey among academia and research institutions to investigate the need for PDM technology and the relevancy of the directions empirically. Based on the insights gained, the paper suggests several solution directions and/or avenues for future research. Specifically, we highlight the need for developing customized PDM tools and usage instructions for these tools in different data-sharing settings to facilitate the usability of PDM technology. For establishing trust in PDM technology, we highlight the need for employing various mechanisms such as certification, standardization, and open-source software tools. Thirdly, we call for investigating all factors that are influential in PDM technology adoption to set the usability and trust factors in perspective.