AbstractThis point of view paper challenges and extends Lyytinen et al.’s (J Organ Des https://doi.org/10.1007/s41469-023-00151-z, 2023) conceptualization of Digital Twins of Organizations (DTOs) as highly complex models including multiple organizational facets like agency, conflict, and emergence. They argue that the journey to achieving a fully functional DTO is a long way. However, we suggest a more parsimonious approach, focusing on leveraging digital trace data on the four universal problems of organizing: task division, task allocation, provision of rewards, and provision of information. Using the specific context of a holacratic organization, we argue that some organizations already produce extensive digital traces that can be leveraged to construct a DTO that is fit-for-purpose. We propose that existing data-science methods like predictive models, matching algorithms, clustering algorithms, and association rule mining can be employed to transform these digital traces into actionable insights for decision-makers. This approach not only addresses the complexity concerns raised by Lyytinen et al. (J Organ Des https://doi.org/10.1007/s41469-023-00151-z, 2023) but also offers a near-term pathway for holacratic organizations to benefit from DTOs as decision-support tools.