Towards a Digital Twin of a Holacratic Organization: A Point of View on Lyytinen et al. (2023)

This point of view paper challenges and extends Lyytinen et al.'s (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. (2023) but also offers a near-term pathway for holacratic organizations to benefit from DTOs as decision-support tools