Copyright ©2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Collective Data Analytics Capability Building Processes: a Governance Model Boriana Rukanova*, Anneke Zuiderwijk-van Eijk**, Moorchana Das***, Yao Hua Tan****, Toni Männistö***** *Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands, b.d.rukanova@tudelft.nl **Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands, A.M.G.Zuiderwijk- vanEijk@tudelft.nl *** Delft University of Technology, M.Das@student.tudelft.nl ****Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands, Y.Tan@tudelft.nl *****Cross-Border Research Association, toni@cross-border.org Abstract: Collective data analytics capability building offers opportunities for government organizations to develop capabilities that would be difficult to develop on their own. However, research on that topic is scarce and there is still a limited understanding of how collective data analytics capability building processes contribute to the value realization of the individual participating organizations. In this paper, drawing from the governance literature and by analyzing a case study from the customs domain we develop a governance model that allows to analyze collective data analytics capability building processes. Our governance model is a contribution to the literature on the use of data analytics in government, with the specific focus on understanding the collective data analytics capability building processes. For practitioners, the model can be used for identifying scenarios for engaging in collective data analytics initiatives in a multi-level context. Keywords: Governance, collective, data analytics, capabilities, value, customs Acknowledgement: This research was partially funded by the PROFILE Project (nr. 786748), which opinions expressed by the authors do not necessarily represent those of all partners. 1. Introduction Governments today are facing big challenges in the domain of international trade. They face increase in international trade due to developments such as Brexit and eCommerce, and at the same time they need to ensure safety and security while at the same time facilitating trade (Tan et al., 2011). To address such challenges governments are starting to explore the possibilities that big data and data analytics can offer. Big data refers to data that is high in volume, velocity and variety and that requires specific technology and analytical methods for transforming it into value (De Mauro et al.,