Flexibility in governance and operations is difficult to achieve due to tension inherent to formalizing ways of functioning to ensure stakeholders’ trust and building in margins of maneuverability for implementing changes. The way in which organizations have traditionally addressed this challenge is through adopting change management processes. These refer to a series of tasks for a seamless transition from a current state of affairs to a new one without affecting the data sharing operations or decreasing trust among stakeholders. Change management processes can be negotiated at the beginning of a partnership in conversations around governance. While no examples of change management models in data sharing partnerships within the development sector surfaced in this study, discussions with experts suggest that this is a relevant option for data sharing initiatives that are built to last.
From an architectural perspective, experts agree some of the biggest challenges are the scalability of existing infrastructure and how to finance information technology (IT) updates down the road. In this respect, there is a consensus on the importance of developing scalable IT plans at the very beginning of an initiative, anticipating how IT needs will evolve based on, for instance, an increased number of data users or the emergence of new technologies and standards. As an example, the uptake of application programming interfaces included the need to update much of the existing open data infrastructure to accommodate a different way of consuming the data by users. In the last few years, application programming interfaces have facilitated access and use of data by developers and programmers, reducing the need to download files or push paper.
No person or data sharing initiative can predict the future. But thinking ahead to plan for necessary updates to the infrastructure helps clarify future funding needs and ensures the initiative will remain relevant for stakeholders and users.
Repurposing data sharing initiatives to face new challenges
The Microsoft Open Data Campaign experience shows how important it is to build flexibility and change into data sharing collaborations.
One of its facilitated partnerships was aimed at monitoring air quality in the United Kingdom and involved the Alan Turing Institute – the U.K.’s national center for data science and artificial intelligence. After the emergence of the COVID-19 pandemic, this project was rapidly repurposed to help London authorities measure the impact of lockdown restrictions on the city. The Alan Turing Institute did this by deploying the infrastructure of the air quality study to measure the city’s “busyness” and the public response to government interventions.
While this was not the original intent of the data collaboration, the data streams had already been put in place, and the data infrastructure was able to generate insights relevant to the COVID crisis. High levels of trust between data partners allow for such flexibility.