Data sharing brings data sources together to enable cross-analysis, creating additional value for results across government. Data sharing across government as a whole is often ad hoc, driven by high-profile incidents. In contrast, data sharing as a program is a systematic and scalable approach to enable data reuse and service innovation.
Sharing requires compromise, strong sponsorship and political leadership. This means that CIOs should work with stakeholders to develop a strategy for sharing data at multiple scales, focusing on value and government goals.
All participating parties accept increased risk to data they previously controlled, as well as exposure to data deficiencies, in exchange for mission delivery contributions or budget savings.
There is a responsibility to provide value and improve over time.
A data-sharing program does not need to solve the whole problem at once and can develop value in proportion to the effort. Data of mixed quality exposes the author to criticism for lack of control, but also exposes the user to risks of inaccuracies in decisions based on faulty data.
The data subject or author of the data and the data managers must trust that the information is shared appropriately, despite the sometimes conflicting expectations of the stakeholders. Years of culture of siloing for security reasons must now be shifted to using data to serve citizens and accelerate improvements.
Gartner estimates that by 2023, 50% of government organizations will establish formal accountability structures for data sharing, including standards for data structure, quality, and timeliness. At the same time, organizations across all sectors, including government, that implement data sharing will outperform their peers on most business value metrics.