Primer 3: Articulating Value and Building an Impact Evidence Base
Demonstrating the concrete, tangible value of increased access to and re-use of data
Posted on 22nd of March 2021 by Andrew Young, Andrew Zahuranec, Stefaan Verhulst, Kateryna Gazaryan
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In the past, open data advocates have tended to argue for increased data re-use by relying on normative arguments. They noted how open data could enable greater transparency and provide accountability. While these arguments can be persuasive in some contexts, private-sector leaders, government officials, and the public sometimes need to understand how open data investments will tangibly benefit them. Otherwise, open data becomes another “nice-to-have” instead of an immediate need. In these circumstances, it is often better to appeal directly to personal or organizational interests, to provide simple explanations of how open data will support an actor’s short, medium, and long-term goals.
Identify clear, specific use cases: A well-defined problem leads to targeted solutions where it is possible to understand who data work will help and how. After identifying a general issue it wants to improve (e.g. adolescent mental health or climate change), an organization can refine its focus toward an actionable problem and have in mind a clear, measurable outcome they intend their work to produce. Organizations might find it helpful to frame their concern as a question, one answerable through data science. They may find it useful to use participatory question formulation processes that allow stakeholders to develop questions they would like answered.
Assess and segment demand: Data’s value can often seem ephemeral to those with immediate needs, lacking direct impact. Organizations can avoid this sense by trying to identify which specific organizations data re-use work might benefit and engaging directly with them. By understanding which government actors, businesses, and nonprofits would gain, organizations can build a constituency determined to see a project to fruition.
Offer opportunities to use and contribute to datasets: Data re-use work can be a narrowly organized effort, conducted by only a handful of senior analysts. By limiting the user base, however, organizations also limit the effort’s supporters, making it harder to launch and easier to end. When organizations allow data assets to be used by a large cohort, whether that be the public or another audience, they can build a constituency that can identify innovative new uses for data and are committed to seeing the project’s success.
Open Data’s Impact: A collection of resources from The GovLab examining the global impacts of open data, including tools, books, and 37 detailed case studies of illustrative projects.
Data Collaboratives Explorer: A repository of over 250 data collaboratives initiated around the world with the goal of creating new public value.
Data Collaboration for the Common Good: A report from the World Economic Forum outlining value propositions for public-private data partnerships and strategies for maximizing that value.
The 100 Questions Initiative: An exercise, relying on expert and public input, that seeks to identify important societal questions whose answers can be found through data science and collaboration.
Open Data Demand: Toward An Open Data Demand Assessment and Segmentation Methodology: A methodology that guides users through the process of identifying who would benefit from the insights open data can generate.