Title: Data-Driven Governance Version: v.01 Date: 6/8/2021
At Govrn, we view outcome-based donations (OBDs) as an idea that combines innovations and research that already exist in unique ways. We’re bridging connections between related ideas to try something new. Read more about Govrn and OBDs here.
It’s worth mentioning that our work exists in the broader context of a governance renaissance. So many people and organizations are rethinking the roles of institutions, governance, and civic engagement to create more equitable, transparent, and participatory systems better able to address complex problems.
There’s no way we can cover all of what is going on in the space. But we do want to highlight some amazing work by others to both set the context for the broader idea of governance innovation and to explain where some of the ideas for Govrn come from.
Last time we talked about collective intelligence. This week we’re diving into data-driven governance, where we’ll introduce a few key terms and dive into how Govrn contributes to the ecosystem.
In 2013,1 the US federal government recognized that publicly opening their data would strengthen democracy, improve government services, grow the economy, and increase social good. In a step towards open government, President Barack Obama signed an executive order “making open and machine readable the new default for government information” and creating an Open Data Policy. Since then, both the Open Government Data Act and Foundations for Evidence-Based Policymaking Act have been signed into law. (Federal open data is available at data.gov.)
Meanwhile, at the municipal level, most major cities2 have Chief Data Officers and/or Innovation Officers. They are responsible for opening city data to the public and using it to increase operational transparency, legitimacy, and equitability.3 Here are a few examples of how cities are using open data: Kansas City KPIs, Boston CityScore, and New York Analytics Projects.
In addition to increasing data-informed government operations, there has also been a rise in evidence-based policymaking. Evidence-based policymaking is a results-focused approach that evaluates the impact of a policy and builds the knowledge base for future decisions. Of course, there are also challenges associated with this approach, but the idea of rigorously evaluating the results of a policy is worth calling out as it has received growing attention in recent years.
This may come as a surprise, but a lot of governance-related data that we think should exist actually isn’t yet available. Dataset curation takes resources, and if a dataset isn’t valued, it might not get measured or aggregated. Or if it is measured, it might not be at the right spatiotemporal resolution or accuracy to solve the problem at hand.
For example, when bacteria started spreading in New York City cooling towers and people were dying of Legionnaires’ Disease, the city desperately needed a dataset identifying the tens of thousands of buildings with cooling towers. The problem? New York City didn’t have that dataset. (Luckily they were able to curate one through obscure tax credit information.) For a less urgent but still critical example, try searching for air quality data on New York City’s open data portal - one of the best in the world. The spatiotemporal resolution is 43 neighborhoods with only the yearly average. Or, read about how cities are underestimating greenhouse gas emissions by up to 145%.
Today there are open data portals but no robust open marketplace to signal demand for data that isn’t yet available or adequate. OBDs present an opportunity for constituents, experts, and government officials to place societal value on data and spur proactive open data stewardship. Per the above examples, OBDs that are about broad problems like improving public health and mitigating climate change will very likely create positive externalities of data creation and sharing along the way. This is essential for public goods creation and public problem solving.
Data-driven governance is awesome, but not if you over index on the “wrong” metric or goal. An OBD by nature invites the public, community leaders, domain experts, and practitioners into the goal creation process. Metrics and goals will therefore be transparent and benefit from the perspective of a large and diverse group of individuals. This is data-driven governance driven by the people and supported by government institutions, rather than driven by government institutions with feedback from the people.
Data-driven governance has many stakeholders, and Govrn connects them all in one place. Constituents, domain experts, community leaders, and politicians are able to organize around collectively agreed upon goals and metrics. And more importantly, they have the option to stay connected throughout the entire governance lifecycle. This includes everything from defining a public problem, signalling demand for data, iterating on goals and metrics, critiquing the implementation, and evaluating the impact of the solution.
Govrn aligns the concept of evidence-based policymaking and data-driven governance with a very powerful lever: campaign finance. Right now there is high public demand for evidence-based policymaking and data-driven governance, but there’s no direct mechanism to invest in these processes. Investing in politicians who operate this way is a direct way to support this type of governance.
(Christine) Making a comment section here for people to add their thoughts in a bullet point style format. Or feel free to rewrite/add to the paper directly in the above sections!
1: The calls for data-driven governance started decades ago.
2: It’s really important to remember that not all regions have equal access to open data portals and data availability/quality. Data deserts, data gaps, and the digital divide are pressing problems in the data-driven governance age.