As governments grapple with how to achieve data-driven efficiency improvements, often in the middle of the most successful efforts is a job that barely existed as a job a few years ago: the chief data officers, appointed in cities large and small, who are making rapid progress toward solving a range of vexing urban problems.
For the past two years, we've been able to bring together these data leaders and accelerate their successes via the power of a peer network. They help each other with analytic approaches to tough policy issues like traffic congestion and lead-paint abatement, and they also troubleshoot the operational aspects of their jobs, such as hiring and training staff and managing vendors. They don't just share results and source code -- they share their processes, methods and the pitfalls along the way. They make their job descriptions, RFPs and data-sharing agreement templates available to each other. They even help each other build open-source data tools.
While the CDOs in our Civic Analytics Network are leaders at the forefront of their young field, some of the insights gained from their work are transferrable to all cities, regardless of their data-maturity stage. From the CDOs' conversations we have distilled a list of important steps that data-savvy local and state governments should undertake:
- Produce an open-data policy roadmap that enables transparency and produces opportunity for researchers, community groups and those with additional data. Emerging open-data principles -- including the need to tie together related datasets, improve the use of geospatial data, and make it easier and cheaper to publish data -- were set out by the CDO group in an open letter intended to inspire vendors to make their product offerings more responsive to the unique needs of cities.
- Incentivize and enable cross-departmental collaboration by creating the right data infrastructure. Los Angeles' GeoHub, for example, is the city's public platform for exploring, visualizing and downloading location-based open data. It allows departments across the city to plan and do their work in closer coordination with each other and communities.
- Adopt enterprise-wide procedures that facilitate digital insights. Strong CDOs establish platforms for city-wide data warehousing or other tools that facilitate data exchange across departments. Allegheny County, Pa., pioneered this approach by connecting multiple disparate departments and services in its human-services data warehouse. There and elsewhere, enterprise-wide tools also include data usage practices, security protocols and standardized legal and data-sharing agreements. In New York City, for example, the Mayor's Office of Data Analytics (MODA) created the MODA Process Map to help departments develop data-readiness practices and internal awareness.
- Promote broad data literacy by offering opportunities for data fellowships, loaned and part-time talent, and relationships with local universities and businesses. In addition to bringing in data champions, cities also can develop internal capacity, as was done in San Francisco with its popular SF Data Academy, now copied or emulated in several other cities.
- Experiment with new approaches. The best CDOs are infusing human-centered design approaches broadly across their cities in ways that put the customer at the core of their operations. Others are experimenting with behavioral economics, nudges and other new ways of thinking about how to deliver the best results to deliver public value.
- Link civic engagement with city analytics by using visualization and feedback tools to generate and capture civic participation. Boston recently used public input to crowdsource its future vision for the city, and has leveraged civic input to update both its website and its open-data portal. Kansas City uses a quarterly feedback mechanism called the Citizen Survey where citizens are able to communicate their top priorities for the city.
- Build guardrails to protect equity, fairness and privacy. Analytics is a practical tool for overcoming resource shortages and for distilling disparate data, but public officials need to maintain controls and realize that the use of analytics itself is a valuable asset to be deployed strategically. Attention to and transparency about what projects are chosen, what data is gathered, and how it is protected are critical components.
