Decision making about city data and analytics services

By Jeni Tennison, an expert in data, technology and public policy, and a Public Digital Network member.

As part of the Bloomberg Philanthropies City Data Alliance, Public Digital will be helping cities who already have advanced data projects to become more data-driven, digital organisations. The essence of this transformation is to shift cities from thinking of data as something they might publish simply for transparency, towards implementing what we call “Data as a Service”, a concept we explored in the first post in this series.

In this post, we will look at how the way in which decisions get made about data can support (or challenge) the development of data and analytics services, and the important role of data governance.

Decisions decisions

Any city government looking to improve their Data as a Service will need to answer some tricky questions:

  • What data should they collect, procure or aggregate? What sources of data are residents and visitors comfortable with local government having access to? Is existing data of the necessary quality for the uses it needs to be put to?

  • Which data should be published as open data? And which data should have more specific constraints over who can use it or the purposes to which it’s put?

  • If it’s not open data, who should have access to particular datasets and for what purposes? What counts as a legitimate use of data?

  • Given the broad scope of data that people and organisations might be interested in, and limited resources, whose needs should be prioritised?

  • How should the city balance its role in providing data and analytics, and the role of other organisations such as businesses and charities in creating data and analytics services?

Some of these are strategic questions, where the answers might be linked to broader city government priorities. Others are more ethical questions, which need to be made with an eye to the potential risks and opportunities of different data practices and applications, the communities who benefit from them or are harmed by them. Both sets require deliberation; without it, cities won’t provide the right kinds of services, and could find they encounter push-back and reputational damage that holds back future progress.

Strategic decisions about data

Moving to publishing with purpose entails making strategic choices about which data and analytics services should be developed and invested in. Data and analytics services should not be solutions in search of a problem, but tools that are applied to address broader city government priorities.

For example, if a city has a problem with the proportion of its elderly population who are living in poverty, the kinds of data and analytics services it prioritises should be different to one that has issues with youth unemployment, or a need to build resilience in handling the impacts of climate change, or a requirement to cut its expenditure. This isn’t to say that data and analytics services will always be an appropriate tool for a given challenge, only that they should be part of the toolset that cities consider. How might they help to target interventions? To nudge people’s behaviour? To reduce workload?

Political leadership at the city level needs to identify city-level strategic priorities. Data teams within cities need to be able to propose ways in which data and analytics services could help.

Ethical decisions about data

The collection and use of data comes with both risks and opportunities. Different communities may be benefited by them or harmed by them. Governments – as public servants – have a particular ethical responsibility to ensure that the use of data advances equity and sustainability (in the environmental sense), and serves the long term needs of the whole community.

Governments are also by no means immune to more general public concerns about the ways in which data is being collected and used. These include concerns about the use of emerging technologies such as facial recognition; about data breaches and privacy impacts; and about biases and inequities in the operation of public institutions that can be magnified by their use of predictive analytics or automated decision making. When something goes wrong, as well as harm to citizens, other organisations or the environment, there may be reputational and electoral consequences for the city government and its political leadership.

This means cities need to lay out their approach – as London has with its Emerging Technology Charter – and have checks and balances in place to ensure the risks that come with the increasing use of data are understood and mitigated.

Robust data governance

The need for both strategic and ethical decisions to be made about data speaks to the need for data governance: having robust and formal mechanisms for making those decisions.

Existing city governance structures might incorporate data governance into the ways they work. For example a city might establish a council subcommittee with specific responsibilities to oversee the city’s collection, use and sharing of data. As with the wider shift to evidence-based policymaking, this requires data and digital awareness and literacy at the political and leadership level, something the City Data Alliance will be supporting through its mayoral training.

An alternate approach might be for cities to engage in more participatory data governance. Communities who will be affected by the city’s data practices would be informed and consulted and preferably actively involved in the co-design of those data services. The DECODE project, for example, has experimented with forms of democratic and commons-based data governance, involving citizens themselves in decision making about what should be done with data. Participative data governance practices not only help cities to embed equity in their data practices and manage data-related risks, but build trust and relationships with the communities they serve.

A final challenge for data governance processes is that they need a certain amount of agility, enabling a city to try new things in managed ways, and learn quickly based on experience, and as technologies and norms change. Like digital services, governance needs to be an ongoing, sustainable process, not a one-off consultation exercise.

Next steps

This series of posts has outlined some of the things cities need to consider as they steward and provide sustainable and equitable access to data that supports innovators inside and outside the public sector. The idea of Data as a Service provides a vision for the role a city can play; putting it into practice requires work on platforms, processes and people.

The City Data Alliance exists to make this a reality. We want to work with cities with real ambition. If you’re interested in any of the concepts we’ve explored in this series and would like to share your thoughts or find out more, contact us at: [email protected]

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