Governing by data: Limits and opportunities
Most people running a commercial website look at data such as page views, user ratings and popular search terms. They may well analyse this data through the use of a funnel model that looks at the sales, or other single objective, that the site facilitates.
But governments have to use more complicated measures of success, something illustrated by a system that will visualise usage of Estonia’s state portal, which provides information and a gateway to public services in the country.
“If you look at a river delta, you see a lot of pathways that are criss-crossing, you can zoom in and see from where people are coming and going, what are the relations between different services and articles,” says the portal’s head Raimo Reiman of what is required. He has not found a product that provides this out of the box: “Traditional analytics methods, especially using funnels and things like that, don’t really work for us because we don’t have such clear end-goals for people,” he says.
As well as numerical data, the state portal uses “soft analytics”, including written comments and interviews. As a result of considering all of this, last year it added articles based on life events including starting a family, setting up a company and moving house. Another recent change has made links more visible, which has reduced complaints and raised satisfaction levels – particularly important when an organisation exists to serve the public.
The site’s status as a part of government affects the data-gathering tools it can use. “We’re not using screen recording, mouse tracking or things like that, because we have estimated the risk of data breaches as being too high,” says Reiman. The portal does not require users to log in for many functions and in general aims to keep things as anonymous as possible.
Complex measures of success and the need to serve citizens while protecting their data are all ways in which public-sector organisations can differ from companies in their use of data analysis.
“In theory and in practice in some areas, data analysis is incredibly useful for better understanding the population that you serve, the issues that face the country that you govern and how people are currently interacting with government,” says Gavin Freeguard, head of data and transparency at the Institute for Government. But it should not be seen as providing all the answers: “We talk about ‘data-driven’, which is quite nice as it alliterates,” he says. “I think you want to be data-informed rather than data-driven.”
The best results for government come from using data alongside other kinds of information, both quantitative and qualitative. Public service – including being fair to all citizens – makes data quality particularly important for government. “There’s been a bit of a propensity recently to focus on the flashy data analytics output you can produce, rather than the fundamentals of the data,” says Jeni Tennison, chief executive of the Open Data Institute. But unless data is high in quality, reliable and representative, the results are unlikely to be useful. “We’re in a bit of danger of creating stuff that looks really pretty, but doesn’t have substance to it,” says Tennison, adding that one risks is public bodies preferring to use data that is easy to obtain, such as web-scraped material, rather than rigorously-checked statistics. Ensuring data is analysed fairly is particularly important when data analysis is used to decide where to target services. “The concern is about false positives,” says Richard Puleston, director of strategy, insight and engagement at Essex County Council. If a system predicts an individual needs the involvement of social workers and they don’t, that intervention could cause harm as well as wasting public money. “I don’t think our algorithms are good enough to give us a level of confidence, and ethically we don’t want to go there,” he says of person-focused targeting.
