Published by William Mosseri-Marlio on 14 April 2016
- Our Work
- The Reformer Blog
19 April 2016
“When data is used effectively, everyone benefits from better services that can be delivered at a lower cost to taxpayers.”
This recent statement, made by the Minister for the Cabinet Office, Matt Hancock, resonates with a recent discussion at Reform’s strategy day. Presentations from the Behavioural Insights Team and Nesta made it clear that a more effective use of data will fundamentally change public services in 2030. This will be seen in two key areas:
1. how the state delivers services for users; and
2. how citizens interact with government.
Public services in 2030 will be delivered proactively: they will prevent negative incidents from occurring rather than respond to them once they have happened. Key to this will be the use of predictive modelling – the process of calculating future outcomes by collating information surrounding similar outcomes in the past.
Predictive modelling is being piloted across the globe. In London, the Metropolitan Police Service has developed a predictive analytics tool to identify individuals at risk of committing violent crimes. New Zealand has attempted to predict which children might be at risk of maltreatment. The University of Chicago has helped develop a misconduct warning system for police officers based on their exposure to particularly stressful incidents. These are all at early stages – and both New Zealand’s and Chicago’s attempts have run into ethical concerns – but they provide a glimpse of tomorrow’s public service model.
Tomorrow’s citizens will develop a more personal relationship with the state. By sharing their data they will be able to receive bespoke services. In healthcare, more than 165,000 apps are currently available to smartphone users. Deloitte has identified the opportunity for future health apps to transmit real-time information on conditions to doctors, to receive immediate health advice. In the USA, Lumiata has taken it a step further, using sophisticated algorithms to predict health risks of individuals. If these methods were applied nationwide in the USA, McKinsey & Company estimates that savings of 12 – 17 per cent could be made in annual health-care costs by preventing ill-health and unnecessary medical interventions. People would also benefit from avoiding the need to receive treatment.
A more personalised and predictive model offers considerable benefits for citizens. The Government, and future ones, should be bold in pioneering these techniques. In so doing they can transform the way public services are delivered, providing the high-quality, low-cost services to which the Government rightly aspires.
Emilie Sundorph, Research Assistant, Reform