Making public policy in the digital age
A week is a long time in politics. It should be a long time in policy too — Andrew Greenway & Richard Pope
In big organisations, ideas are cheap. For a long time, turning them into reality wasn’t. That is changing.
Modern design and development practices mean it is possible to prototype totally new services and iterate existing ones quickly. Teams working on digital services can test with the public in near real-time. Insights that once took years to emerge can be uncovered in days or weeks.
The effects of this trend are being seen everywhere. The State of Devops 2017 report found that even relatively low performing organisations update their online services weekly or monthly, and the better performers deploy changes hour-by-hour.
Shorter cycle times are increasingly the case with government services too. For example, the UK Government Digital Service built an e-petitions service in 12 weeks. The Peruvian government created a new, digital provisional driving licence in three months.
Yet while designing and building services has become faster and less linear, policy development — defining the set of rules and choices that shape a public service — has mostly stayed the same.
Most policy tends to be two things: 1) done up front in a separate team from those charged with implementation and 2) a long, painful process.
Policy is still largely a world of ‘target operating models’, development plans and position papers.
There are some decisions that governments make — about nuclear deterrents, say, or diplomacy — where this is clearly still the right approach. But the bulk of bureaucratic activity is about delivering services to people — things like helping people back into work, move house or access healthcare.
This is a problem, because policies and services are inseparable. In most people’s experience of the state, the policy is the service is the institution.
When the policy is broken, the service fails. And when the service fails, trust in the institution providing the service diminishes. More often that not, high-profile breakdowns are seized upon as a failures of technology or implementation. The truth is that policy is often the culprit.
So, what are the necessary ingredients for good, digital age policy development?
Setting a vision through prototyping
Prototyping is an effective way of communicating a complex policy by actually showing how it might work. It can help stakeholders think beyond their usual frame of reference and consider bold alternatives.
Rapidly iterated and tested prototypes also allow risky assumptions to be tested much earlier in the policy development process. By sketching a prototype of a service in code, it is possible to start to understand the implications of particular design choices and to identify where the really hard design problems might lie.
Multidisciplinary teams
Good policy development demands genuinely multi-disciplinary teams. Only with technologists, security professionals, designers, content, comms, legal and other subject matter experts working towards the same aim is it possible to properly understand trade-offs between things like utility, privacy and security.
One thing we learnt from this approach in the UK government context is that those people all need to be a full part of the team; semi-detached secondments are not enough. If it’s a lawyer popping in to ‘give legal’s opinion’, or a security expert doing a final sign-off, then it won’t work.
Understand the limitations of technology
Good policies require an understanding of the limitations and opportunities of technology that will be used to execute them. Good regulations require a genuine understanding of characteristics of the technology they seek to regulate. These things are especially true of emerging technologies like machine learning or differential privacy.
Trying to understand the impact of a policy approach detached from the technology that will implement it is inherently harder. To put it another way: in many cases, you only get to the answers by doing the work.
Real-world change, not ‘innovation’
There is a risk of seeing this approach as just applying technology to the current policy process, or suggesting the creation of new innovation labs. However, that would not address the core issue.
While policy makers do need to carve out space to experiment and innovate, the challenge is to make sure what is learned isn’t left on the periphery, or only applied to things with little political or societal impact.
The real opportunity is in shortening cycle times and getting better, tested services in use by the public more quickly.
It still needs to be accountable
The first step to all this is finding leaders who will put trust in the team doing the work. Those leaders will give teams the space and the power to do the right thing. This is scary, for everyone involved. Even so, we’ve seen no internet-era government succeed without creating this level of trust.
However, trust is not the whole story. Providing regular feedback of findings to the people ultimately answerable for the effectiveness of the policy-service is critical.
That feedback loop should include elected officials (or in the case of civic institutions and companies, the board and/or governors). Accountability should not be an event that happens at the end of a programme when the dust has settled and the fires put out. It should be as iterative as the team delivering the service and designing the policy.
The way laws are designed might also need to change to allow for experimentation and trials (always within well understood parameters). To borrow a programming term, legislation needs to allow for some amount of monkey-patching, where modifications can be made at run-time.
In the government context this generally means some form of secondary legislation. So, for example, primary legislation might say that a service can be made to apply to particular districts, but the exact list of districts is prescribed in secondary legislation.
Policy isn’t just a job for government
We believe public policy teams in companies and civic institutions should embrace this approach too. For example using prototyping to communicate how they might implement a particular legislative change like GDPR, or how they are responding to a particular issues in society. The work of the UK bank Monzo in using prototyping to show new approaches to managing mental health is a nice example of the latter.
Conclusion
For both companies and governments, we believe treating policy as a special case represents a huge missed opportunity.
Public policy can become faster, more accountable and more attuned to the complexities of the digital age.
To get there will require empowered, multidisciplinary teams, comfortable with testing their riskiest assumptions as early as possible, sketching in code, and working in the open. It will not take long to see the difference.
About the authors
Andrew Greenway and Richard Pope were responsible for developing the UK government’s Digital Service Standard in 2013, which all central government services are assessed against.
Andrew is a partner at Public Digital, a consultancy that helps for governments and large organisations adapt to the internet era. His book, Digital Transformation At Scale, is available on Amazon.
Richard is COO at IF, a consultancy that works with organisations to show how they can be trusted with data, and a fellow of the Harvard Kennedy School of Government.
