An introduction to Open Policy Making and design
This section introduces design, digital, data and Open Policy Making and tell you when to use this Toolkit.
Getting started with Open Policy Making
Defining Open Policy Making
Open policy making helps civil servants create and deliver policy that meets the demands of a fast-paced and increasingly digital world. It means that policy that is more informed and better designed for both the government and users by:
Open policy making is about developing and delivering policy in a fast-paced and increasingly networked and digital world through:
- using collaborative approaches in the policy making process, so that policy is informed by a broad range of input and expertise and meets user needs
- applying new analytical techniques, insights and digital tools so that policy is data driven and evidence based
- testing and iteratively improving policy to meet complex, changing user needs and making sure it can be successfully implemented.
How to be an Open Policy Maker
Be open to new ideas and new ways of working
Listening to new ideas and engaging people will give you new insights and help you see problems from a different point of view. Design thinking and agile working are examples of new approaches that can help seeing a problem from a user perspective.
Read Policy Lab’s introduction to design in policy making for more information on design thinking and policy making.
Gathering evidence, information and a broad range of views is vital. It is important to be humble about what you know, and what you don’t know. Open policy is about recognising that you are not the only expert and that you do not have monopoly on good ideas and policy development. Where good ideas exist, it is your job to find them.
Be prepared to be told something is not working and open to new suggestions, data and evidence. This will help you to understand different points of view and make iterative improvements.
Understand the real needs of users
Understanding user needs will help you develop policy that works for the people it impacts. Begin by understanding how users currently experience a policy and go from there.
- How do users want to experience a policy once implemented?
- What are their needs from the policy?
- What is going to make a user experience positive or negative?
help you to understand who your audience are and how they work.
Involve the public
Engaging with the public will help you understand and gauge the public mood. The people with the most knowledge of how services and policies are working are those that it experience it first hand. Their experiences can help you to understand the needs of citizens and create more informed ideas.
Work with experts and engage with new knowledge
Experts can help you to better understand a policy problem, review possible solutions and challenge assumptions.
Experts include user researchers and ethnographers who work with users to understand their experiences and problems. Designers can help to create innovative policy ideas throughout the policy cycle and facilitators can help you talk to the public and engage in an open and safe environment. Academic experts and subject matter experts can bring new knowledge to a policy area. Digital experts open up the possibilities of engaging at scale and analysing large volumes of evidence at pace.
Test and use evidence to improve your policy as you go along
Test and and iterate policy solutions to make sure they will work for users in the real world. This will help to take a policy from the idea stage to a deliverable product that works.
Use data to learn, prove and succeed
Use data to generate new insights and learn what is working and what is not. It can tell you about who your audience and users are and help you understand what the problem is from their perspective.
Policy Lab: an introduction
Policy Lab is bringing new approaches to policy-making. From data science to user-centred design, it provides fresh thinking and practical support, working as a research and design testing ground for policy innovation across government.
The Lab is funded by departments and works on projects coming from all parts of government.
Open-policy making is important to the Lab’s approach. Policy Lab creates a neutral space for policy-makers to collaborate across departments and engage with the public and external experts in key policy areas. This involves a rigorous, collaborative process, working in close partnership with policy teams and using a range of innovative tools and techniques.
The practices of Policy Lab are described throughout this toolkit and in the Policy Lab Methodbank.
Policy Lab support is best suited to addressing intractable, complex, systemic policy problems that require fresh thinking that can lead to potentially transformative solutions.
So far, Policy Lab practice has involved 3 main areas of focus:
- providing new policy solutions through inspiring practical projects
- building the skills and knowledge of the policy profession and wider civil service
- inspiring new thinking and innovation in policy through writing and experimenting
The Lab’s approach is agile, flexible and iterative and can help departments in many ways.
- supports policy teams to identify new insights into the needs of service users
- generates ideas that can stimulate innovation and transformational change
- acquires knowledge and expert opinion to inform policy development
- creates opportunities to make policies more deliverable through testing and prototyping
- produces efficiencies and cost savings
Policy Lab has so far worked on 10 practical projects ranging from policing in a digital age to family mediation and the future of ageing. As of November 2015, 2,500 civil servants who have been involved in lab lights, sprints, policy schools and learning and development training courses. The Lab has also engaged with over 5,000 people inside and outside government through talks, workshops and its online presence.
Policy Lab offers lab taster sessions, which are an opportunity to work up a project idea in an introductory workshop for policy teams who may be interested in running a lab project. These are usually followed by policy sprints, which are more intensive, collaborative workshops over 1 to 3 days designed to help teams accelerate a project.
Lab full projects can run from 3 months to a year and involve working intensively with service designers, ethnographers, data scientists and subject specialists on complex challenges. Policy Lab also runs experiments designed to develop a number of policy ‘firsts’ for government. The Lab invites departments to set a challenge or get involved to try new ways of working through one-off trials of new and emerging techniques.
If you are interested in working with Policy Lab email firstname.lastname@example.org
Themes of Open Policy Making
Making policy iteratively and quickly: agile policy making
Agile policy making: an introduction
Agile is more of a mindset than a tool or technique. It was initially conceived by software developers in the 1990s, and has been adopted in digital service development in government, but it can be applied to policymaking too.
It works well where things are unclear and non-linear, when you don’t know with certainty what might happen. It asks you to put the user first, thinking about what they need, rather than what might be easiest for our organisations. You can then co-design and develop ideas iteratively, with feedback from users improving them.
It encourages multi-disciplinary teams, recognising that fresh perspectives create better ideas. You must be flexible and adaptive, open to new ideas, opportunities and feedback.
Agile in digital services
GOV.UK and all digital services on it are built using agile methodology. The Government Digital Service has an extensive introduction to Agile, which can be very helpful for policy makers too.
Examples of agile policymaking
Policy Lab worked with the Department of Health and the Department for Work and Pensions to support people to manage their health conditions and stay in work.
They organised this work in a series of short policy sprints (short project bursts). The first was a 3-day session with a multi-disciplinary team including policymakers, data scientists, ethnographers, designers, GPs, employers, Jobcentre staff, community organisations. They spent time understanding the problem and developing practical research and co-design solutions with users.
The plan was flexible with weekly ‘stand up’ meetings to adapt the plan according to the insight the research was generating and from user feedback from the prototype policies. This helped to create better ideas through recognising different perspectives and listening to user responses.
Designing policy with users: co-design
Designing with users: co-design
Open Policy Making is about working with users to understand their problems and create policy that works for them.
The process of creating products, services or policy with users is called co-design.
Co-design is a way of working that creates policy directly with the people that policy impacts. Co-design and Open Policy Making believe that are experts in their own experiences, and can bring different points of view that inform and innovate a policy’s direction. Co-design puts users at the core of policy creation so that policy is more informed and responsive to their needs.
This often takes the form of workshops, hack days and idea jams. These events let users explain their current problems and then work with policy makers and designers to come up with solutions for the future.
Co-design can work at any point in policy design, however it is most commonly used at the beginning of a policy to help understand where a policy needs to focus.
Co-design and policy making
Co-design can be done in a number of ways with policy making. Policy Lab and the UKTI Ideas Lab use co-design techniques to make sure that all the policy they create is designed around the experience of the user.
Hack days and ideas jams are events that can run for hours or days and are a popular tool for co-design working. They bring in experts, users and outside knowledge to approach problems from new perspectives and develop solutions quickly.
Workshops are another way of co-designing policy. Tools like challenge setting, sketching and change cards can quickly improve understanding of a problem and the direction any solution needs to take.
Open data is also an important part of co-design. Open data used at hackathons can bring in outside expertise and help you to design innovative solutions, quickly and easily.
Reading and information
There is a large amount of literature on co-design. Steve Hilton’s book More Human looks at how co-design and open policy can impact policy and government.
UX magazine has an in depth look at co-design and how to do it.
Using data to inform policy: open data
Open data: an introduction
More data is being generated than ever before, from apps and devices people use everyday, to the administrative data that government departments keep on their services and customers. Open data can benefit policy in numerous ways. It:
- brings in external thinking through hack days to open eyes of ministers and officials to design better solutions. This has been used at places like MoveMaker and SkillsRoute
- can help policy makers work with voices of citizens and create choice for users. Ofsted’s school dashboard has done this with schools to help parents choose
- creates a different relationship between citizen and state, increasing awareness and sometimes encourages engagement
Not all data is fully open. Like Open Policy Making there are scales of openness. The Open Data Institute (ODI) spectrum helps you to see how open you can be. Read more information about Open Data from Open Knowledge Foundation’s School of Data and Open Data Institute.
Examples of open data
Citymapper is one of the best known examples of open data. It takes data from transit authorities and the public sector around the globe to make cities easier to use and ‘reinvent the transport app for the world’s most complicated cities’.
There are also prototypes on GOV.UK that highlight how open data can be used to report on the success of a policy. These prototypes are not working yet but they do show how policy can work with digital and open data to improve understanding of the policy. View the prototype on housing and free schools
Why you should use data to understand
Data science techniques, such as clustering and predictive analytics, can help to identify an issue quickly, and allow you to make interventions earlier to avoid a major problem occurring.
For instance, by analysing comments and feedback data from GOV.UK, it’s possible to see where most complaints are occurring, who is involved and how to mitigate against the issues reported in them.
One example of this is passports. If complaints are increasing in frequency, and often contain words relating to the online service failing, it is possible to undertake maintenance at an early stage to avoid complete service failure.
How to use open data
1. Get the data
Open data is often useful to further augment existing data to improve your knowledge and cross reference information. Open data is free and available from UK Data Archive, Data.gov.uk and the Office for National Statistics.
Often the best approach is just to explore. There are many places that hold openly available data that can be used for analytical purposes. Policymakers should seek data and not be overly prescriptive about traditional methods of understanding policy issues.
2. Use data to identify policy issues
Data visualisation techniques can make your data more compelling and show where policies are failing to reach their intended targets.
An example would be the visualisation of the LSYPE (Longitudinal Study of Young People in England) survey data to show transitions between different aged cohorts. By viewing data in this way it is possible to find trends, such as the large number of people moving from family care into unemployment between the ages of 20 and 21. This highlights an area to look at further and and begin to create policy interventions around.
Data visualisation, analysis and open data are often specialist tools and working with experts is often necessary.
Ethical implications and privacy concerns in using data
There are many ethical and privacy considerations when using data. Data that is heavily aggregated will be safe to use, but will not always make for compelling or useful analysis. Personal-level data is great for bespoke tailoring of services and interventions, but creates potential issues around privacy and protecting the anonymity of citizens.
Policymakers should think about what they are trying to achieve and how it could impact on the privacy of citizens. They should ensure that they are working within the knowledge and information management guidelines set out by their departments, and the terms of the Data Protection Act.
Understanding user needs: user research
This guidance provides a broad overview of the methods and techniques available to conduct user research. Research can incorporate both qualitative and quantitative techniques.
Qualitative techniques are intensive and often small scale. These include focus groups and one-to-one interviews, and are typically used to explore and analyse unstructured data.
Quantitative techniques involve higher-volume research, and include online surveys, face-to-face interviews, and involve a structured approach to data collection and analysis.
Read more about user research in the Digital Service Manual.
Understanding the emotions of users: ethnography
Ethnographic research usually involves observing target users in their natural, real-world setting, rather than in the artificial environment of a lab or focus group. It aims to gather insight into how people live; what they do; how they use things; or what they need in their everyday or professional lives.
Read more about ethnography and how to do it in the government service design manual.
How to measure the impact and success of Open Policy Making
- Initial questions
- Examples of measuring success
- Types of success
- When to measure success
- How to measure success
- Government guidance
Measuring success in open policy: an introduction
There is no single way to measure the impact or success of a policy; each policy should be evaluated individually and according to its nature. It is important that the measurement of success is built into the design of policy from the outset.
Many policy makers talk about measuring success, but it’s vital that you’re clear on what constitutes success. For example, getting 20,000 young people onto a youth programme is an achievement but it is not an impact. Have they gained anything from it? Has it had any negative impacts? Is the programme being run as intended?
Some initial practical questions to consider
- what evidence do I need?
- are there certain questions which will be asked of me after implementation in order to meet objectives?
- is there an opportunity to add to an existing evidence base?
- who is this programme likely to impact and in what ways?
- what am I trying to achieve? Consider creating a theory of change
- how can I work with my main stakeholders and analysts?
- is there already evidence I can use to inform the development of my policy/programme eg held by What Works centres?
- who is doing work in this area, eg academics, think tanks, that I can link up?
Examples from around government
In 2014 to 2015 the Behavioural Insights Team worked with HM Revenue and Customs (HMRC) to understand how they could encourage small businesses use government programmes that they could benefit from. They investigated how HMRC could use existing communications channels differently to prompt and inform.
One option considered was whether they could contact businesses at the same time as they would for other matters (such as VAT returns). As there was some concern that providing extra information might detract from the core HMRC message, they ran a trial.
The trial used almost 400,000 HMRC emails to communicate to small- and medium-sized enterprises (SMEs) about the programmes they might benefit from. Businesses were randomly allocated to 2 groups; those that received the old type of email message and those that that received the new email message, which contained information on government programmes. A variety of ways of conveying information within the email messages were also used.
The trial showed that simplifying the messages worked very effectively. But the team also found that some messages were more effective than others. Telling firms that their type of organisation had been chosen to receive information on the programmes was the most effective of all. The sheer number of emails also significantly increased sign-ups to the programmes, demonstrated by the peaks in demand in the period following the release of emails.
Types of success and impact measurement
Measuring and evaluating impact must be considered upfront at the policy design and scoping phase, and then continuously throughout policy delivery. To evaluate successfully, certain measures which need to be put in place, and questions which need to be asked, before the policy or intervention begins. Examples of these are:
- establishing a baseline: what is the state of a policy before any changes to it are made, or before any new policy is designed and introduced?
- establishing a control group: do I need to measure what would have happened anyway if certain changes hadn’t been made to demonstrate it is my design/policy which has been effective and not something else?
How to measure success and impact
When considering an evaluation or impact assessment it’s always worth involving analytical colleagues for their advice. Whether you want to conduct a small scale, in house evaluation with minimal budget, or commission something larger out such as some randomised control trials, analytical advice and guidance is likely to be useful.
It’s also important to involve those delivering and designing the policy in the process from the beginning. This will help you to understand what is feasible and will hopefully secure buy-in to the evaluation process.
- The Magenta Book: central government Guidance on evaluation best practice for policy making
- The Green Book: central government guidance on creating and analysing policies, programmes and projects
- Test, Learn, Adapt - Developing Public Policy with Randomised Control Trials: Behavioural Insights Team guidance on building randomised control trials into policy development
- Principles of Impact Evaluation (OECD)
- Inspiring Impact: funded by Cabinet Office and BIG Lottery Fund, a programme to encourage high quality impact measurement
- Charities Evaluation Services: Part of NCVO, a useful hub of various evaluation tools and resources
- UNICEF Impact Evaluation: series of videos aimed at not for profits conducting their own impact assessment.