Organisations and city authorities need to share data to make the most of it.
Organisations in cities collect many types of useful data, including data about:
- places (geospatial data) and things like traffic lights and public transport
- services (like transport timetables and service opening hours)
- physical assets (like building ownership, or IT system documentation)
- vulnerable people and their needs (for example NHS or police data)
- addresses and information about development plans
Ways to share data include:
- in person (at meetings or events)
- in print
- via physical media like USB sticks or DVDs
- privately over the internet
- on a website in an open format with an open license
- using an application processing interface (API)
- using a third party that can offer additional services and analytics
Case study – CityVerve Manchester
CityVerve uses Internet of Things (IoT) technologies to improve city services. IoT refers to a network of devices including vehicles, appliances, and other technology that can collect data and share it with other devices in the network. If you have a smart speaker connected to a lamp in your home, then that is an example of the Internet of Things.
CityVerve focused on 4 main themes:
- culture and public spaces
- health and social care
- energy and the environment
- travel and transport
It created a ‘platform of platforms’ that allowed the city and other organisations to access multiple sources of data with controlled access. This enabled them to analyse data from different sources, fostering collaboration and innovation.
Outcomes
The project has:
- changed the usual relationship between a public body and its suppliers from customer/vendor to collaborate partnership
- broken down barriers by connecting different sources of data, which has led to new and solutions that wouldn’t be possible if the data were kept separate
- brought new ideas via collaboration with small and medium-sized enterprises (SMEs)
Source
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A collaboration between citizens and government to monitor corruption around rice subsidies and rice production programmes in San Miguel in the Bohol province of the Philippines.
The project involved citizens including farmers, agricultural technicians and local government officials in corruption and production monitoring efforts.
Factors for success
The assessment identified 2 main local factors that helped the BULHON project succeed:
- High levels of participation in community activities like village assemblies, and dense social networks between people. These mean that information spreads effectively through communities, and problems can be shared and solved together
- Local government officials being well embedded in their communities, with the boundaries between government and community being helpfully blurred and government officials readily available to everyone
Results
The research also identified positive impacts the project had for the local community, as well as achieving its main goal on corruption:
- Citizens who took part in the monitoring felt motivated and empowered, gained respect in their communities, improved their self-esteem and even made new friends
- Even people who did not take part in the monitoring themselves felt that the local government was ‘looking out for them’ and felt more able to come forward with issues
- Both farmers and local government officials felt that local government services improved, and farmers better understood the services on offer
- Because of improved techniques and use of resources, rice production actually increased in San Miguel
- Citizens, farmers and local government said that their attitudes to each other had improved
Source
Creating a logic model can help you assess the impact of your actions and interventions.
It is useful for:
- mapping benefits over different timeframes
- understanding how these benefits affect different groups of people
- communicating your rationale and direction
- testing which changes are most effective or have the biggest barriers
- defining indicators and data collection plans for your metrics
How to make a logic model
You will create a logic model in a collaborative session with a diverse and inclusive set of stakeholders.
- challenges
- activities
- outputs
- outcomes
- impacts
If the intervention is relatively well defined, you can start from the first column (challenges), and then move left to right, mapping out how they link to each other by asking questions like:
- So what does that lead to?
- What would be the result?
- Who does that affect?
If the intervention is not so well defined, you could start from the first column (challenges), then move to the last column (impacts) in order to set the vision, and then work backwards through the fourth, third and second columns by asking things like:
- So what is needed to achieve that?
- What are the preconditions?
- Who needs to be involved?
Once the content has been mapped out, you will guide participants through a prioritisation exercise to prioritise the outcomes, using a method like:
- Plot outcomes on a 2×2 of expected scale of impact’ against ‘expected ease of measurement.
- Ask each participant to identify their top 3-5 priorities and select those most commonly identified as a priority.
- Rigorously score each intended outcome using a scheme like Multi-Criteria Decision Analysis
How it helps
Now you can use your model to create specific monitoring and impact assessment materials. Tailoring your impact assessment helps you:
- Prioritise which outcomes to monitor when your resources are limited
- Identify unintended positive and negative outcomes
- Include stakeholders in setting targets
- Make sure you have a robust data collection plan with timelines
- Create materials to collect data, like survey questions and community data
- Balance quantitative and qualitative analysis
- Consider the risks and limitations of your data collection and analysis methods
Further source reading
How it works
- Answer questions on 6 themes:
- Culture
- Leadership
- Data lifecycle
- Systems
- Skills
- governance
- Get results based on your and your colleagues’ combined answers
- See how your data maturity differs across departments
- Get advice and support to improve your data maturity
Further source reading
Group interviews, focus groups and panels are similar to one-to-one interviews, with a few tweaks that make conversations with more than one person go smoothly. The size of your group can vary, but discussions tend to be best when there are between 3 and 8 people.
A group interview lets you hear from more people in a shorter period of time. And participants will often build on and give their perspective on other people’s points. This can give you a more rounded picture. But take care, a group interview can lack depth and is more prone to bias.
Follow the general interview guidance for setting up a one-to-one interview. Ask for consent, use a discussion guide, and have a structured way for capturing notes.
Extra tips for group interviews
- With more people it takes longer to go through the questions. But people still get tired, so try to keep the conversation to less than 2 hours
- Include a break if the interview is over an hour
- Give everyone a chance to introduce themselves, so that you understand the context for what they say later
- Set ground rules to make sure everyone is given the chance to speak and that only one person speaks at a time
- Even more so than in one-to-one interview, consider using visual prompts to keep everyone focussed
- Use a code in your notes so you can easily capture who said what
After introductions, check that your participant has completed the consent form if you’re using one. If they haven’t, you can ask them to complete it there and then.
Make sure the interviewee is comfortable. Let them know that:
- this is a safe space for them to discuss topics without judgement
- you are interested in hearing their perspective even if it is negative
- they don’t have to answer a question if they don’t want to
- they can take a break if needed
- they are free to stop the interview any time without giving you a reason
- they can withdraw consent later if they change their minds (up to the point anything is published, or merged with other information and can no longer be pulled out)
Accessibility
You must make sure your interviews are accessible for your interviewees. This can mean making accommodations for someone’s needs. See our guidelines on running accessible sessions for tips on making sure nobody is excluded.
Using your discussion guide
You don’t have to stick rigidly to your discussion guide. It is a guide. Listen and ask follow-up questions. Feel free to jump forward to other questions if they come up naturally. The conversation should feel natural.
If you notice the interviewee going off on an irrelevant tangent, wait for a suitable time to interrupt them, and move onto a new question. ‘I’m just keeping an eye on the clock, and I’d like to move on to…’ is always a handy excuse.
Don’t share your opinion or judgement, you don’t want to bias your research. Silence is okay. The less you say the more the participant will want to fill the space.
If you have a note taker, allow them some time at the end to ask follow-up questions of their own.
Finish up with something that signals you are at the end of the questions you intended to ask. ‘That’s everything from us, is there anything you think we should’ve asked you?’
Explain what will happen next and if you plan to follow up with them, set some expectations of when and why.
Taking notes
There are numerous ways to take notes. Verbatim, or smart-verbatim notes are best because you are recording everything that is said, in the way that it was said.
This:
- reduces the chance of misunderstandings
- makes sure you have captured all the information
- lets you quote people directly later
People can speak quickly, making it hard to get everything down. This is why recording can be useful to refer back to and fill in any gaps. If you miss something the interviewee says, note down the time, so you can easily find the right spot in the recording.
Taking notes and recording the conversation can be trickier if you are interviewing in person rather than online. Focus on capturing specific data, and if you can’t capture verbatim notes, try to get the overall sentiment of each answer.
If you are interviewing multiple people (either in a group session, or in multiple one-to-one interviews), you can use thematic analysis to see what findings are similar across your range of participants.
A research interview is a discussion between a researcher and one or more other people.
The researcher is trying gather evidence that will help make decisions on a project. The researcher could be you, someone else in your organisation, or someone you have brought in to carry out research for you. Using an experienced professional user research team can help make sure your research is ethical.
An interview can give you insights about complex topics, including how people feel about things and why. These kinds of empathetic insights can improve your decisions or creations, by taking a diverse group of people’s challenges, needs, experiences and perspectives into account.
Setting up
Interviews are most often done one-to-one, but you can also do group interviews and run panels with more people. You might decide to have a separate note-taker so the interviewer can concentrate on the conversation.
You will need:
- to write a discussion guide (we’ll explain how!)
- somewhere to write notes
- an agreed method for capturing notes
- details about the research to send to participants
- a consent form or other way of getting and recording interviewee consent
45 minutes to an hour is usually enough time to get good answers before everyone gets too tired. But that may differ depending on how complicated the subject is.
Depending on what you are trying to find out, it can sometimes be useful to have visual prompts or prototypes for the interviewee to respond to.
Writing a discussion guide
A structured discussion guide will make sure the interview flows well, that you ask all the questions you want to, and that you ask the same things of different people.
- Write down what you want to learn from the interview. This could be a high-level research goal or a list of themes you want to cover
- Use this to break up your document with subheadings
- Start the script with an introduction to who you are, who you work for, and what the conversation is about
- Next, write questions under each subheading
- Use open questions that cannot be answered with a simple ‘yes’ or ‘no’. Instead of leading the interviewee towards a particular answer, open questions let them answer however they want to. And their answer can open the conversation up for follow-up questions
- Don’t go straight into any big, difficult questions as you may intimidate the interviewee. A good way to break the ice is by asking questions about themselves like ‘Tell me about your typical day’
- Get feedback on your discussion guide from others on your team. They might think of some important questions that you’ve missed
Participant information letter
A participant information letter (PIL) is an overview of what the project is about. It should give participants enough information to make an informed choice about whether they want to take part. It must be written in clear plain language and will usually be about 2 pages long.
Some things you should include in your Participant Information Letter include:
- What the project and interview is about
- What they will be asked to do if they take part
- Whether they will be getting paid or incentivised in some other way
- What personal information you’ll be collecting and storing (in line with your organisation’s policies)
- Whether their participation will be anonymous and confidential
Writing a consent form
Your consent form goes alongside the participant information letter. On your consent form, ask for confirmation that the interviewee has read the participant information letter and that they have had:
- a chance to ask questions
- their questions answered
- the complaints process explained to them
Check that they understand that they can:
- refuse to answer any question
- withdraw from the interview
- change or withdraw their consent
- complain about anything that happens to them
all without having to give a reason.
If applicable, also check that they understand:
- who you might share information from the interview with
- any risks there might be of taking part in this research
- that the interview will be recorded, what the recording will be used for, and who (if anyone) you might share it with outside your organisation
- that what they say might be included in research reports (using their name, organisation, role, or no attribution at all, depending on what you agree about the level of anonymity)
- you won’t share their personal details with third parties (outside your organisation)
- that you may take photos or video and use them in research reports that you might share with third parties (outside your organisation, who you are working with)
Organise a time and send details
Agree a time for the interview. Send the interviewee all the information they’ll need with plenty of notice. If they feel informed and prepared, they will be more relaxed in the interview.
Include:
- the consent form if you’re using one
- the video conferencing link or directions to a venue
- background information or sample questions
The methods and case studies under the theme of Gathering Evidence will help you:
- carry out experiments, surveys, observations and measurements
- find clues or proof that help you figure out if something is true or if it works
- understand if an innovation or invention is good or helpful
For example, if someone claims ‘This new app helps kids learn maths better’, evidence could include be test scores or feedback from kids who used the app.
Why is evidence important?
Evidence helps us make good decisions.
Let’s say a group of people wants to build a new playground. They’d need evidence to know if kids will like it, if it’s safe, and if it fits in the community.
They might collect data by asking kids what they want, watching how kids play, or testing the materials. This way, they can make sure the playground is fun and safe for everyone.
Evidence is like a guide that helps us avoid mistakes and make things better for people, especially those who are often left out, like disabled children or people in poorer communities.
Types of evidence
There are 2 main types of data: quantitative and qualitative.
- Quantitative means counting or measuring things with numbers. For example ‘there are 10 apples and 5 bananas in the basket’
- Qualitative data means describing the qualities of or your experiences of something. For example, ‘the apples are sweet and crunchy, and the bananas are soft and perfect for smoothies’ It’s all about the details and feelings!
Together, these 2 types of data help us understand not just how many fruits there are, but also what they’re like and why people enjoy them.
Inclusive innovation metrics
Inclusive innovation metrics are ways to measure if an innovation helps everyone, especially marginalized groups, and the environment.
For example:
- What are the backgrounds of people who are using this?
- Can disabled people able to access it easily?
- Were people, especially those often left out (like women, minorities, or young people), involved in making design decisions?
- Does it improve people’s lives in marginalised communities?
- Are innovations supporting good energy use, reducing waste and harmful emissions?
- Are innovations improving people’s health, like access to clean water, healthy food or healthcare, and the health of the planet?
- Are innovations supporting biodiversity, like plants and animals?
By tracking these things, we can create a fairer, healthier, and greener world for all.
