January 25, 2022 Data, Learning and Reflections, Programme Blogs, Programme Themes Clearer signals: moving towards purposeful multi-agency data sharing PublicationBy Rebecca Godar Over the last two and a half years, I’ve been working with the TCE Programme to design and deliver Bespoke Support Projects that aim to ‘change the conversations’ that strategic partnerships have with and about data. TCE wanted to encourage local partnerships to have conversations that are more curious, more evidence-informed and that involve people from across the complex system involved in tackling exploitation. We learnt a lot about what works and what doesn’t to shift conversations about data in this way. We developed various tools and ways of thinking about data that can support these conversations – you can view a range of resources exploring these issues on our microsite.The most important lessons weren’t about the activities we ran or the tools we used, they were about how to facilitate conversations about data to develop new insight and new strategic actions. The core insight being that leading conversations about data is a strategic role, supported by technical and operational expertise. This post outlines 10 top tips from our experience. We’ll be sharing these in more depth, with opportunities for more curious conversations, at our workshop on the 1st of February 2022. Book yourself a place: Curious conversations need time and space, and that means leaders giving their permission for people to spend time away from the day job to think and talk together. It can take a few sessions to build the trust needed for people to feel they can challenge each other’s perspectives and feel safe in offering their own. Leaders from across the partnership attending the meetings and showing their own commitment to learning is an important signal that this behaviour is encouraged.Have a clear purpose or set of questions to answer. This might be to produce an exploitation problem profile, or to investigate a particular aspect of young people’s experience, such as access to mental health services for those known to be at risk of exploitation. This provides motivation for different agencies and organisations to get involved and work to remove barriers to data sharing and access. It also sets a timeframe for people’s involvement, and an output from the work that can be shared to promote future collaboration.Be inclusive. Look out across and beyond your partnership to identify the organisations, services and individuals who might hold data that can help to answer your questions, and the analytic capacity to make use of it. Sometimes the data and the capacity don’t live in the same place and it takes strategic leadership to focus the partnership’s resources on bringing the two together.Start small, start somewhere. Some local areas initially aimed to design a new data collection process, or to match data about individuals across datasets. These approaches can be useful in the long-term, but they take a long time to actually generate the data needed to support conversations about strategy. This means motivation and engagement can wane, whereas considering what you can learn from data which is already collected, reported and shared can produce quick wins and build momentum behind the potential for bigger projects. Sometimes this means looking at existing data through a new lens – take a look at the resources on patterns of help and patterns of harm for ways of doing this.Recognise the diverse strengths in your workforce. By bringing people from different areas of the organisation or partnership together, local areas can build a network of different skills and capabilities to support work with data. Some people will feel confident with interpreting data but not have an in-depth understanding of the work. Others will have strong views about what is needed, but not feel able to make the case with data. Some organisations in the partnership might have well-developed analytic capacity, while others might not have sophisticated data systems, but hold rich intelligence through their experience of working directly with young people. In our experience, data analysts and practitioners rarely meet and don’t have an opportunity to share these skills together. Show your appreciation for these different contributions and encourage people to work together to make the most of the skills around the table.Define what you mean by data. Data can mean different things to different people. For a data analyst, data usually means structured standardised records in an IT system, which can be turned into charts and tables using software. For a researcher or an intelligence officer in the police, data might include the text written in case files, and data analysis includes reading and coding that text. We might also want to include feedback from children and young people in their own words, or reflections from practitioners about their practice. We might mean only information about young people, or we might include data about the workforce and the local community. Having a conversation about what counts as data in your partnership, and why, can help people to see that strategic intelligence isn’t just about numbers, but about drawing on as many sources as we can to get a better picture.Encourage critical thinking about data. Data has strengths and weaknesses as a source of evidence for making strategic decisions. Ignoring the weaknesses risks our conclusions being based on flawed evidence. Our data is a product of our practice systems, IT systems and governance, and so is what is not recorded (see this article on children missing from data). Practitioners are the experts in what gets recorded and why, and analysts often have a clear picture of both data quality and the quirks of the IT systems that collect it. Use their expertise to interrogate how the data is made, and think carefully about what this means for how you interpret any patterns you might find. This understanding of how data is made from practice can inform the design of new data collection practices and systems.Put data in context. Many people we worked with through the BSPs said they found working with data intimidating and confusing. They found it difficult to see the connection between the chart and their work. We found it helpful to put the data into context, using case studies, maps, and the voices of children and young people to illustrate and illuminate findings. When we did this, practitioners who had been disengaged came to life, pointing out the patterns in the data and how these fitted with their own experiences. The reflections became richer and it was easier to move from data to action when we took this approach.Talk explicitly about ethics. A familiar theme across the BSP projects was the desire to collect and share more data about individual children. This was driven by a strategic ambition to know more and to have better intelligence to inform decision-making. However, when we spoke to practitioners and service managers, we often found that people were uncomfortable with the idea of sharing information about children, particularly with the police. This fabulous blog about peer mapping highlights some of the concerns emerging on collecting data about young people only known through a peer. These are valid concerns that cannot be overcome by dictat. We found it helpful to give space to discuss the principles around balancing knowing more with respecting the rights and privacy of young people.Don’t just look for answers, look for better questions to ask. Leaders who ask questions, show humility and admit to not knowing encourage other participants to contribute their own perspectives and insight, and the gaps in their own knowledge. Treat ‘not knowing’ as an ongoing challenge to be solved – how can we know more tomorrow than we do today? Who else in our system might know more? Data doesn’t hold all the answers on how to better protect children and young people from exploitation, but it can give us indications for fruitful lines of inquiry.