Recent world events such as the US elections and ‘counter’ revolutions on progressive issues have reminded us that we live in a complex world. As we make progress on some social issues, others encounter barriers and resistance in ways that aren’t always predictable.
The Cynefin framework distinguishes between ‘complicated issues’ and ‘complex issues’. Complicated issues have many moving parts but can be understood by expert technicians - the classic example is a Formula One car which can be fixed with the right diagnosis tools and technicians, but is a mystery to the average person.
Complex issues by contrast don’t have an operational manual and are not understood fully by any one person. The causes and effects are unknown and may change over time. Addressing climate change, or reducing harm in the child protection system, or solving housing undersupply - these and many (most?) other social issues are really complex issues.
Complex issues can’t be addressed by a single organisation drawing up a strategy and executing it. They require different players to come together and collaborate, within and often between different systems. No single person knows the answer, so experimentation and learning is the only way to make progress. The term ‘ Impact Networks’ has been popularised to describe collaborations of people and organisations that work together to address complex problems. There are people who specialise in supporting collaborations to form and build readiness for change. Latitude’s expertise is on creating the data systems that enable sharing of insights and knowledge, and using data to accelerate innovation in the design of solutions (service models).
We’ve been doing lots of work this year on how sectors can collaborate on data across Education, Alcohol and Other Drug (AOD) and Homelessness sectors.
Here are some lessons learned.
1. Data is central to effective collaborations
Good collaborations require lots of things to be successful including having a clear purpose, building trust across differences, some ‘backbone’ support, etc. But it’s hard to decide what to do without a shared understanding of facts. There are often mountains of data collected in complex systems by individual organisations, but it is seldom brought together and used by those organisations. Where multiple organisations work together, you need to be able to see the whole system, track changes, hold players accountable and compare outcomes.
2. Power needs to be in the hands of those closest to the point of service
Most impact networks / collaborations include social service providers who are funded in some way by government or philanthropic organisations. Often funders are the ones who define what is measured to track their contracts. But effective problem-solving of complex issues requires that the service providers are in the driver’s seat, not the funders. It’s these organisations that design and deliver services, and so their data is closest to the needs, and they are best placed to innovate and adjust services based on the data. Social organisations can collaborate on data to provide more insight but also to build power and influence in the system.
3. Well-designed data infrastructure and standards are needed
Our projects focus on analysing de-identified data at the individual beneficiary level data that comes from many different sources. If it’s an education collaboration that’s row-level data about students, their needs, progress, unit completions, etc. To share that detailed level of data (e.g. across 20 or 30 or more organisations) requires a sophisticated and secure data warehouse and hundreds of different coding rules to bring it all together in a consistent way. Sometimes sectors have standardised data collection requirements, but sometimes a collaboration needs to conference and decide what standardised metrics to collect.
4. Collaborating on data can lift all boats
One of the side benefits of data collaboration is that different organisations learn good practices from each other. It’s quite common for there to be large differences in size, geography and history between organisations within a given sector (like homelessness) let alone between sectors. Many organisations may have analysed their own data or developed their own monitoring dashboards, and when you collaborate, you can select useful examples from each organisation so everyone gets access to high quality tools. This also exposes more people to learning about how to use data, and builds momentum on data maturity within organisations.
5. Individual as well as collective benefits are important
The key reason to collaborate on complex problems is to make progress on the problem and break down bottlenecks in the system. However, it’s hard for organisations to maintain motivation if the only benefit is a longer term system impact. We’ve found by developing both ‘whole system’ dashboards and also individual organisation operational dashboards, we can deliver extra value at the organisation as well as collective level. For example, a tool built to analyse sector trends in presenting drugs of concern in our AOD collaboration can also be used by individual organisations to spot changes and emerging needs in their own data.
We look forward to advancing this work in 2025 and uncovering new lessons to share.
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