How to build local data projects that can be scaled and reused
While many data-related challenges and problems are similar across organisations and sectors, it's easy to assume these challenges are unique, and to develop solutions in isolation.
For example, an open data-powered app could potentially be re-purposed across other sectors and datasets. There would be many benefits for local organisations – around economy of scale and shared-learning – of reusing and repurposing the resulting methodologies and products for similar data-related challenges.
This research project, as part of the ODI’s R&D programme, explored how we could help projects which have worked in one area to either grow to a larger area – or be picked up by a new team in another area. When this happens, successful projects and services can benefit a greater number of people.
Scaling data innovation: why is it important?
We see two ways a project or initiative can ‘scale’:
- It can scale up. A project/initiative that has worked effectively at a small scale can be scaled up to improve systems, ensure sustainability, or cover a wider geographic area or a larger population base. This could be managed solely by the original project team, or in collaboration with partners, or franchised to an external supplier.
- A project/initiative can also scale out by being repeated, repurposed or re-deployed across other sectors, organisations or areas. The project team can share learnings and allow others to build on and reuse their work.
- Blog: How to design to scale – lessons about local innovation
- Case studies of local innovation
- Scaling data-enabled projects: barriers and checklist
- Innovation network and scaling data initiatives
- Blog: How can we scale up local data-enabled projects?
At the close of our scaling data innovation project, we wanted to talk about our findings. Read How to design to scale: lessons about local innovation.
As part of the project we visited teams across the UK who are using local data to bring benefit to their areas. Whether that is helping people make more informed educational decisions, supporting those in recovery from addiction or to track worklessness in an area – we wanted to highlight projects doing interesting things so other people can learn from them or try to replicate them.
The five case studies are:
- Addiction Recovery Companion: Supporting those in addiction recovery
- Glasgow City Council: A city-wide approach to innovating with data
- MyEd: Find a place to learn from ‘cradle to career’
- Smartline: Smart wellbeing inspired by the community
- Trafford Data Lab: Revealing patterns in worklessness data through visualisations
Our research identified a number of barriers which could prevent projects such as those described above from scaling up or out. These are broken down into key themes: data, technical, resources, knowledge and collaboration. The checklist aims to help those involved in designing, planning or running products and services to explore the issues that might help them scale beyond short-term or small-scale products.
Learn more about our work with Arup (design, engineering and technical consultancy) around building a network of open innovators and scaling data innovation.
This blog post describes our research into helping local data-enabled projects scale up, and the opportunities and barriers around scaling. Read How can we scale up local data-enabled projects?
We hope that people share their project stories so that more people can learn about them and learn from them.
Background and funding
This work is part of a three-year innovation programme, running to March 2020 with a funding profile of £2m each year from Innovate UK, the UK’s innovation agency.
Through our R&D programme, we aim to shape future services and promote productivity and growth with cutting edge expertise.
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