We imagine each resource, each technology and data initiative, as progressing through phases. A biological metaphor might speak about conception and adolesence, to adult maturation, and then death and even beyond death.
Actual initiatives are not linear, but messy and complex and iterative. So, let’s extend our mental image from one initiative to many, to hundreds. At any given moment there are many initiatives – and potential initiatives and past initiatives – at the same time, at each phase of this life cycle.
Then for all these together and across the sector, we can speak about:
Innovation and Creation
What does it take to innovate new approaches to big problems, to recognize successes, and to develop a vision? To even articulate the challenge, map the system and the problem space, and to identifying causes and effects and levers? What organiations and methods will support the synthesis of existing ideas, programs, and resources? How can we support the creation of new public goods?
Sustain and Improve
A good deal is written about sustaining and maintaining organizations and their impact, on measuring and evaluation, and responsible ways to scale or the choice to not scale at all. Yet data initiatives in civil society have a terrible track record in this regard, not just because of funding challenges. What changes must be made and what conditions might a society create addresses these issues? What organizations currently focus on this issue, and what other organizations are missing?
Retire and Reuse
There is great need to address end-of-life concerns – what happens to assets, data, knowledge and learnings when funding runs out? How can we keep data from being as a pesticide, causing unforeseen negative outcomes downstream? There’s great opportunity to amplify cross-sector learnings outside of the research publications.
A vision for such a healthy life cycle in the sector is about doing this not just once, but improving our capacity at every phase, to be able to achieve repeated, consistent, and ever-improving successes.
Which frameworks and organizations, for example, are excellent at improving our capacity to innovate and to discover new approaches
The full life cycle of data initiatives in civil society is not given sufficient consideration. Often the focus is only on innovation, and the first public release. There’s an assumption that users and stakeholders will see value in the tool and choose to perform occasional updates, and that’s sufficient.
This lack of attention to full life cycle is emblematic of broader issues:
- Funding and programs favor MVPs and pilots over meaningul and sustained impact
- Lack of knowledge retention, few reusable assets, and work repeated on the same challenges.
- Strategic and long-term thinking is de-prioritized, or is disjoint between the organization(s) and the technology and data initiative.
- Fabriders life cycle of network-centric resources
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