This resource is developed by and for open government influencers - civil servants and civil society representatives seeking to collaboratively make governance processes transparent, participatory and accountable. It is intended for those who want to be an open government influencer.
The original guidance includes recommendations and experiences from experienced leaders in Europe and Central Asia. It follows the publishers' joint journeys in navigating challenges to creating an enabling…
User Type: Policy maker or adviser
This resource is a series of tools to help clarify, plan, collect, and use data, information and evidence to evaluate an innovation as well as spread the learnings and results. It is intended to be used throughout a project to incorporate evaluative and intentional processes and feedback loops.
This resource gives the real story of how government innovation labs develop in the development context in Eurasia, Asia and Middle East: organic and people-driven, often operating under the radar until safe to emerge. It shares a truthful examination of the twists and turns of seeding, starting up and scaling labs, covering the challenges UNDP faced and their failures, as much as their successes. It includes in-depth histories and lessons regarding 4 UNDP innovation labs.
The resource is meant…
This resource contains two guides: one about the general field of behavioural economics and another is on developing behavioural interventions for randomised controlled trials (RCTs). The website also contains an academic directory of researchers working in this field.
The GovLab's Public Problem Solving Canvas is an online interactive canvas based on twenty questions to create and develop your public interest project. These twenty questions are designed to help you refine your understanding of the problem and those whom it affects; express your Big Idea; and turn that idea into an actionable strategy in the real world to the end of improving people's lives.
The term data collaborative refers to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors — including private companies, research institutions, and government agencies — can exchange data to help solve public problems.
This resource outlines 8 Phases for designing and implementing a data collaborative (partnership) at an institutional level. The online resource includes examples, enablers, tools, and resources for…
This mini-book is based around the Cynefin framework, a contexutalisation and sense-making framework developed by Dave Snowden. The resource provides an overview of the Cynefin framework and use of narrative research, guidance and a tool for developing shared sense-making, and tools and guidance for developing a portfolio of experiments for different types of problems, distinguishing between complicated and complex problems.
The publisher requires a free login in exchange for downloading the…
The resource was designed to help organisations: develop a clearer understanding of the range of purposes of collaborations, reflect on the partnerships they have established, and focus on ways to strengthen new and existing partnerships by engaging in discussion about issues and ways forward. The resource contains guidance as well as an interactive partnership assessment tool.
Although it was created with the health sector in mind, it is relevant for other sectors as well.
For innovation…
This is a LinkedIn article exploring what a canvas for an Experimentation System should include. It is a way to visualise an experimentation system in a one-page view. It's author says it bring hundreds if not thousands of actions and decisions into context and helps to translate nebulous terms like 'innovation culture' into practical actions. The article offers explanations of the 20 building blocks and offers the canvas via email request.
This resource includes a framework, basic guidance and canvas for use in mapping and assessing organisational readiness and capacity development, designing and developing assessment criteria for capacity-building, facilitating strategic dialogue, supporting and assessing the impact of innovation teams and labs, and enabling structured focus on what elements should be prioritised in capacity-building efforts as well as for case production and knowledge sharing.