The project will focus on the growing importance of real-time data and in particular how digital tools can be used to generate information in support of more adaptive, contextually relevant, decision-making and programme management and implementation.
Background
In the drive towards digitization, there are a great many issues around privacy, access, and coverage of data. There are also issues of the analysis and use of real-time data in decision-making, a process that has proved far from immediate and straight forward. And there are concerns about the risk of automating and therefore de-humanising data collection and usage. Moreover, as the use of digital technologies has increased, so too has the learning about what sorts of environmental and contextual factors can support or inhibit the use of any data generated, reinforcing the need to better understand the wider institutional environment in which data is situated.
The research project, led by IDS in partnership with FeedbackLabs, Reboot and ODI, will seek to develop a conceptual and practical framework to enable case study organisations and subsequent development efforts to navigate these challenges while maximising the potential of real-time data for adaptive management.
It will do this in the following ways:
- Analysis of relevant literature and applications of real time data from development and further afield, especially the private sector, space exploration and military;
- Deriving common principles and a framework for analyzing and designing real-time data for adaptive management interventions, with the aim of providing substantive and operational direction to future efforts;
- Testing the framework in real-world settings through a series of detailed case studies;
- Publication and communications of findings to audiences across the development and humanitarian sector, including policy-makers, practitioners, technologists, researchers and communities in developing countries
Objectives and outcomes
The research consortium’s collective objectives for this work are:
- to generate new knowledge, ideas and frameworks to help development organizations better understand the possibilities and navigate the challenges of integrating real-time data and adaptive programming;
- to test these knowledge, ideas and frameworks in ways that supports wider engagement and use; and
- to drive and support the subsequent use of this knowledge in methods, tools and processes that enhance the application of real-time data in adaptive development efforts.
The hoped-for outcomes include:
- to see these methods, tools and processes being used by policy-makers, practitioners, and researchers across the sector
- to see more higher quality programmes and policies that seek to achieve development goals through fusion of real-time data and adaptive management
- to ultimately see development goals being met in more timely, relevant, appropriate, creative and innovative ways
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