How can new data sources and real-time information systems improve decision-making?
Innovation and data are also important themes in the larger Sustainable Development Goals agenda. It underpins the entire agenda as a vehicle to solve “wicked challenges” across all the SDGs.
One example of real-time information systems is UNICEF’s U-Report, a simple SMS tool that enables decision-makers to source the opinions of young people. Currently, U-Report is live in 21 countries and more than 2 million people are sending or receiving messages every week. A recent poll of U-Reporters in Liberia triggered government action to address the rampant problem of sexual abuse of students by their teachers.
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“Phones against Corruption” is a SMS-based tool powered by UNDP to report corruption in real-time in Papua New Guinea. A first version was made available to 1,200 public servants and within four months, more than 6,000 SMS were received and investigated. There are now over 200 cases of alleged corruption under investigation.
These initiatives are not worthy of mention because they leverage mobile phones or include an app, but because they are examples of initiatives that led to actual action.
They influenced decision-making and were designed based on innovation principles that underscore the importance of designing with the end-users.
Leveraging new and emerging data sources to improve humanitarian aid and development is the second component of our question at the WHS.
For example, can the analysis of airtime credit purchases help to understand nutrition patterns and monitor food security? WFP and U.N. Global Pulse tested this and found that proxies derived from mobile phone data can provide valuable real-time information on food security. In Kosovo, UNDP and U.N. Global Pulse tested whether data analysis can help to improve emergency services, showing that analyzing anonymized emergency calls can help predict peak times and locations of future emergencies.
Our responses to the question of how new data and real-time information systems can improve decision-making are very much work in progress. However, we believe that the underlying principles are worth pursuing for future innovation.
Here are four thoughts about the future of data in development:
1. Ensure representative data.
Traditional data collection mechanisms often have built-in biases and are particularly prone to overlook women’s unpaid work and agency. We have to work with National Statistics Offices to develop ways of collecting inclusive and contextual data — for example, thick data with ethnographic methods.
2. Plan for data equity.
More and more governments have opened up large data sets to its citizens in the spirit of transparency. “Provide it and they will use it” is the logic. But this requires data analysis capacities that few people have. Data needs to be provided in a more accessible way to all parts of society, particularly the most excluded.
3. Invest in R&D to understand the user’s needs.
Currently, the majority of the user research is based on small samples and difficult to scale. Data needs to support people’s agency. “We should ask at every step of the way how can we empower communities and frontline workers to take better decisions over time, and how can we use data to enhance the decision making of every actor in the system,” argue Isobel Roberts and Giulio Quaggiotto.
4. Navigate politics.
Data innovation is about triggering change. This will necessarily lead to some being empowered, while others losing either material assets or privileges. “Despite innovation efforts and optimism across the development sector, few innovations lead to actual sustainable, systemic change,” the Overseas Development Institute noted in “Innovating for pro-poor services: why politics matter.” Barriers for scaling up innovations are often political in nature, and navigating these politics must be transparent and planned for.
The innovation discourse in the humanitarian and development spaces is evolving. The global networks launched at the WHS, the Global Alliance for Humanitarian Innovation and the Global Humanitarian Lab, are a testament to this. Their focus on supporting local innovators and partners reflects that our innovations will not solve their problems. Data innovation needs to provide communities, individuals, and governments with the means to trigger change. It is our mandate to ensure it benefits the most marginalized and protects human rights of everyone.
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