How Big Data Can Help the Developing World Beat Poverty [VIDEO]


The United Nations also see the possibilities of big data and in 2009 the U.N. Secretary-General Ban Ki-moon launched the initiative Global Pulse. Global Pulse serves as an innovation lab and they aim to raise awareness of the opportunities of big data and bring together different stakeholders such as big data scientists, data providers, governments and development sector practitioners. The objective is to help catalyse the adoption of big data tools and technologies and to help policymakers understand human well-being and emerging vulnerabilities in real-time, in order to better protect populations from shocks. Not only the U.N. is involved with exploring the big data opportunities for the developing world. The World Economic Forum is discovering the possibilities. The WEF developed a white paper discussing the possibilities of big data and the new possibilities it offers for international development. The World Bank is researching big data and they have developed a map that visualizes the locations of World Bank-financed projects to better monitor development impact, improve aid effectiveness and coordination, and enhance transparency and social accountability. Finally, the International Aid Transparency Initiative makes information about aid spending easier to access, use and understand. Of course these are just a few of the many new initiatives. Anoush Rima Tatevossian, who leads the global strategic partnerships and communications for the United Nations Global Pulse, notes that big data “offers a new tool in the development toolkit, and must be approached with a nuanced appreciation of its power, and also of its limitations”. She remarks that there is a long way to go and with this post I would like to share my opinion on how big data can help the developing world beat poverty.

Mobile Data

For the vast amount of the poor, a simple or basic mobile phone is the only interactive interaction with the World Wide Web. Although in the developed world smartphones may seem to be the common device, they still only account for 10,44% of the global mobile website traffic. On the other hand, traditional mobiles take up 78,98% of mobile worldwide website traffic (with tablets taking 10,58% of the traffic). Luckily there are vast opportunities for the developing world to use data created by basic mobile devices to identify needs, provide services, and predict and prevent crises for the benefit of the poor. Cignifi, a Brazilian startup, for example developed a technology to recognize patterns in the usages of mobile devices. The system recognizes phone-calls, text messages and data usage and based on this information it can recognize someone’s lifestyle and his/her corresponding credit risk profile. Cell-phone Call Detail Records (CDRs) as Cignifi uses to determine the credit risk profile, capture vast amounts of data that can be analysed. Data such as time, location, recipient’s location, duration of call etc. provide extremely valuable information when analysed correctly. As Emmanuel Letouzé describes on his blog, CDRs from a city in Latin America could predict socioeconomic levels. But CDRs are not the only mobile data that can be used. What about the data from the 100 million users that use the app Facebook For Every Phone? Most of the Facebook users in the developed countries have probably never heard of this app made by Facebook, but every month it has 100 million active users that connect with each other via their mobile (not smartphone). All this valuable mobile data can be used and when combined with other data sets can help citizens in developing countries.

Use cases

The Engineering Social Systems department (ESS) of Harvard has collected several inspiring use cases. Big data offers for example the possibility to predict food shortages by combining variables such as drought, weather conditions, migrations, market prices, seasonal variation and previous productions. Or what about the possibility to better understand the dynamics of slum residents using mobile data to develop predictive models to better serve the poorest. For example using CDR information to map changes in the slum population and direct latrine and water pipe building efforts for the benefit of the slums residents. Time-series analyses performed on CDR combined with random surveys can lead to better insights about the dynamics of rural economies and provide insights on how governments should respond to economic shocks in rural and poor environments. The World Bank shows an example where big data is used to ensure the right distribution of the right medicines to the right location at the right moment in time. A pilot programme called SMS for Life improved the distribution of malaria drugs at a health facility level in rural Tanzania, reducing facilities without stock from 78% to 26%.

Big data as a catalyst

Big data can be as a catalyst for long lasting improvements, but we will have to look further ahead to see that. Mobile data alone is not sufficient to really create opportunities that could impact developing countries on the long term. Therefore, more data sources are required, ranging from data from NGO’s, to public data and social data. There are so many different NGO’s active in the developing world, which all do very valuable work to beat poverty and reduce diseases or hunger. What if all those NGO’s would use one standardized mobile app (smartphone or tablet) to collect data (a pre-defined set of metrics) in the same consistent manner across villages, countries and continents? It would could create a fantastic high-level overview of what’s going on in the developing countries. When the data collected by the NGO’s is combined with data from the mobile devices carried by the citizens, social data from applications like Facebook For Every Phone, world food market data and with the public data of the (local) governments, big data can truly have a long term impact on poverty by the insights that can be derived from such a vast amount of data. The question of course remains, why should NGO’s cooperate in such a tool? Well the answer to that can be simple: if you share data you can use data. It will enable the NGO’s to do a better job. Even more, the same data can also be shared with the private sector, such as for example FMCG companies or manufactures that want to obtain a better view of the emerging markets. Of course, only when private companies also share their data. This is already happening and it is called “data philanthropy”. The World Economic Forum refers to it as “corporations that are encouraged to share anonymised data for use by the public sector to protect vulnerable populations.” Nike is one of the pioneers on this approach, as they share data from the 57.000 different materials they use with the entire supply chain. Of course, also governments should open up their data to the public, private organisations, NGO’s, journalists and entrepreneurs. Kenya is one of the pioneers in Africa regarding opening up their data. As the World Economic Forum report notes: in 2009 they opened the Open Data Portal where the government shares 12 years of detailed information regarding their expenditures, household income surveys as well as health facilities and school locations. The portal can be accessed by anyone via the web or via mobiles. As is the case in the developed world, governments in the developing countries should take the lead in creating the legal framework for sharing and using open data in order to protect privacy and ensure transparency, simplicity, compatibility and security. In addition, the governments should stimulate the development of the required technical infrastructure and to create an environment where smart individuals and organisations can use the data to create new tools and applications. Governments can organize hackathons to develop, together with entrepreneurs, new solutions for the poor. This will enable that the data can be updated continuously via different organisations and becomes available and useful to the citizens. Big data does however require also a cultural and policy change as a blog post by the World Bank shows. Data in a study by Esther Duflo and Abhijit V Banerjee among 18 developing countries showed that the people in those countries are not literally starving of hunger (the study showed that they received enough food) but that their diets were not sufficiently nutritious. Meaning that government should not provide or subsidize more rice or noodles, but provide or subsidize more nutritious food. A very important difference that was made visible with big data. Big data offers many opportunities for the developing world to beat poverty, but it will require different organisations to work together in order to achieve lasting results. In addition, the joining organisations should ensure transparency and availability of the data. Transparency will stimulate awareness of the possibilities, ensure data accountability and reduce bureaucracy and corruption. Availability of the data will ensure that multiple data sources can be fused, such as CDRs, open data, social data, government data, NGO data and corporate data, to create valuable and relevant new insights that will truly have a long term impact. Check out Global Pulse’s video on what they do exactly:

Image: By Valter Campanato/ABr via Wikimedia Commons
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image:developing nation/shutterstock The amount of data created is not only growing in the developed world, also the developing world is experiencing rapid growth in data creation. However, a large part of the data created in the developing world has a different origin than in the rest of the world: the developing world is progressing rapidly to the mobile era and is largely skipping the desktop and wired era. This requires a completely new approach, but also offers a vast range of possibilities to beat poverty.