In September last year, world leaders agreed on a set of goals to improve the state of the world as part of a new sustainable development agenda. The goals are known as the Sustainable Development Goals (SDGs). Each goal has specific targets to be achieved over the next 15 years and each target is measured by precisely defined indicators. The indicators are the backbone for monitoring progress towards sustainable development and they require high quality, efficient data to track progress and promote data-driven decision making by public and private organizations. However, collecting and analyzing data, particularly in emerging markets, is challenging, costly and the data often quickly becomes obsolete.

At the same time, mobile penetration is growing exponentially. According to the Mobile Economy Report by GSMA, half of the population of the world now has a mobile phone and an additional one billion subscribers are predicted by 2020, taking the global penetration rate to approximately 60%. The high geographic penetration, granularity and speed of the data enables telecom operators to systematically capture individual, social, economic and geographical data points across populations. Once aggregated, mobile data becomes a powerful data source which allows analysis on social interactions, population density, mobility, spending patterns, etc. The potential of these signals and data to address social needs and transform development and humanitarian actions is tremendous.

Not surprisingly, the use of mobile data for development is growing in importance to a wide range of development actors who can now use data to prioritize actions and measure their impact over time. Some of the use cases include understanding the needs of the low income populations, predicting and adequately managing epidemiologic outbreaks and food crises, as well as helping the most vulnerable communities to get access to finance.

Predict and prevent epidemiological spreads

Prediction and early prevention of transmissible diseases can be achieved with cell phone data. A research by Harvard Business School and seven other institutions combines cell phone data from 15 million people in Kenya with information on the regional incidence of malaria to show how human travel patterns contribute to the disease’s spread. Identifying the spread of infectious diseases using mobility patterns can help institutions and aid workers react quicker to the crisis by pointing out where to prioritize intervention. Then they can decide where to focus their resources and manage quarantine zones. They're also able to estimate import and export levels of the outbreak per region simply by visualizing mobility patterns based on cellphone data.

Manage food crisis

Mobile data can also be used as a proxy indicator for food insecurity. With the support of the World Food Program and UN Global Pulse, Real Impact Analytics researched means to effectively identify areas at risk of extreme hunger. Researchers at Real Impact Analytics found a high correlation between voucher purchase patterns and several food security variables (e.g. expenditure on food, vegetable consumption). The data can be aggregated to provide early warnings to governments and development organizations so that sudden changes in food security can be quickly remediated.

Improve access to finance

Ajay Banga, President and CEO of MasterCard labeled financial inclusion by 2020 “our generation’s equivalent of putting man on the moon.” Governments, NGOs and private companies are working on innovative solutions to reduce poverty and assure access to finance.

One example is the push for micro-credit and loans geared towards low income individuals in both rural and urban areas. These efforts often face important hurdles when it comes to scaling due to lack of information to build accurate risk models for low income individuals, especially in remote areas. To help lenders mitigate risk and reach more borrowers, First Access combines financial and mobile data to reliably predict credit risk for borrowers with the agreement of the borrower. The company combines demographic, geographic, financial and social data from mobile phones and other sources in real time. The approach has allowed millions of low income borrowers to gain access to financing, to improve their well-being.

There is a global momentum and consensus that leveraging data could possibly help address some of the SDGs. Once anonymized to protect privacy, data, tools and methodologies, they can reveal real-time trends on population behaviour and perceptions related to sustainable development issues. Such insights can guide the public sector to respond more effectively to emerging crises and vulnerabilities. For this to happen, we need to empower public-private collaboration to ensure that the data created by the individuals is used for their benefit and the benefit of society. Fortunately, many actors are tirelessly working on bringing these stakeholders together and making it happen.