Data CollectionMillions of people across the world suffer from extremely impoverished living conditions and nations and organizations around the world have committed to greatly reducing this number by 2030. Surprisingly, data collection has and will continue to play a crucial role in this process.

In the last few decades, the world has experienced a significant decline in the portion of the global population that may be considered extremely poor. But how do we know this? Data collection is extremely important in determining a baseline for poverty as well as measuring successes in measures to eradicate it.

Data collection has taken several forms throughout the years, becoming more accurate and streamlined. However, there is still room for improvement in streamlining efforts, which takes human power, technology investments and funding. In short: without data collection, ambitious efforts toward ending global poverty may drag on or stall altogether.

Surveys are a primary means of data collection. Statistical groups see this as the best measure of current lifestyle conditions of those living in poverty. These types of surveys can measure levels of income, familial distribution, education, employment, gender ratios, birth rates and death rates across a large representative portion of any country’s population.

The coverage and frequency of these surveys has increased over time, making measurements that much more precise. However, this data still remains largely incomplete in many areas due to migration, refugee situations, and minimal access simply due to the level of danger.

Innovations in technology are helping to close inherent gaps in survey systems when it comes to data collection on poverty. Automating surveys make the collection even more accurate and organized as well as can become more widespread, reaching the once-unreachable. Cell phones and computers with Internet capabilities have carved out a new path for data collection, as they are accessible to most extremely poor countries. These technologies are also more fiscally responsible for the distributors in the long run.

Data collection is extremely important in continuing the battle against extreme poverty, to help better understand the problem at hand: what may be working, what is not, and what corrections will potentially make a huge impact.

Casey Hess

Photo: Flickr

Global gender data gapThe Bill and Melinda Gates Foundation announced in May that it will donate $80 million to reduce the global gender data gap. This donation will contribute to meeting the United Nations Sustainable Development Goals by 2030. Current data collection standards do not adequately record women’s economic and social information in developing countries.

According to a press release by the organization, “a lack of comprehensive, current information about women and girls, especially in developing countries, hinders efforts to advance gender equality.” In order to achieve the health, educational and social proposals of the United Nations Sustainable Development Goals, world entities need access to accurate information about women everywhere. Closing the global gender data gap would provide that information.

The New York Times reports that standards for collecting data are gender-biased. These standards also fail to account for the complexity of women’s global situations. For example, many traditional surveys do not count female-led households in the same way as male-led households. They do not fairly count women who are homemakers or caretakers. Surveyors might end an interview after documenting “homemaker” as a woman’s primary activity, even if she has other economic occupations.

According to the same New York Times article, surveyors only collect about 30 percent of women’s economic activity. On the other hand, surveyors collect 75 percent of men’s activity. Statistics like this compelled the Bill and Melinda Gates Foundation to improve data collection methods. Entities such as the United Nations Foundation and the U. S. Department of State have also joined them.

The funding will support the creation of effective training techniques and improved tools for people who work with data. Tools like the Population Council’s Girl Roster Toolkit can provide those who collect and analyze data with holistic perspectives about issues girls suffer from globally and how they must properly document them. The Girl Roster also connects the world’s neediest young women with services in their areas.

In order to keep governments and politicians accountable to use the new and improved data, organizations like Avenir Health’s Track20 will help governments connect with women worldwide in order to give women access to family planning services.

The good news is that data gaps are already closing for women. According to the New York Times, the number of mothers dying during childbirth has dropped more than 40 percent worldwide. Similar statistics show much progress, but others show the need for more work to completely close the global gender data gap.

With the help of sponsors like the Bill and Melinda Gates Foundation and the work of data analysts and cooperative governments, the world can continue to give women everywhere the chances they need to live whole and happy lives.

Addie Pazzynski

Photo: Flickr

Monitoring Global Poverty

While taking action is an important part of fighting global poverty, it is also critical that international organizations correctly assess the situation through different methods of data collection and analysis. Monitoring global poverty is crucial for ending it.

Since the World Bank’s first census in 1975, attempts to monitor global poverty levels have widened in both scope and methodology. The invention of PovcalNet in the 1980s enabled researchers to access the poverty distributions of 191 countries online. However, the diversification of research methods entailed as much inconsistency as convenience, as data collected by different teams seemed to suggest entirely different results.

Since one organization cannot survey all the households of the world, analysts often collect survey results from the governments of different countries. This introduces inconsistencies into investigation methods, including differing methods of selecting and interviewing sample populations.

When measuring qualitative measures such as household participation, patterns of consumption and perception towards poverty, long-term participatory observation can be more appropriate than surveys, as the wording of questions can manipulate the results.

After data is collected, it is classified and represented into charts or graphs, where more complications can occur. There exist many statistical methodologies, including parametric, non-parametric and lognormal, and countries differ on how to define poverty in various environments.

To standardize data collection and facilitate monitoring global poverty, the World Bank has been urging nations to adopt the National Strategies for the Development of Statistics (NSDS), emphasized at the Marrakech Action Plan for Statistics in 2004.

NSDS requires not only economic support, but political cohesion between departments and local communities in each country. The NSDS Knowledge Base will compile research techniques and provide 100 indicators to the progress of Sustainable Development Goals so that results from different countries can be comparable.

Difficulties of standardization often derive from insufficient infrastructure, such as the failure to register all citizens on census, and requires a long-term investment. In such cases, innovative measures can improve cost-benefit efficiency.

The UN’s Data for Development report from 2015 suggests using satellite imagery and mobile-phone-based data collection. Instead of designing a separate survey, data from social media and mobile call traffic can be repurposed as an indirect indicator. In East Africa, for example, mobile technology is expected to cut up to 60 percent of the cost of traditional paper surveys.

Haena Chu

Photo: Flickr

Rwandan agriculture

Of the many tragic legacies that the civil war in Rwanda have had for the country, the effect of the conflict on Rwandan agriculture has developed in unexpected ways. A report from showed that during the civil war, historical climate data were significantly compromised. As a result, farmers have faced increased risk of crop failures due to droughts, flooding, and other damaging weather patterns.

The Rwanda Climate Services for Agriculture project aims to bolster Rwandan agriculture by filling in gaps in Rwanda’s climate data records and disseminating meteorological data to farmers, according to a report from the Research Program on Climate Change, Agriculture, and Food Security (CCAFS).

The report goes on to explain that this project will expand upon elements of the Enhancing National Climate Services (ENACTS) approach, which is already being implemented in eight African countries. ENACTS connects satellite data with on-the-ground station observation from Rwanda’s National Meteorological Agency (Meteo-Rwanda), and provides to farmers the information gathered therefrom via “maprooms.” These maprooms are publicly accessible websites providing dynamically updated information on weather patterns such as temperature and rainfall, according to the Meteo-Rwanda website.

Furthermore, the project builds upon the Participatory Integrated Climate Services (PICSA) approach, which entails integrating NGOs and agricultural extension staff with local farming communities. With easy access to climate data, Meteo-Rwanda’s maprooms will expedite this process by giving intermediaries more accurate and timely information about the ares where they will need to function.

According to the CCAFS, the project aims to provide climate data to one million farmers.

Given the importance of Rwandan agriculture in the local economy, this project represents an important step forward in repairing the damage of the civil war. According to, agriculture accounts for one third of Rwanda’s GDP, and eight out of 10 Rwandans are employed in agriculture. Thus, softening the impact of flooding and drought will provide significant economic benefits the country.

Peter Della-Rocca

Photo: Flickr

data_standardsSetting higher standards for data reporting and compatibility is essential to track and foster progress in initiatives all over the world. That’s why two networks, Development Initiatives and Publish What You Find, are heading a project to develop more universally applicable data standards and help organizations and projects transform their data to match the new standard.

Improving data standards for organizations, particularly those administering aid in countries abroad, will help elucidate the work being done and facilitate collaboration and communication between groups in different sectors. These standards also allow for interoperability, which is defined as the ability for technology and software systems to communicate, exchange data and use this data for researchers to draw conclusions about projects.

Needless to say, higher standards for information will improve the efficiency and speed with which organizations analyze and improve their efforts and also allow them to share their efforts with other groups who can replicate them. Doing so will not only improve the way information it is collected but it will also make it more widely available — improving access to and understanding of the latest projects organizations all over the world that they are engaging in.

In investments directly related to foreign aid, such as those in healthcare, education, agriculture and water access, higher data standards will allow organizations to share the outcomes of their projects with donors who can track the flow of their funding. They can also publicize their findings with other organizations that can then compare and collaborate to find more efficient, cost-effective solutions.

Something as seemingly small as transforming and improving the way with which organizations report their statistics can make drastic improvements to people’s health and way of life all over the world. Examples of this are logging administration and efficacy of immunizations, schools or communities with the highest risks, spread of disease and robustness of food resources. Interoperability allows organizations and donors to link up and improve the work they are doing.

Development Initiatives and Publish What You Find hope their data allows people to make more efficient use of data, whether by directing the flow of funding or improving aid projects. Efforts like these will improve access to information on development flows and therefore their efficiency. This project is ambitious in its design of overhauling sector-level systems, but the change it will bring about will be much broad, influencing the lives of people all over the world.

Jenny Wheeler

Sources: Omidyar, Devinit
Photo: University of Mary Washington


Data collection is essential to address public health concerns in the developing world. If a nonprofit or government institution cannot identify risk factors, outbreaks, health trends and vulnerable populations, aid cannot be targeted effectively at the people who need it the most. As Margaret Chan, director-general of the World Health Organization puts it, “without these data, countries and their development partners are working in the dark – throwing money into a black hole.”

That is why the World Bank, the U.S. Agency for International Development (USAID) and the World Health Organization (WHO) recently announced the Roadmap for Health Measurement and Accountability and a Five-Point Call to Action. These initiatives are meant to encourage the governments of developing countries to strengthen their public health registration systems, with the goal of making health aid more effective while avoiding some of the data-collection pitfalls of the past.

While previous data-collection initiatives, many motivated by the Millennium Development Goals, led to dramatic improvements in public health knowledge gaps, they also had some negative consequences. These were mainly a result of the programs’ tendencies to fragment as well as detract from country-led approaches to data collection.

Jimmy Kolker, assistant secretary for global health in the U.S. Department of Health and Human Services, points out that data collection should not be an “end in itself.” To be effective, governments need to have the political capacity to support, and act on, the data that they collect. In contrast to previous initiatives, the Roadmap and Call to Action are intended to empower countries to develop their own integrated health systems, which should be more sustainable and robust in the long-term.

The Five-Point Call to Action includes some very specific public health monitoring goals. For example, the third point emphasizes a need for adequate civil registration systems, with the goal of registering all births by 2030, as well as registering 80% of deaths and their causes. The reasoning behind being so specific in establishing broad standards is that in the past, data collection efforts were hampered by a lack of coordination; a poor focus on specific health issues also failed to reveal broad trends and strengthen public health systems. Thus, these initiatives emphasize establishing accurate measurements of a few basic indicators, such as births and deaths, as well as having basic reporting and public access mechanisms in place.

The Call to Action calls for adequate data collection and interpretation through modern technology, not just traditional registration systems. Point four emphasizes that by 2020 all countries should have “real-time disease surveillance systems in place, including the capacity to analyze and link data using interoperable, interconnected electronic reporting systems within the country.”

As technology has developed, aid agencies and governments have an ever-growing list of resources that can help them monitor, collect, and interpret health-related data. Up to two-thirds of the world’s population in 100 countries is absent from public registration systems, a gap that must be filled by modern data-gathering and reporting solutions. Mobile technology is an enormous boon to governments trying to build data collection and dissemination systems.

For example, since 2008 Bangladesh, with relatively little funding and prior to the aforementioned initiatives, has managed to strengthen programs for establishing electronic medical records, centralized databases, accessible online resources for data-entry and reporting, and citizen feedback mechanisms. Bangladesh is a great example of how a low-income country can rapidly modernize its public health data resources cheaply and efficiently, a model from which other developing countries might learn, spurred on by the recent initiatives by USAID, the WHO, and the World Bank. Perhaps, with some financial and technical support from these institutions, developing nations can create their own path toward improved public health.

Derek Marion

Sources: MA4Health, World Bank, Devex
Photo: Leaning Forward