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From better data to development solutions: Capacity building in the Democratic Republic of Congo

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mission in DRC, Democratic Republic of Congo
Photo: Valeriya Anufriyeva/Shutterstock

The Statistics for Results Facility (SRF), a multi-donor trust fund, worked with countries to improve the production, availability, and use of data for evidence-based decision making. Its holistic, system-wide approach to tackling data challenges from different entry points produced a number of concrete and sustainable results in countries, leading to better coordination and new waves of technical and financial support for better data and lasting impact. SRF supported 8 countries and one region-wide project in Africa: Afghanistan, Democratic Republic of Congo, Ethiopia, Ghana, Lao PDR, Nigeria, Rwanda, and Senegal.

Today we’re highlighting a project from the Democratic Republic of the Congo (DRC), which aimed to strengthen the capacity of the National Institute of Statistics (INS) to both generate and disseminate robust data.

With an estimated population of 84 million people in 2018, DRC enjoys a wide variety of natural resources like minerals and fresh water. Unfortunately, the country has suffered from a series of violent conflicts and remains one of the poorest countries in the world. In this environment, the national statistical system of the DRC had long suffered from deficiencies in human resources, institutional capacity and statistical information (the most recent population census being for 1984), and governance mechanisms for the National Statistical Systems and the INS were incomplete when the project started. Ready to help the DRC change this narrative, SRF disbursed nearly $12 million USD and catalyzed substantial results.

Three components comprised the overall strategy: human capital, physical resources, and data production. First, SRF aimed to instill INS workers with new knowledge, offering them the opportunity to study for a degree in statistics, computer science, or demography. The World Bank recognizes that human capital is a key feature in every country’s development: it is our world’s most precious—and often most overlooked—resource. Furthering statistical workers’ education not only improves the quality of the data they collect, analyze, and disseminate, but also provides a more well-rounded approach to the entire statistical process. Thanks to a grant from the Facility, 23 young Congolese pursued formal degrees from one of the top institutions like the Institute of Statistics and Applied Economics in Abidjan, Ivory Coast. Among them, 15 completed the Bachelors’ program and are applying their new skills at INS, while the rest are continuing education to become Statistics Engineers. SRF also supported on-the-job training for statistical skills such as SPSS, STATA, and R for 284 existing INS staff members.

Video: SRF work in the DRC [French]

Another contributing factor to INS capacity is their physical resources. Upon arrival, SRF assessed that the pre-existing INS facilities were unsupportive of a modern work environment that requires advanced technology. Demolition and reconstruction efforts established a six-floor office building complete with IT connection, training rooms, and a dedicated library and archive to enable more efficient work environment and user-friendly data dissemination. SRF also helped the INS develop its own website in line with best practice data archive and dissemination policies.

With human capital and physical resources in place, SRF also supported data collection activities and the data management process. For example, SRF supported the preparatory stages of the population and housing census, including the pilot census cartography, development of its methodology, training and deployment of field teams, and the pilot report. This support was particularly relevant for the DRC, which had not delivered a census in 30 years. The project also supported preparation for the enterprise census, training roughly 1700 enumerators and supervisors.

Inspired by SRF's progress, other partners joined forces to continue the support in DRC. This is the true heart of SRF: its catalytic effect. The population and housing census will continue to receive support from the United Nations Population Fund, and an IDA-funded project continues to assist the DRC’s enterprise census, illustrating the gains that can be made when the development partners collaborate to support capacity building.

During implementation, the project experienced several setbacks mainly due to the fragile security and political situation and low capacity for the project implementation, which caused delays in realizing program objectives. The INS and the SRF team continued to progress despite challenges by assessing the situation and adjusting the approaches as necessary. Country commitment, realistic expectation setting, careful planning for the sequence of the project, flexibility in implementation, and patience were some of the key lessons learned from this project and can be applied to other projects in the country and region as well.

The Statistics for Results Facility recognizes that data scarcity and lack of statistical capacity around the world does not have a silver bullet solution; rather, each country requires customized new approaches to build capacity, provide trainings and infrastructure, and most importantly instill confidence that better data can unlock sustainable development solutions. By tailoring specific strategies to reach unique country goals, SRF ensures that clients can achieve concrete outcomes, step by step. However, a particularly fragile country like the DRC will need continued investments over time to sustainably transform their statistical capacity. Now that the Statistics for Results Facility has closed, its catalytic effect is more important than ever to galvanize new waves of support to continue this vital work.

The Statistics for Results Facility (SRF) is supported by the United Kingdom’s Department for International Development and the Government of the Netherlands.


Masako Hiraga

Senior Statistician/Economist, Development Data Group, World Bank

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