In the 21st century, the use of data fundamentally transforms the way we communicate, do business and make decisions. The use of data fundamentally transforms the way we communicate, do business and make decisions. The transition from the millennium development goals (MDGs) to the sustainable development goals (SDGs) poses new challenges in the realm of data for development and drives a massive demand for high quality data.
There is a pressing need for data on specific topics, such as water quality, and in general for data and evidence to enable better monitoring and evaluation of development results. This data is needed to increase accountability, effectiveness and efficiency. Governments and supporting organisations will be required to generate unprecedented amounts of high quality data in order to monitor and report on progress in implementing the SDGs. It is crucial that this data is collected using consistent methodologies and, when possible, is openly available to all stakeholders. A key consideration is that some data may be sensitive and cannot be shared in a raw format.
Data collection for the development sector
In the development sector, a large part of data is collected by people going into the field to perform surveys and conducting other measurements, such as water quality. The Handbook focuses on these data collection projects, providing guidance on the journey from data to decision according to five stages: prepare – design – capture – understand & share – act. The guide describes how to design such projects; how to implement the data collection process; how to combine the collected data with other data sources; how to analyse the data to gain insights and make informed decisions; and how to make the data openly available.
The importance of a good set-up
Too often data is collected using inconsistent methodologies which leads to data that is not useable and/or comparable. Sometimes, additional data is collected just because there is the opportunity to do so, which leads to data-fatigue, both in the collecting organisations who see no concrete results from their large efforts and the people from which the data is collected who see no tangible results from the large amount of data they have given. Lastly, data is often not shared, causing other organisations to collect the same data instead of building on existing data. Data is only useful if the quality is high and collected with a specific goal in mind.
Handbook on Data Collection
The AfriAlliance Handbook on Data Collection provides guidance on how to best develop a data collection project to ensure high quality data is collected and maximum impact is achieved. Focusing on the development sector and the collection of data, the Handbook covers the main elements to consider when designing and implementing a data collection project. Where applicable, it will also point you to more detailed resources.
The Handbook provides guidance for projects to:
- Focus on achieving impact.
- Only collect the data that is needed to achieve that impact.
- Build on existing data.
- Use the most efficient method of data collection.
- Make sure data benefits the communities it is collected from.
- Share data whenever possible to ensure others do not have to do the same work.
The main authors of this handbook work with governments and non-governmental organisations that strive for equal access to public services, reliable infrastructure and a safer environment. Good data is critical for effective decision making, collaboration, and accountability. Akvo provides partners with the data platform to help them capture, clean, visualise and share data. That data platform is supported by a series of services to build local expertise and ensure success from data to decision. With five regional hubs in five continents, Akvo has supported over 20 governments and 200 organisations in more than 70 countries and is consortium partner in both the Groundtruth 2.0 and AfriAlliance programme. More information can be found at www.akvo.org.
This blog was written by Marten is Akvo’s services manager, based in Amsterdam. You can follow him on Twitter @mato74.