Big data, big deal?
28 September 2017
Benefits and challenges associated with Big Data for results measurements
In our last blog, we explored the use of big data for monitoring and evaluation (M&E) purposes in international development. We concluded that big data can provide us with great insights into aid effectiveness; it can show whether development projects have been successful and facilitate a more adaptive process toward designing programmes that deliver better outcomes for disadvantaged people. However, current projects are still in the pilot phase and much still remains to mainstream the use of these techniques. With this blog we would like to build on our first blog by exploring the potential benefits and practical challenges associated with applying big data.
Benefits of big data:
However, there are challenges of big data:
Big data can provide added value, if used correctly. In projects where there is a large amount of unstructured data, or where there are few privacy concerns big data can offer huge insights. This was also one of the conclusions in the annual UKES evaluation: “Data linkage, the availability of big data, and the options remote sensing provides are increasing the number of questions we can answer. Data visualisation opens up doors to better understanding and communication of data”. However, big data probably has less to offer to projects that are targeted towards communities with no access to internet. Whether the opportunities outweigh the challenges will therefore need to be assessed on a case by case basis taking these contextual factors into account.
How we apply big data in M&E will also be different in each sector. Satellite imagery, for instance, is more applicable in agricultural projects than in gender-related projects. For gender-related projects social media monitoring can be more useful. For example, it can be used to determine the effects of women’s economic empowerment campaigns. It is possible to analyse the extent to which people within a geographic location are positively or negatively associated with a certain topic on social media. By analysing changes in these associations, it becomes possible to draw conclusions on the success of the campaign.
If we look at scale of benefits and challenges of this specific case, we see the benefits outweighing the challenges. The social media data is readily available and close to real time. Specific tools are available that are able to analyse these large amounts of unstructured data. As a result, the specific expertise needed for analysis is limited and so are the ethical challenges; people choose to share information on social media. Methodological challenges are still present as not all people use social media and therefore results might be skewed. These challenges should therefore be taken into account when interpreting the results.
Ultimately big data has the potential to show whether development projects have been successful and facilitate a more adaptive process toward designing programmes that deliver better outcomes for poor people. As sectors provide an interesting lens to look at big data, we’ll explore this more detail in our next blog.
This blog is the second of a “digital in development” collaboration series between PwC Kenya, PwC Netherlands and PwC UK.