Stephen Kalungu is the Country Director at GiveDirectly’s Kenya office. GiveDirectly disburses cash grants to poor and vulnerable households around the world. The non-profit organization has pioneered using cash as aid and has contributed to the growing use of cash grants by aid organizations and governments.
With his prior experience as a field manager, he has interacted with grant recipients — gaining first-hand insights into their needs and challenges. Additionally, having managed processes from the Kenya office, Stephen has a comprehensive understanding of the entire disbursement process, which enables him to consider multiple viewpoints when addressing the complexities involved in assisting those in need.
In this interview, we chatted with Stephen about the challenges of scaling aid programs, how to target beneficiaries, and how some processes that sound simple in theory can be challenging to implement.
Challenges of scaling aid programs
Stephen explained that GiveDirectly has funds that can be used for any purpose and funds that the donor restricts for a specific use. Although GiveDirectly only gives unconditional cash transfers, there are elements of their program that can be tailored to suit some particular project need or funder’s outcomes of interest. Stephen explained:
“As we talk about scale, there is always the question about the who-why-where. When I speak about what, I am speaking about which project, and for that project, who are going to be the target beneficiaries and who are going to be the funders.”
Much of the project tailoring is motivated by research. Examples include
- Testing the impact of digital nudges on beneficiary spending choices.
- Testing the impact of different transfer models (such as. lump sum versus monthly payments) on household food security and learning outcomes.
- Testing how transfers complement other non-profit and government-led programs (such as the take-up of the National Health Insurance Fund (NHIF) cover).
Besides funding, another challenge for scaling is infrastructure. GiveDirectly delivers cash transfers using digital payments, such as mobile money transfers. Some regions don’t yet have the financial infrastructure for beneficiaries to receive digital payments and spend their transfers. Although, Stephen pointed out that:
“The good news from what we have seen is that… cash is able to trigger the infrastructure and market development by itself!”
Simple in theory but challenging in practice
Stephen highlighted how programs that seem simple when designed in the head office may be impossible to implement in the field.
“It’s very easy for you to sit in the office and you think of a process that you think is very simple, but when it is implemented on the ground you find that it’s almost impossible to be able to do it.”
Stephen highlighted an example of implementing a financial planning exercise in which beneficiaries were required to write down their savings plan. Due to low literacy levels, the field officer often had to write down the plan on behalf of the beneficiary. The field officer’s involvement in writing down the plan risked diluting the beneficiaries’ ownership and potentially undermining the intended outcome.
GiveDirectly encourages a recipient-first model of program delivery. The program should be adapted to suit the target beneficiaries. The head office and field teams work closely together to ensure the program can be implemented effectively.
Targeting beneficiaries
Poverty is widespread in rural areas where GiveDirectly works, and around 80% of households are eligible for aid. Instead of attempting to exclude the 20% of households above the poverty line, GiveDirectly provides transfers to all households. For GiveDirectly, the risk of making an error and excluding a household that needs aid outweighs the cost of giving transfers to all households. Additionally, GiveDirectly’s research partners found that excluding some households has other costs, such as reducing the subjective well-being of the excluded households. [1]
In urban areas, populations show greater diversity, and GiveDirectly does not have the budget to give transfers to all households. GiveDirectly works with partner organizations to assist with identifying the beneficiaries who are most in need.
Current challenges
Our interview concluded with Stephen highlighting two challenges that our community of researchers could work on: designing scalable methods for targeting beneficiaries in areas that are too dangerous to visit in person and designing machine learning solutions to translate local languages for phone calls between beneficiaries and GiveDirectly’s call center.
Many of the poorest regions in the world are in active war zones and are too dangerous for GiveDirectly field officers to visit. GiveDirectly needs methods that can be implemented remotely to target beneficiaries in these areas. One solution that shows promise is using mobile phone metadata to target aid. GiveDirectly has partnered with researchers to test this method in Togo during the COVID-19 pandemic. [2]
GiveDirectly’s call center handles a large amount of communication between GiveDirectly and beneficiaries. The call center receives calls in an array of different languages and local dialects. To manage communication more efficiently, the call center may benefit from live translation to enable GiveDirectly representatives to communicate with beneficiaries even if they do not speak the same language.
The interview with Stephen Kalungu was led and summarised by Matthew Olckers.
[1] Graff, Tilman, Johannes Haushofer, James Reisinger, and Jeremy Shapiro. “Psychological Well-Being Is Much More Strongly Related to Income Than to Inequality.” Working Paper (2019). An earlier version circulated as “Is Your Gain My Pain? Effects of Relative Income and Inequality on Psychological Well-being” is available here.
[2] Aiken, Emily, Suzanne Bellue, Dean Karlan, Chris Udry, and Joshua E. Blumenstock. “Machine Learning and Phone Data Can Improve Targeting of Humanitarian Aid.” Nature 603, no. 7903 (2022): 864–870. Link: https://www.nature.com/articles/s41586-022-04484-9
