Promiscuous data: Experiments with research in Nigeria and Nepal

K. P. Greiner
Differences that make a difference
5 min readAug 17, 2017

With contributions from Equal Access colleagues: Prabin Shrestha (Nepal) Fatima Ibrahim (Nigeria)

From Merriam-Webster dictionary

We’ll admit it — we were hoping “promiscuous” would get your attention. And it IS an accurate word for what we want to describe, which is a use of data that doesn’t discriminate, that is not restricted to one class of use, or audience.

In the field of international development, we use data from program implementation and evaluations in reports for our financial supporters, for practitioner peers, and for the general public. In this essay, we want to briefly describe a few different uses for data that go beyond program evaluations and reports. Some of these uses are well-known and established, others are less frequently practiced in international development, and thus ripe for discussion and experimentation.

At Equal Access International we developed the “RAAM” model (below) to use with our field teams to experiment with how we can get more mileage out of the data we collect as we implement a range of communication for social change interventions across the globe. We are currently seeking to strengthen our use of data beyond reporting, by experimenting with new ways to use data for Action, for Advocacy, and for Motivation.

To be clear, the model does not suggest an “either/or” scenario,” with data fitting neatly into only ONE of these categories. The model (a simple typology, really) is guided by the belief that data can and should be used in multiple ways: to reach those who need it to make decisions, to support those seeking to improve programs, and to motivate those who helped generate the data, either as data collectors or research respondents.

The next three examples from our work in Nigeria and Nepal illustrate different ways to use and experiment with data.

Data for action: The case of Arewa24

Arewa24, the 24-hour Hausa language satellite radio station in Northern Nigeria, had a challenge hidden within a huge success. Of the millions of viewers watching Arewa24 programs (either by broadcast satellite, YouTube or through a mobile phone app), hundreds of thousands were calling the interactive voice responses (IVR) mobile phone system to respond to opinion polls and record open-ended feedback. From the very beginning it was noted that many callers had a hard-time understanding the system, as thus the hang-up rate was quite high. The in-country research team used IVR data for action to design two small solutions to the hang-up problem: 1) An on-air promotion of the system, using drama and two charismatic actors to model how the system functions; and 2) using fewer and more-simply worded questions. The result was a tripling of the number of viewers who called the IVR system and did not hang up. The weekly average of callers who stayed in the system to respond to polls or give open-ended feedback jumped from 6,500 to 19,000. The Nigeria team used data for action, improving the measurement process itself and increasing the number of viewers sharing their perspectives, which helped continually improve our broadcasts.

Arewa24 data report, Interactive Voice Response (IVR), March-May, 2017

Data for advocacy: “SMS my voice” in Nepal

Listeners in Nepal who follow Equal Access radio programs on good governance and civic participation are invited to text questions for their local elected officials to the “SMS My Voice.” A compilation of the comments and queries is compiled into a booklet that is shared with officials and other key decision makers. Interviews are then conducted with the concerned authorities and their responses are broadcasted through the radio program. SMS My Voice data is also shared digitally with local citizen-journalists who can share and discuss listeners’ ideas and questions with additional audiences.

When radio programs feature local leaders, the voices of the powerful are carried to citizens. SMS My Voice makes it possible for citizens to respond to their elected leaders, airing their concerns and questions, which increases the accountability of those leaders. In the design of the civic participation aspect of our communication for social change intervention, we were inspired by MyVoice in Nigeria and UNICEF’s U-report, which are similar services for amplifying citizen voices.

Data for motivation: “Visibilizing” community engagement in Nepal

Stanford professor BJ Fogg has a helpful model describing how human behavior can change if the right conditions are present; a combination of ability and motivation, with a “trigger” to spark action. The emerging strategy of “gamification” offers additional helpful insights on motivation, including the idea that “extrinsic” rewards, like money or prizes, are less effective and less sustainable than incentives like praise, recognition, and making progress visible. Video game designers understand this well, and have mastered the art of motivating through points, badges and levels.

In Nepal, we are using data from our interactive voice response (IVR) system to make visible the number of radio listeners who engage with Equal Access programs. Our field team uses simple maps and graphics to share IVR caller data back at the district level (from whence it came). We have just trained a group of community-based facilitators who will be using the data maps during conversations with radio listeners and community leaders in the districts where we broadcast.

Showcasing the top districts in Nepal (Most engagement with interactive Voice Response/IVR system)

We envision complementing the maps with other forms of recognition, like certificates for our facilitators who are able to increase the levels of civic participation in their district.

Data for reporting will always be required for those working on externally-funded programs. Data for action is the backbone of a good monitoring system. Data for advocacy and data for motivation often get less attention in the field of international development. By sharing this typology of data use, the RAAM model, and some illustrative examples, we are hoping that other organizations and individuals may decide to also share promising practices in their use of data.

Thanks for taking the time to read this essay — We welcome your comments and questions.

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K. P. Greiner
Differences that make a difference

Passionate about human rights and social change. More writing at www.kpgreiner.com. Social and Behaviour Change Team, @UNICEF Dakar, Senegal