EEP/Shiree: Using adaptive programming to monitor change in Bangladesh

written by Salimah Samji

How do you effectively monitor an 8 year, £83.5 million (around USD$135 million) challenge fund that partners with NGOs to improve the livelihood of 1 million beneficiaries? A daunting task indeed.

The Economic Empowerment of the Poorest (EEP/Shiree) program is a partnership between the UK Department for International Development (DFID), the Swiss Agency for Development and Cooperation (SDC) and the Government of Bangladesh (GoB), whose objective is to lift 1 million people out of extreme poverty by 2015. The fact that it is a challenge fund that has managing partners, consortium academic partners and NGO partners, all with many moving pieces, made it crucial to have agile decision making tools in order to respond to the needs of their beneficiaries in real-time. Traditional M&E methods of baseline, midterm and endline surveys were deemed insufficient.

The need for real-time measures and iterative decision making created the space for experimentation and innovation. Armed with authorization from their donors, the EEP/Shiree team set out to explore, experiment and create Change Monitoring System 2 (CMS 2). There are a total of 5 CMS tools which include in-depth life histories. They crawled the design space to find and fit solutions that would work in their context (pilot-test-adapt-iterate). Here is a summary of the three pilot phases:

  • Phase 1: Optical reader technology: They first created a simple survey for the NGOs partners to administer and fill out. The surveys were then digitally scanned. They quickly learned that this was too cumbersome a process and it took 2-3 weeks to receive the surveys. The time-lag was too long, they needed something more efficient.
  • Phase 2: Java enabled phone: Since mobile penetration is high, they partnered with mPower to develop a ten minute, monthly census survey on the phone. They equipped up to 20 field officers (the front line personnel who work at the field level with beneficiary households) with simple mobile phone devices that used the Bangla script for the survey. It was meant to be a 6 month pilot but it lasted for 1.5 years by which time they had scaled to 100 devices, with surveys and simple visualization. Convincing NGO partners as well as the visualization and the development of an in-house feedback loop mechanism took much longer than had been anticipated.
  • Phase 3: Android smart phone: The dropping costs of smart phones in the market (android phones were $60-70) created a lucrative option. The smart phone allowed greater flexibility (field staff just update the app on their phone), more functionality and accountability (GPS location of households, photos and voice recording verify that the beneficiaries are being met regularly). mPower also built a dashboard that allowed the comparison and served as a litmus test to identify red flags that required further investigation, ultimately allowing the NGO partners and EEP/Shiree to tailor recovery plans to the beneficiaries needs and changing context.
image of feedback loop

After the trial-and-error and incremental adjustments over three pilot phases, EEP/Shiree deployed a full roll out of the system towards the end of 2012 (3 years later) with the use of smart phones. EEP/Shiree project partners have over 700 smart phones equipped with an Android operating system, internet connectivity and GPS capability, and have been monitoring over 100,000 households every month across Bangladesh as well as accessing information through an online visualization dashboard that is updated in real time.

Here are some of the challenges they faced:

  • Bringing NGO partners on board: The NGO partners were reluctant and viewed the collection of data as an imposition from above. Asking, “why do we have to do it?” and saying “we don’t have time.” They did not understand that the data and the dashboard could serve as a management tool for themselves. NGO partners were then involved in the design of the questions and were included in the process. It took approximately eight months for data collection to cross the 100,000 per month mark which has since been consistently met and represents most households.
  • Infrastructure constraints: Accessing the dashboard from some areas still face connectivity issues. De jure, every field officer is supposed to visit once a month but de facto not all of them do. The sheer scale of the program makes it physically difficult to monitor. While changing the survey questions is easy – you just download the new form on your phone – the back end dashboard change costs are high. Furthermore, by changing questions you lose the ability to compare across time.
  • Effective use of existing data: While the data is used to respond to the needs of the beneficiaries, very little predictive/trend analysis is done. The data is not used to challenge assumptions of what works and to continuously refine their understanding of the dynamics of ascents out of and descents into extreme poverty. This is partly because no one is responsible for this task and so it doesn’t get done.

Complex problems do not have clear solutions. The fact that the donors were flexible and created the space for experimentation and innovation allowing several pilots to be tested (all with good reasoning) is commendable. Throughout the process, EEP/Shiree and mpower co-designed CMS 2 and their continuous cycle of partnership led to a virtuous cycle of action. The leadership on both sides meet every 2-3 months to discuss what is working and what is not, which helps adapt process to technology and technology to process. Together they built a dynamic monitoring tool, proving that this can be done at scale. This is a far cry from the usual case of consultant comes, builds an MIS system and then leaves.

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