Adapting Monitoring Systems During COVID-19 in Bangladesh
By March 2020, the COVID-19 pandemic had reached Bangladesh, and the offices of the Feed the Future Bangladesh Livestock Productivity for Improved Nutrition Activity had closed. Staff worked remotely, and in-person trainings, surveys, and monitoring visits halted. Instead, the Activity activated other ways of continuing its standard activities, including monitoring, evaluation, and learning (MEL).
Without MEL data, the Activity, which is funded by USAID and implemented by ACDI/VOCA, would be unable to learn and adapt, making it harder to serve its participants in southwestern Bangladesh. At the same time, government restrictions and health protocols could not be ignored. The MEL team was forced to weigh the risks and find creative solutions to safely move forward. While working from home, staff began communicating online using platforms such as Microsoft Teams and WhatsApp. For the MEL team, the crisis required a similar shift to the digital space and remote monitoring systems.
As these new monitoring systems became standard practice, defining the protocols for monitoring and collecting data became critical.
Below are five key methods the Activity used to continue its MEL efforts during the pandemic:
1. Moving toward Digital Data Validation
Prior to the pandemic, the team conducted its data validation using hardcopy documents, such as farmer registration forms. When COVID-19 became a reality, the team designed a plan for remote monitoring to comply with health protocols and USAID policies. They began using messaging applications, such as WhatsApp and Imo, to conduct virtual trainings and track documents received electronically. They then entered the data into ACDI/VOCA’s Learning, Evaluation, and Analysis Platform (LEAP), a streamlined system that simplifies the reporting process by standardizing project asset management and performance visualizations. Rather than validating the data against hardcopy documents, the MEL team validated it within LEAP, deleting all suspect data before reporting on it.
2. Holding Virtual and Hyperlocal Trainings
To avoid large group gatherings, the Activity held trainings online or at the hyperlocal level. The MEL team led orientations with local community agents and livestock service providers, especially those who already had smartphones, on Microsoft Teams, Google Meet, or Zoom. These community agents and livestock service providers then led their own virtual or small in-person trainings with a maximum number of participants allowed. They also cascaded the training to fodder entrepreneurs, who continued to share with farmers in their community. To verify participation in virtual trainings, facilitators took screenshots of those in attendance.
3. Recording Training Instructions
Along with trainings, the Activity also prepared community agents and livestock service providers to conduct project activities within their own villages to avoid violating travel restrictions. Each community agent and livestock service provider received recorded instructions from the MEL team as a reference for how to make decisions and maintain compliance across all the districts.
4. Collecting GPS Information
To cope with the changing COVID-19 situation, the team developed survey forms on digital platforms, such as Kobo Toolkit. Kobo Toolkit allows the user to conduct surveys offline, providing a critical workaround for those operating in remote villages with unreliable internet access.
Because the MEL team could not travel, they prepared livestock service providers and community agents to lead trainings and other activities. They then used GPS information gathered using a cost-effective Android application called Simple GPS Display to collect the trainers’ locations and verify and monitor the trainings.
5. Revising the MEL Plan
As the situation evolved, the team discussed with USAID the challenges surrounding the existing MEL plan, which relied on field-based verification and data quality assessments. Because of the travel restrictions, the Activity updated its MEL plan to incorporate digital aspects and to reduce some targets for activities that were difficult to organize during the pandemic, such as livestock fairs. As part of this review, the Activity also updated its data management manual and process for calculating indicators. Using Microsoft Power BI dashboards, the MEL team was able to reflect on the data in real time and submit a revised plan to USAID.
Maintaining the quality of data collected is challenging for many development programs during the pandemic. For the Livestock and Nutrition Activity, the shift to a completely digital monitoring system over the last year has resulted in lower costs, contrary to the popular opinion that going digital is expensive. A downside of remote monitoring is that it is challenging to report unplanned outcomes or indirect impact without being in the environment to detect them. However, these systems have the potential to help programs forgo disruptions and continue MEL efforts safely, especially among critical groups, such as those most negatively affected by the pandemic.