Virtual Data Collection and Participatory M&E by María José De León and Chandani López Peralta

Hello! We are María José De León and Chandani López Peralta from TolaData, a digital platform for remote monitoring, evaluation and collaboration for the not-for-profit sector. I, Maria, am a Guatemala-based M&E expert with 13+ years of experience with INGOs, major donors and UN agencies. I, Chandani am a Berlin-based development professional with 10+ years of experience in international development.

As M&E specialists, we were accustomed to collecting data directly from the field, engaging and collaborating with local communities, beneficiaries and other stakeholders – this made M&E a participatory and systematic learning process for everyone involved. However, COVID-19 has shifted traditional data collection approaches to remote practices and increased our reliance on Information and Communication Technologies (ICTs).

Good news is, we can still sustain participatory M&E while working on virtual settings.

Just follow these hot tips:

  • Design M&E systems, tools and methodologies with the local counterparts: a participatory and inclusive approach to M&E increases the sense of ownership and motivation amongst everyone associated with the project. Moreover, staff members can gain clarity on what data collection tools/methodologies work best in certain settings and can accustom themselves to those early on. This helps to build their skills and capacity, improves programmatic performance and reduces the risk of rejection of ICT during data collection.

Tools for collaboration and training: Skype, Google Hangouts, Zoom, Mural

  • Bolster access to and use of ICT for data collection: COVID-19 has severely limited traditional data collection mechanisms, such as focus groups, interviews, direct observations, households surveys, etc. This has opened doors for development professionals to work closely with their local counterparts to leverage ICT and remote methodologies available and applicable in data collection locations. Even in areas with limited or no access to the internet, one can collect data via phone interviews, SMS forms or mobile data collection apps that can be used in offline settings.

Useful tools: ODK, KoBoToolbox, Magpi, CommCare, SurveyMonkey, RapidPro.

  • Leverage ICT for collaboration and reporting: Digital dashboards and collaboration platforms help local staff members, project teams, stakeholders and donors to easily collaborate and stay on top of project interventions while enabling staff to visualize and share results in real-time. Effective, timely and transparent communication within-and-across teams, opens up space for discussions of challenges, outcomes and the real needs on the ground; helps gather high-quality data; improves project performance; keeps staff safe in volatile situations, partners abreast of the changing operating environments, and enables decision-makers to meet the needs of the most vulnerable.

Useful tools: TolaData, DevResults, Granity, ActivityInfo

Using ICTs for data collection does not conflict with participatory M&E, in fact, it helps in making M&E possible, inclusive and effective in fragile contexts. Having said that, the role of local counterparts, communities and beneficiaries during M&E design and implementation is paramount and must be incorporated early on – without their support, explicit consent and approval of the tools chosen, the data collection process cannot be successful.

Rad Resources:

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

1 thought on “Virtual Data Collection and Participatory M&E by María José De León and Chandani López Peralta”

  1. michael sholinbeck

    Hi, thanks for this post. Other than ODK, which i am familiar with, which of the tools you list would be useful for collecting sensitive data? Thanks

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