On May 15-18, 2017, QED participated in the 9th Annual ICT4D Conference in Hyderabad, India. Project Analysts Sandeep Yadav and Purnima Mehta, of QED’s Monitoring, Evaluation, and Learning (MEL) team, were attendees and presenters at the conference.
The topic of their presentation was “Benefits and Pitfalls to Integrating Technology into M&E Activities,” focusing on the use of emerging technologies such as mobile data collection, remote monitoring, drones, virtual reality, and augmented reality. A special emphasis was placed on the limitations of technology and addressing concerns such as security, data privacy, regulatory constraints, as well as selectivity bias. Sandeep and Purnima also discussed the USAID/Afghanistan Monitoring Support Project-East (MSP-E) as a prime example of how the project demonstrates QED’s endeavor to integrate technology into its data collection, organization, and data visualization efforts.
The presentation included an engaging group discussion activity, which the audience participated in eagerly. The activity encouraged audience members to share their expertise and experiences and to also suggest technological solutions to a hypothetical monitoring scenario. The result of the group discussion activity led to many interesting ideas regarding how technology can be used to enhance M&E activities. Interestingly, a few of these ideas, such as tablets and GPS tracking, are already being deployed by QED in its fieldwork.
With a theme on the use of information and communications technology for achieving sustainable development goals, the conference brought together companies and non-profit organizations from across the world who presented insights from their works in health, agriculture, disaster management, education, and financial inclusion, among other development sectors. Insights included geographic data, inter-institutional collaboration, overcoming cultural barriers, and fostering an ethos of innovation and data-driven decision making. The concluding panel of speakers stressed the importance of good analysis and best-fit approaches, which might often be neglected at the expense of intensive efforts to collect as much data as possible.