Top 10 Takeaways from M&E Tech Conference

The introduction of new technologies in the monitoring and evaluation (M&E) field is upending long-standing methodologies for collecting data and engaging with communities. The M&E Tech Conference, held in Washington, DC September 25-26 and sponsored by The Rockefeller Foundation, GSMA, and FHI 360, addressed a number of issues to break down the gap between technology hype and implementing realities. The top 10 highlights from the opening session follows.

1. Information and communication technologies (ICT) are helping to increase the speed of data collection, but have not yet increased the speed of analysis. The world of “big data” is still overwhelming, and many questions remain regarding data reliability.
2. Over 70 percent of international nongovernmental organizations (NGOs) are using mobile technology in their work, and just over 50 percent are integrating ICTs into M&E specifically.
3. While many new ICTs are being tested, the efforts have been piecemeal. No one has institutionalized ICTs in M&E at the operational level; rather, efforts tend to be carried out ad hoc.
4. ICTs have allowed us to reach a greater number and wider diversity of people than ever before, but the cost is not always cheaper.
5. Widespread agreement was voiced that a paradigm shift is needed to separate approaches to “M” (monitoring) from approaches to “E” (evaluation). Perhaps if we did more and higher quality monitoring, there would be less need for evaluations.
6. The intersection between technology and M&E needs leadership and donor funding to test what technologies are working and which ones aren’t.
7. ICTs have not made significant progress toward tightening feedback loops.
8. The issue of privacy in data collection and analysis needs to be taken seriously in developing countries. Everyone has a right to privacy. 
9. To avoid fad fatigue, staff members need evidence of what technologies are working well before they buy in to a new way of doing their work. 
10. Many of the same rules still apply: Data collection needs to be coordinated to avoid duplication of efforts; more information should be shared among partners; and results need to be made accessible and understandable to those who contribute.