MERL Tech DC 2018 has ended
Back To Schedule
Friday, September 7 • 9:30am - 10:30am
Hard Talk: Will Technology and Big Data Replace Monitoring Evaluation, Research and Learning?

Log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
The most challenging aspects of purposeful Monitoring, Evaluation, Research and Learning (MERL) are most often: 1.) selecting informative metrics and 2.) performing MERL efficiently. Many individuals in MERL assume that technology and big data will dramatically improve both the selection of informative metrics and MERL efficiency. However, as a community, we also understand that existing structural constraints in the MERL ecosystem may either hinder or render ineffective technology-enabled tools. In addition, the biases present in large data sets may mean that metrics selected using machine learning are no more informative than those already in use and that MERL will ultimately be ineffective at improving institutional performance. In this interactive panel, we will discuss the existing structural barriers to the successful implementation of novel technology in the MERL space and what realistic expectations should be regarding the ability of big data to improve MERL outcomes.

In this interactive discussion, our participants will both try and answer the question:

Will technology and big data improve MERL or will existing structural issues in our communities, paired with known biases in existing data sets, make MERL all-the-more challenging?

Session slides


Alexa Courtney

CEO, Frontier Design Group
Alexa Courtney has over 17 years of experience working in the US and globally in South Asia, Africa, and Europe; co-designing strategies with organizations to better adapt and create impact and leading research, assessment, and evaluation teams. She pioneered the application of design... Read More →
avatar for Madeleine Gleave

Madeleine Gleave

Chief Data Scientist, Nithio
Madeleine Gleave is Chief Data Scientist at Nithio, a new analytics and finance platform dedicated to scaling off-grid electricity access across Africa. Madeleine was previously the Advanced Implementation Specialist for Dharma.ai, where she led the implementation of Dharma’s data... Read More →

Samuel V. Scarpino

Chief Data Scientist, Dharma.ai
Samuel V. Scarpino is the Chief Data Scientist and Dharma.ai and is an Assistant Professor in the Network Science Institute at Northeastern University--with appointments in Marine & Environmental Sciences, Physics, and Health Sciences. Scarpino's research spans a broad range of topics... Read More →

Friday September 7, 2018 9:30am - 10:30am EDT
Academy Hall Main Room 1825 Connecticut Avenue NW, 8th Floor, Washington, DC 20009