Data collection for research- based organizations – to aid research! Metrics: How am I doing? How’s My Program/Project Doing? How’s My Nonprofit Doing? 12NTCNPOKI Stan Mierzwa
May 16, 2015
Data collection for research-
based organizations – to aid
research! Metrics: How am I doing? How’s My Program/Project Doing? How’s My
Nonprofit Doing?
12NTCNPOKI
Stan Mierzwa
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Agenda
• Who is the Population Council
• Case study of electronic data capture (what, why, how)
• What we didn’t capture that I wish we did
• Trends for tools
• Need for a focused group in ICT
The
Population Council conducts biomedical, social science, and public health research. We deliver solutions that lead to more effective policies, programs, and technologies that improve lives around the world.
Capturing Data
Why capture self-report data electronically?
• Research indicates interview method affects answers to sensitive questions
• No interview bias’
• Increased privacy and confidentiality may lead to more honest reporting
• With Face to Face (FTF) interviews, participant may be more likely to:
• Under-report on sensitive questions
• Over-report desired behaviors
What is ACASI?
• ACASI = Audio Computer Assisted Self-Interview
• What is the
interviewer’s role?
Why did our IT group get involved in this sort of project?
• Decision was made to partner more closely with the programmatic groups and researchers – where possible
• Help where there was an un-met need
• Improve collaboration (internal and external)
• Help present innovative solutions during proposal preparation – add value
What we did not capture
Data NOT Captured that could have been useful-good problem
• Total number of electronic surveys done thus far
• Warehoused the data to be able to report on it all
• Keep track of all surveys, listing translations, locations done and key indicators
• % of incomplete and error surveys
• Centralized list of success stories
How the data may relate to the “bigger” organizational picture
• M&E
• Capture data to align with key elements monitored
• For potential future funding
• Efficiencies to drive down cost
• Efficiencies to look “on the ball”
• Efficiencies to prove innovative
Tools
Tools to consider
• From unconventional places
• SMS; USSD; IVRS
• “Smart” devices
• Wisebags; Refrigerators (I’ll explain)
• Smartphones
• Open-source
• Frontline SMS
• Open Data Kit (ODK)
• The tool should not be the focal point!
Need for separate ICT group?
(another good problem)
Questions or comments?
One More Time!
• Small data capture projects can end up scaling up fast – prepare yourself
• Partnering with research staff is a very positive experience
• Look ahead – capture qualities about the survey data itself
• Consider how you might start to become a semi-profit center
• Move quickly if you build something
• Get engulfed in the work
Acknowledgements
Samir Souidi
Irene Friedland
Craig Savel
Deborah Boccio
Ashutosh Mishra
Adan Isaac
Paulino Ruiz
Chung Wu
Mike Lim
Du Luu
Paul Hewett
Barbara Mensch
Jim Sailer
Ruth Merkatz
Pamina Gorbach
Lauren Katzen
Sarah Littlefield
Evaluate This Session! Each entry is a chance to win an NTEN engraved iPad!
or Online at www.nten.org/ntc/eval
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