Locally-Led Developmental Evaluation Advantages and Limitations: The Case of Headlight Consulting Services
By: Endashaw Beshir, Esrael Woldeyesus, Tseday Tilahun, Yitbarek Woldetensay, and Yomif Worku Introduction Development and humanitarian challenges are local in nature; hence, effective humanitarian and development assistance requires an inclusive approach that centers local actors throughout all aspects of the work (USAID, 2022; USAID Learning Lab, 2022). Locally-led development improves the participatory process and enhances
What is a Developmental Evaluation? (101 Level)
By Julie Mandolini-Trummel, CLAME Specialist, and Alison Harrell, CLAME Specialist, Headlight Consulting Services, LLC This blog post is the first in a 3-part series on Developmental Evaluations. In Parts II and III of this blog series, we will explore how to identify if a DE is a good fit for your project/activity and how DE
Two Tools for Assessing and Leveling Up CLA in Your Everyday Work
By Georgia Handforth, CLAME Associate, Headlight Consulting Services, LLC This blog is the second of a three-part mini-series on organizational learning and the Collaborating, Learning, and Adapting (CLA) Framework. Welcome back to our mini-series sharing Headlight’s experiences with Collaborating, Learning, and Adapting (CLA)! In the first post in this series, we talked about why CLA is
Evaluation Rigor in Action—The Outcome Harvesting Methods Memo
For the last 9 months, we have had something big in the works, and we are finally ready to share it. Headlight Consulting Services has compiled our first Methods Memo to provide guidance for professionals of all levels to implement stronger CLAME practices. This particular piece’s goal is to provide evaluators practical guidance for deciding
Introduction to Secondary Analysis
By: Maxine Secskas, CLAME Associate, Headlight Consulting Services, LLC This blog post is the third in a 3-part series on components of qualitative methods. This blog continues the discussion on how we at Headlight conduct Qualitative Analysis from the previous post called Intro to Primary Analysis. This blog post will build on the information from
Introduction to Primary Analysis
By: Maxine Secskas, CLAME Associate, Headlight Consulting Services, LLC This blog post is the second in a 3-part series on components of qualitative methods. This blog post (as well as the previous post with tips on qualitative coding and the upcoming post on Secondary Analysis coming on April 7) is intended to expand on our
Top 5 More Dos and Don’ts of Qualitative Analysis
By: Maxine Secskas, CLAME Associate, Headlight Consulting Services, LLC and Chelsie Kuhn, CLAME Specialist, Headlight Consulting Services, LLC This blog post is the first in a series of 3 posts on components of qualitative methods. Welcome back to Headlight’s educational blog series on all things collaborating, learning, adapting, monitoring, and evaluation (CLAME). You may have noticed
Findings, Conclusions, and Recommendations Matrices
By: Chelsie Kuhn, MEL Associate, Headlight Consulting Services, LLP This blog post is the last in a series about qualitative methods. Up to this point, our series has covered thoughts on qualitative rigor truths, things to keep in mind for implementation, and recommendations to help with qualitative data analysis software and coding setup considerations. To
Choosing the Right Qualitative Analysis Software
By: Chelsie Kuhn, MEL Associate, Headlight Consulting Services, LLP To facilitate the implementation of recommendations from our last post on Qualitative Rigor, we thought it might be helpful to offer up some considerations for choosing a qualitative analysis software before getting further into the process. Qualitative analysis software allows researchers and evaluators to better organize,
Designing Rigorous Qualitative Practice (part 1)
By: Rebecca Herrington As researchers and evaluators work to monitor, evaluate, and learn from developments in the field, we often collect qualitative data from beneficiaries and stakeholders via observational interactions and documentation, focus groups, key informant interviews, and more. Many are apprehensive to trust findings and recommendations from qualitative data, and they critique the qualitative
