91 - “Some people may not understand why you have to sacrifice”: Evaluating learning outcomes through stories from Ghanaian women in graduate supply chain management programs

Abstract Information: Women are significantly underrepresented in supply chain management (SCM) globally, and particularly in sub-Saharan Africa, where SCM growth drives rapid economic and social transformation with vast gender implications. In Ghana, for example, women comprise only 18% of the SCM workforce. This trend begins in higher education, with fewer female students starting in and advancing to subsequent degree programs than their male counterparts. Noticeably absent, however, are the perspectives of women enrolled in SCM graduate programs in sub-Saharan Africa. Therefore, the Center for Applied Research and Innovation in Supply Chain - Africa (CARISCA) designed this study to elicit these women’s stories - their motivations, expectations, challenges faced, and successes celebrated - while pursuing master's and doctoral degrees at a leading SCM university in Ghana. We virtually conducted individual and group interviews with a total of 15 women and thematically analyzed transcripts according to principles of frequency, ​​universality, differentiation, and emotional response. Preliminary results indicate that most women felt the effects of acting against social gender norms and experienced “imposter syndrome” related to belonging. Participants coped with this by building community among peers, engaging with mentors, and taking encouragement from activities focused on lifting up women in SCM. Additional challenges included initial relationship building and vying for mentorship from overstretched advisors. While scholarships and associated training activities were universally recognized to facilitate success, an infrequently reported theme was that this unintentionally created stress related to maintaining good standing. These stories contour the process and outcome evaluation of training objectives for the USAID/CARISCA project.

Relevance Statement: Large international development projects have complex monitoring, evaluation, research, and learning (MERL) plans that integrate a variety of indicators and data sources to speak to the achievement of multiple objectives while serving thousands or millions of beneficiaries. While some of this data may be collected qualitatively, the rich and deeply personal stories of intended beneficiaries are sometimes lost in the quest for the most parsimonious evaluation approach. Arizona State University and Kwame Nkrumah University of Science and Technology have partnered to build the Center for Applied Research and Innovation in Supply Chain–Africa (CARISCA), funded by the United States Agency for International Development (USAID). CARISCA facilitates capacity strengthening for excellence in four areas: training, research, research translation and utilization, and inclusion and impact for women in supply chain management. CARISCA tracks 18 process indicators over these four components and uses a variety of evaluation methods in the MERL plan, including survey and interview data from training participants and end users of products generated.

But a different approach - storytelling - was needed in order to elevate the experiences of one group this project is designed to empower - women investing in graduate supply chain management programs. In this proposal, we describe how storytelling collected via qualitative interviews can add value to a large-scale evaluation in practice. As part of the evaluation of student learning overall, these stories are paired with quantitative self-reported data and program milestones to compare how external perceptions of success match with internal perceptions. This approach is useful in the unique context of graduate education, where trainees - particularly those from typically marginalized identities - can simultaneously experience episodes of near-crippling self-doubt and bold intellectual growth. We apply rigorous qualitative research methods to the storytelling approach; beginning with an a priori sample size determination and continuing with the generation of inductively-derived and deductively-derived codes, codebook development, and systematic application of codes before thematic analysis.