Staff Capacity Building and Data Analysis

Written by Kyle Krym, Aythos's Agriculture Programs Intern

As part of my internship, I’ve recently been designing and conducting multiple staff capacity building trainings. Topics of trainings have included creating Google Forms, drafting project proposals, making flexible budgets, using statistics, designing surveys, and analyzing and visualizing data. These trainings have gone quite smoothly over Zoom and have also been a lot of fun, serving to further solidify our close working relationships.

Besides getting to engage more closely with the amazing team in Nepal, conducting these capacity building trainings has also allowed me to:

1. Pass on the knowledge I have gained from graduate school and past jobs and internships;

2. Come up with creative ways to further current projects by making them the focus of the training sessions;

3. And provide value as an intern that will serve Aythos’ staff and organization well into the future.

In designing these trainings, my goal has been to make each training build off the previous one. Introductory statistical analysis and surveying methodology allowed us to then adeptly and critically analyze data from a past survey of Helambu kiwi farmers. Our statistical and visual data analysis will next be used in a training on how to present and tell stories with the data in order for projects to be reviewed or implemented.

While the data from Helambu kiwi farmers was collected last November, only the overall kiwi production of individual farmers and villages had been calculated. What the database actually contained was a treasure trove of insights. A deep dive into the data allowed us to realize larger kiwi producers must have been missed in the survey, a finding which should improve future sampling. It also highlighted statistically meaningful differences within villages when it came to 2018 vs 2019 kiwi production, average kiwi production per plant, the sources of their kiwis, and farmers’ knowledge of kiwi markets.

Potential policy implementations resulting from this analysis includes an increased emphasis on improving kiwi farmers’ collective knowledge surrounding kiwi markets and how to locate kiwi buyers. While the pandemic and lockdown makes going to villages impossible, the data also reveals farmers within each village that might be good candidates to speak with other farmers, either because they have sold their own kiwis at above average rates or because they have managed to enjoy greater per-plant kiwi production.

Aythos is well-regarded for its caring approach and empathy, which is why the organization is trusted and able to repeatedly survey these villages. Once the data is collected, increased data analysis and data visualization techniques will help tell the story of the data, leading to more-informed programming and better results for Himalayan communities. Any organization is only as capable as its staff, and the future of Aythos is bright.