During my internship at Bean Research, I have had the opportunity to experience the breadth of social impact work. Over the past 2 months, my understanding of evaluation has gradually shifted, and I have come to see it much like building a map.
Finding the landmarks
One of my first tasks, involved reading monitoring and evaluation forms from charities to produce short snippets that captured their work. The volume of information was initially challenging, but the process effectively introduced me to the scope of each grantee and quickly became an exercise in judgement. I learned to distinguish the details that best represented a project’s impact and go through multiple sources in a systematic way. By the end of my first week, I had doubled my efficiency from eight to sixteen snippets a day. I later applied the same approach to my work on CashBack for Communities, producing summary sheets that highlighted how different organisations approached creating social impact with evidenced success. Compiling statistics alongside case studies showed me that a representative evaluation depends on balancing measurable outcomes while preserving the stories that explain why those outcomes matter.
Just as mapping relies on identifying the landmarks that define an area, evaluation depends on recognising the information that best explains how change happens. Sitting in on client meetings for new projects gave me my first insight into the early stages of an evaluation, where the conversation focused on uncovering the “threads” that reflected the organisation’s activities and the outcomes it hoped to achieve. Rather than creating something entirely new, strong evaluators work with existing theories of change and the client’s understanding of the work to streamline how they describe driving change and how it can be measured.
Exploring new routes
Maps are rarely perfect on the first attempt, and neither are methods for evaluation. Throughout my internship, I saw the importance of fine-tuning approaches to improve both efficiency and insight. At ChEW’s Festival of Impact and Evaluation, discussions around AI reinforced this idea. It’s a common worry that AI is beginning to take over many forms of human contribution, but this conference emphasised that the focus of AI in charity sector evaluation is shifting to designing systems that optimise processes rather than blanket tasks. That emphasis on improving processes stayed with me during a project I am especially proud of: mapping.
While mapping locations of grantees, the existing software was unable to map deprivation areas alongside pinpoint markers. I decided to experiment with a new mapping software, stepping out of my comfort zone to work with geocoding datasets and developing several mapping options combining locator and choropleth styles. Creating the methodology for this software was particularly gratifying, as I contributed a workflow that the team can use in future projects to visualise both where organisations are working and the level of need in target areas.
Looking back at the goals I scribbled down before starting the internship, I could never have anticipated how much I would learn in such a short time. I am incredibly grateful to everyone at Bean Research for their guidance and willingness to involve me in so many different aspects of the team’s work. It has been an invaluable experience.
Aliza Mathew, King’s College London, Global Health Undergraduate & Bean Research Intern
