Intro
Solving Volunteer Training Challenges Through Field Research and Design
I collaborated with a team of 5 designers to improve produce sorting at Feeding San Diego. Through field observations and interviews, we identified key pain points and created a wearable infographic system that clarified sorting standards, reduced waste, and maintained food safety.
Role
Product Designer and UX Researcher
Problem statement
Problem statement
Addressing Knowledge Gaps in Food Sorting
The volunteer-driven sorting operation faced inconsistent evaluation standards:
- Too conservative sorting - Volunteers discarded edible produce out of caution
- Too lenient evaluation - Unsafe produce occasionally entered distribution
- Inconsistent standards - Different volunteers applied different criteria
The challenge: make expert knowledge accessible to volunteers of varying experience in a high-paced environment with minimal training time.
Field Research Approach
Field Research Approach
Immersive Field Research
We identified volunteers as our main stakeholders that we wanted to improve their experience. We placed ourselves in their shoes to identify their pain points to tackle a real problem.
In-Context Interviews
Through casual conversations during sorting shifts, we captured real-time frustrations and thought processes.
Insights
Insights
Research Synthesis
To visualize our research, we built an affinity diagram grouping observations into three areas: the volunteer timeline, volunteer types, and common challenges. This helped us identify patterns and align as a team on what to prioritize.
Organizing field insights into timeline, volunteer types, and challenges
Mapping the Volunteer Journey
We then mapped the full volunteer process from onboarding to offboarding to track each step and how volunteers felt. This revealed a core pain point: newer volunteers lacked confidence when sorting produce. With little instruction, they often second-guessed themselves, slowing down the process and discarding edible food.
Sorting apples workflow highlighting confusion points
What we learned
What we learned
These knowledge gaps reduced the amount of food reaching families in need, underscoring the need for a solution that builds confidence, improves efficiency, and prevents waste.
Key Personas
Key Personas
Understanding Our Users
Volunteers represented a diverse group with varying experience levels but shared the common goal of ensuring food reaches those who need it most.
Ginny Baker
Student, 12 years old
As a first-time volunteer, I need guidance so I can sort without constantly asking for help.
Ideation
Ideation
Design Strategy
Our solution began to take shape through rapid ideation and storyboarding. The breakthrough insight: volunteers neededguidance at the exact moment of decision-making, not before or after. Early sketches explored infographic posters and apron designs, contrasting good versus bad produce through visual storytelling.
Infographic poster and apron showing visual contrasts between good and bad produce (no mold, no deep cuts, not squishy)
First Iteration
First Iteration
Wall-Mounted Poster Guide
Design approach - Posters showing one apple with all three problems: mold, cuts, and squishiness
Challenge discovered - Two major issues emerged: volunteers never looked away from their sorting stations to reference wall posters, and the cluttered design was too confusing to process quickly during fast-paced sorting
Key learning - Guidance must be in volunteers' immediate field of vision and focus on one clear problem at a time
Realistic vs. cartoon illustrations highlighting mold (black/gray/white fuzz), squishiness (soft when pressed), and deep cuts (can harbor bacteria)
Second Iteration
Second Iteration
Wearable Reference with Photo Realism
Design approach - Infographics on aprons with photographic examples of good vs. bad produce
Challenge discovered - Real produce varied significantly, slowing volunteer decisions
Key learning - Abstract representations enable faster recognition and broader applicability
Infographic on apron comparing minor bruises and small cuts (good) with moldy, squishy, or severely cut produce (bad)
Final Iteration
Final Iteration
Abstract Visual Guide with Clear Messaging
Design Strategy - Illustrated representations focusing on key identifying features rather than exact appearances
Success Factors:
- Clear categorical messaging - "If ___, then it's bad"
- Memorable and repeatable - Volunteers verbalized catchphrases to reinforce learning
- Behavior-focused criteria - Severe cuts, moldy texture, squishy feel
- Universal application - Works across all produce types
Wearable poster on apron with "If ___, then it’s bad" framework illustrating severe cuts, mold, and squishy texture
Results & Impact
Results & Impact
Empowering Volunteers Through Design
The wearable infographic system bridged the knowledge gap between experienced team leads and new volunteers:
- Eliminated sorting confusion, enabling independent decision-making
- Standardized evaluation criteria, improving food safety consistency
- Reduced food waste by preventing disposal of edible produce
Conclusion
Conclusion
What I Learned
This project reinforced that the most effective solutions come from observing users in their real environment. Immersive field research showed how volunteers interact with produce sorting in real time, highlighting the need for guidance that is immediate, clear, and actionable.
Challenges I Overcame
The biggest challenge was balancing visual abstraction: photographic examples were too specific, while simple illustrations lacked clarity. Abstract, behavior-focused representations like the wearable infographic enabled faster recognition and broader applicability.
Key Takeaway
Context is everything in design research. By embedding ourselves in the volunteer experience rather than relying on assumptions, we created a tool that volunteers actually used, improving decision-making, consistency, and efficiency.