New work samples added regularly!
Volunteers and community members frequently interpreted date labels (i.e., “best by,” “sell by”) as strict safety indicators rather than quality guidance. This led to inconsistent decision-making, unnecessary food waste, and reduced confidence when evaluating food items.
It was made clear that increasing knowledge alone would not change behavior, since the existing information was already available but not being used consistently. So, the challenge was not a lack of policy or information, but a gap in real-time judgment under ambiguous conditions, especially in fast-paced distribution environments.
Initially, it was unclear whether this should be addressed through training or a different type of intervention, which required further analysis.
Staff identified frequent confusion around food expiration labeling (best-by, sell-by, use-by), which slowed sorting processes and created risk of unnecessary food waste.
The goal was to improve decision-making accuracy during food sorting by:
Shifting reliance away from date labels alone
Supporting quick, defensible decisions using sensory evaluation
Reducing unnecessary food waste while maintaining safety and trust
The solution needed to function within real distribution conditions, where time, attention, and training are limited. The organization requested a clear, quick-reference performance aid to help volunteers and staff correctly interpret date labels during food sorting.
Rather than delivering traditional training, the solution provides just-in-time decision support to reinforce a consistent evaluation process.
We designed a set of performance support tools (job aids) that volunteers and staff can quickly use during sorting and distribution. Traditional training was not selected because it would not address the real constraint: limited time and attention during sorting.
Analysis showed that individuals defaulted to date labels because they are faster and easier to interpret, especially in high-volume, low-attention environments. This was a key shift in the project, as we moved from trying to explain correct behavior to designing for how decisions are actually made in practice. As a result, the design needed to reduce cognitive effort while supporting accurate judgment.
Prioritizing decision support over instruction
Instead of teaching concepts in isolation, the job aid guides users through a repeatable decision process:
Check for “do not use” conditions
Interpret date labels as quality indicators
Apply sensory evaluation
Reducing cognitive load through visual structure
Information was simplified into short phrases and grouped into clear sections (“Check the Date,” “Use Your Senses,” “Signs to Throw Away”) to support quick scanning and use during active work.
Designing for diverse, untrained audiences
Materials use plain language, consistent visual patterns, and icon-supported cues to ensure accessibility across volunteers, staff, and community members with varying experience levels.
Supporting real-world constraints
The tools were designed for use in fast-paced environments, requiring minimal instruction and enabling immediate application without disrupting workflow.
This approach ensured the solution aligned with both the performance context and the organization’s goal of reducing waste while maintaining safety.
While long-term impact data is not yet available, early feedback from stakeholders and peer reviewers indicated that the materials were:
Intuitive and easy to follow in real-time decision scenarios
Effective at reducing cognitive load through clear visual organization
Aligned with how decisions are actually made in distribution settings
Reviewers specifically noted that the structured flow (“Check the Date → Use Your Senses → Signs to Throw Away”) made the decision process more actionable and easier to remember.
The project demonstrates how simplifying guidance and aligning design with real work conditions can support more consistent decision-making, even without formal training.
This project changed how I think about instructional design. Initially, I approached the problem as a need for clearer instruction, but analysis revealed that the issue was not knowledge, but inconsistent application under real conditions. This required shifting from content design to performance support.
Working with a real client also highlighted the importance of validating assumptions early and often. Weekly check-ins helped refine scope and prevented over-designing solutions that would not fit the environment.
Moving forward, I will prioritize designing for how people actually perform tasks, not how they are expected to learn them in ideal conditions.
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