Our first hypothesis was very broad: edible food exists, but people who need it can’t access it. We planned to cover the whole food ecosystem, providers, community organizations, recipients and everyday residents, thinking we could utilize interview insights to find a gap within it.

BRIDGEGOOD then gave us the amazing opportunity to have our progress reviewed by PayPal Product Managers and Engineers. Their feedback led to a major pivot: rather than trying to design for the entire food ecosystem, we needed to identify a specific user and opportunity to focus on. We then hypothesized that better coordination will increase the amount of excess food that is redistributed.

Our mentor Judy pushed back: restaurants, cafes, and food banks were still too much for four weeks. Each of us pitched one stakeholder, plotted the ideas on an impact vs. feasibility grid, and dot-voted.

We interviewed users 1-on-1 to gain insights into how they deal with or dispose of any extra food in their household, and then their experience around donating to community fridges.

Using AI and FigJam, we first synthesized our interviews by pulling out quotes, pain points and insights and grouping them by category. To explore those insights, we ran Crazy 8s and compared ideas across two teammates.

Then we noticed we were designing solutions without defining the “why.” Instead of generating multiple solutions for one specific problem, we were forcing a single catch-all solution onto multiple problems at once.

So we pivoted backward to anchor our ideas in a core problem first. We synthesized the highs and lows from our interviews and affinity-mapped them into recurring themes. Out of nine themes, one stood out: a lack of centralized information.