40 Million Tons Wasted Each Year.

Context: Hackathon

Timeline: 1 Week

Teammates: Evelyn Wan (Research)

My Role: UX Design, Ideation, Prototyping

And the impacts are colossal.


Food waste accounts for 16% of U.S carbon emissions, which is only 4% less than the toxic emissions of cars and transportation. When organic waste is dumped into a landfill, it undergoes anaerobic decomposition and generates methane, a greenhouse gas 25 times more potent than carbon dioxide.


The U.S spends over $218B (1.3% GDP) growing, processing, transporting, and disposing food that only sits in landfills generating toxic greenhouses and squandering away hours of labor and resources, all the while thousands of families sit in their homes with no food on the table.


Food waste also carries significant financial repercussions for consumer-facing businesses such as distributors, retail grocers, and food service providers who account for roughly 8M tons of landfill waste (40% of waste). All this waste translates to approximately $18.2B in lost profits.

If you're on a time crunch, skip to my designs here. Otherwise, enjoying reading the research!

Initial Research on Food Recovery Systems.

While a substantial portion of landfilled food is inappropriate for rescue due to factors such as spoilage, logistics, and cost of effectiveness, ReFed estimates that based on the rate of surplus food being generated, recovering an additional 5.8 million tons of edible food per year is entirely feasible under the right circumstances. Food rescue is a critical opportunity in a food system that is overrun with high numbers of waste and food insecurity. However, because food rescue systems are incredibly complex and filled with multiple areas of oversight, it is often difficult for non-profit food recovery organizations and programs to thrive and reach their maximum potential. Based on various peer-reviewed articles and food rescue intervention publications, we’ve identified the top 2 barriers to food rescue.

Logistical Barriers

◦ Mismatches between schedules of doner businesses and recipient organizations, and between food distribution programs and clients

◦ Mismatches in food quantity donated versus food needs

◦ Logistical barriers in relation to sorting, pickup, delivery and coordination of these tasks between organizations and staff/volunteers

Locality Barriers

◦ Food recovery networks are unique and reliant to a particular locality because regulatory landscapes differ from county to county so it’s difficult to operate across multiple jurisdictions

◦ Robustness of non-profit operations varies from place to place which makes it challenging for organizers to implement large scale resolutions or apply solutions that work well in all jurisdictions

We need centralized food recovery organizations that are able to adopt and implement the necessary infrastructure and technologies to bypass logistical barriers, connect to their local network, and motivate and educate businesses about the value and significance of donating excess food.

Secondary Interviews.

In order to narrow down a niche problem space and determine a fully operable objective, we conducted a usability research test to understand what's already on the market. 

As part of our user research, we interviewed a total of 5 different food recovery leaders (Chefs to End Hunger, Waste Not OC, Ecoset, Urban Harvester, and Food Forward) within Los Angeles in order to identify the key challenges associated with most food recovery organizations. From these interviews, we were able to identify two predominant models for food recovery: the reverse-logistics model, and the software intensive model. Organizations involved with food recovery can adopt the use of donation matching software(reverse logistics), or software that attempts to systemize the logistics involved with transporting food from a source of potential waste to an organization that feeds people(software intensive).

Our interview guide.

Reverse Logistics Model

Under reverse logistics, when a business receives a food supply shipment, food producers can load any excess food they wish to donate into their supplier’s truck. This truck then transports the donation, along with other donations it may have collected along its route, to its food supply warehouse. Here, donations are collected, stored in food safe conditions, and await pickup by charitable organizations who feed people. Reverse logistics utilizes already existing infrastructure to overcome some of the challenges involved with transporting donated excess food. Food recovery organizations like Urban Harvester, Waste Not OC, and Food Forward all incorporated some aspect of the reverse logistics model in their food rescue operations.

Key Flaws:

◦ Such a model is only able to include clients of a particular food producer

◦ Even with the simplification of scheduling, common logistical obstacles such as backhauls and donor to anti-hunger organizations mismatches still occur. Since surplus food quantity specifications are not entirely communicated, food haulers often end up carrying more than  anti-hunger organizations are able to store, and as a result that additional excess food ends up being discarded. 

Software Intensive Model

On the other hand, the software intensive model works through the use of a data driven technology platform. These platforms include existing third-party matching food and donor softwares such as Copia or Chow match. The platform prompts food producers to enter the type and quantity of excess food they’d like to donate, as well as additional information such as vehicle and kitchen specifications that partnering organizations will need to accept their donation. These specifications may include things like a refrigerated truck or a commercial kitchen. The platform then instantly matches the donation to a logistics partner and anti hunger organization based on these entities’ ability to accept food as well as proximity to the donation site. Once the match happens, scheduling of the pickup and delivery to the pantry can take place. Chefs to End Hunger and Ecoset both utilized some form or aspect of the software intensive model in their food rescue operations.

Key Flaws:

◦ This process requires immense cooperation between the facilitating food recovery non profit, government entities, food producing businesses, anti-hunger organizations, and potential logistics partners.

◦ Even with the utilization of matching donor technology, logistical issues such as backhauls can occur because donors can not continuously gauge and update the amount of food they have. Recipients often misread the amount of surplus food their storage can hold and truck haulers often misgauge the amount of food they have; this leads to discrepancies resulting in backhauled food being discarded in landfills.

What's Already Out There?

Problem & Goals.

Our Niche Problem

After a comprehensive usability test where we interviewed 5 different Food Recovery Organization CEO’s, we narrowed down the primary problem to an overlapping obstacle that nearly all food recovery organizations struggled with regardless of their model of operation: backhauls. Despite the current food recovery models in place, because food donors and anti-hunger organization recipients are not able to fully communicate the quantity of their surplus food in real time, it often leads to additional excess food AKA “backhauls,” being discarded due to a lack of storage.


Road to Belly aims to tackle the key problems that exist in current food recovery organizations. Our app ensures that regardless of locality, the basic issue of backhauls will never interfere with the efforts and operations of any food recovery organization.

Current Food Recovery Organizations' routes (left) and our proposed route (right).

1.) Takes care of the excess food unable to be donated during scheduled food hauler trips-solves the logistical barriers involved with communicating food and storage quantity between donor and recipients in real time

2.) Solves the logistical barriers involved with communicating food and storage quantity between donor and recipients in real time

3.) Matchers food haulers to recipients in real-time

4.) Tackles the changing food recovery landscape by providing food donations for individuals and families affected by Covid-19 in real time

Strategy and Exploration.

Our app hones in on allocating the surplus food that is thrown away in backhauls. Even with software technology, matching the exact amount of food to the exact available storage is difficult and often inaccurate. Not to mention, most of the food that is being distributed by trucks and Food Recovery Organizations are perishable foods. Thus, creating a way to bridge Food Surplus and Hunger Needs in real time is necessary.

Targeted Users:

◦ Truck Drivers for Food Recovery Organizations

◦ Anti-Hunger Organizations (Food Banks, Homeless Shelters, ect.)

◦ Smaller Communities in Need(Churches, Schools, Hospitals, Families, ect.)

Feature Prioritization

This is an early brainstorm session of some features that would be necessary to our target users in the app. Because of the time constraint, it was crucial that we focus on designing out an "MVP" version. Some other features that not included on here will be mentioned at the end.


Based on prioritization of features 1.) Truck Driver who had to notify those in close range of him of surplus food and 2.) the people around him who would accept this food, I wireframed two basic customer journeys for the app.

A Truck Driver notices he has extra food and sends out a ping (left) and an individual/organization in need receives a notification for that ping (right).

Final Designs.

Journey 1: A Truck Driver's Dilemma

A Driver who has extra food is able to notify people around him immediately. The only information they should provide are the estimated amount of servings of food they have and their destination location (either back to warehouse or home).

As people around him receive the notification, the algorithm processes them first-come-first-serve. Based on how many servings are available and how far the receiver is, the algorithm will calculate certain tradeoffs (ideally the cost of carbon emissions of either distance traveled or food wasted) to map out the best route for the driver to take.

Now, Driver has choice to take the route given to them, or make some changes. Let's say the Driver took the first choice. They have various options to view directions, message the receivers for specific directions, or stop the overall route.

If they decide they don't want to make the extra stop, they can cancel the stop and resume their newly created route.

Journey 2: The Road to Fulfillment

The initial onboarding takes receivers through a simple sign-in. Since receivers can range from as big as Shelters to as small as families, they need to be transparent with their numbers up front (bigger and more established organizations will be prioritized in the algorithm since they are recognized people in need). This is the onboarding for Organization affiliated users.

This is the onboarding for personal accounts.

Receivers get notified when a Driver near them has extra food that they'll toss if not taken. The Receiver accepts and the rest is history.

So, what next?

Working Assumptions to Validate

◦ Drivers are able to gauge amount of servings they have leftover

◦ Receivers will adhere to social contract and retrieve the food

◦ Most leftover foods on backhauls are perishable

Features for the Future

◦ Verifying Drivers and connecting them to existing clienteles if they are part of a Food Recovery Organization

◦ Incorporate volunteers into system

◦ Food Stamp verification for individuals

◦ Distinguishing Private and Public Food Recovery Organizations

◦ Educate and motivate businesses about the value of donating excess food

Thank you for reading!