Making restaurant delivery easier to dispatch, execute, and track

Delivery is an important revenue channel for many of Tarro’s restaurant clients. Pizza shops can generate 20–35% of revenue through delivery, often relying on stacked weekend runs. Chinese-American takeout restaurants may deliver across a 5–8 mile radius, with a significant share of orders paid in cash and deliveries handled by family members or long-tenured employees.

But managing those deliveries can be highly manual.

During a rush, staff need to quickly decide which orders to send together, assign the right driver, track active deliveries, and answer customers asking where their order is. Drivers, meanwhile, need to know what to pick up, where to go, and what to do when they arrive without constantly calling the restaurant for help.

My focus was on improving the self-delivery experience and giving restaurants the tools to operate their own delivery business more effectively.

Staff needed to answer questions like:

The goal wasn’t simply to give drivers a mobile app. It was to create a connected delivery system where each person gets the information and controls they need at the right moment.

Drivers typically interact with the app while moving between tasks, so the experience prioritizes clear hierarchy, minimal decisions, and actionable information.

I designed the driver-facing app from the ground up, including order assignment and live tracking, and validated it in live restaurants.

At each stage, the app surfaces the information needed to complete the next action without overwhelming the driver with everything happening across the restaurant.

Staff can see unassigned orders alongside active drivers, identify orders that can be grouped together, and assign them to a driver as a single run.

The map provides spatial context, while the driver queue provides operational context: who’s available, who’s out delivering, and who’s returning.

This lets staff answer the question that comes up constantly during delivery, without needing to call or search through another system:

Some restaurants have a dedicated team of drivers. Others rely on a few employees who switch between restaurant and delivery duties. Some primarily take card payments, while others have a high volume of cash orders.

Rather than assuming one ideal delivery operation, I focused on creating flexible workflows that could support different staffing models while keeping the core interactions consistent.

The design also needed to work in the high-pressure environment of a restaurant: fast-moving orders, frequent interruptions, limited attention, and staff who may not have time to learn a complicated new system.

Driver Management V2 established a foundation for restaurants to manage self-delivery directly within Tarro, connecting the tools used by staff and drivers into one end-to-end workflow.

The broader goal is simple: