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HOTBOX PLUS: enabling seamless food deliveries

HotBox Food, Italy and Innovation Catalyzer

Bharat | Hymke Hemstra | Ludovica Rossi| Nupur P.

5 months

User Research | UI/UX Design | Design strategy | Design ethics 

UX researcher | UX Designer | Visual Designer | Project Manager



In the last few years, the global pandemic has accelerated the growth and expansion of food delivery businesses. This has led to a shift in customer behaviour toward the convenience of cooked meals delivered to their doorstep. As a result, there is more pressure on restaurant managers to ensure timely order preparations, preserving food quality during deliveries or managing riders.

Our client created Hotbox, a ventilated professional oven that can control humidity and temperature between 65 and 85°C. Hotbox ensures warm and high-quality home deliveries without making the food cold or soggy. Because Hotbox allows multiple stops on a single trip, restaurateurs can be considerably more efficient in making higher numbers of quality deliveries, improving their business. To take advantage of this new possibility, Hotbox has developed a custom IoT board to gather data from sensors (Speed, GPS and Accelerometer).


This created a need to organize & make sense of the IoT data in a useful digital application for managers to understand their business efficiency. Our design challenge was to make sense of the gathered IoT data and depict how it may benefit the key stakeholders (managers, riders and customers) in the system. Besides this, the 3 key challenges of the brief were to-



The key research questions were to make sense of the IoT data collected by the smart Hotbox oven during deliveries, identify how can this data be useful to all the stakeholders involved in the system. To further understand the multiple stakeholders in the system, we created a stakeholder matrix of interest, identifying managers, riders & customers are the direct stakeholder in the system. We created an ecosystem map of all components in the system to identify the appropriate research methods. 

We performed an in-depth desk research to learn about the project context such as conditions of riders, IoT technology, sustainability in the IoT etc. We conducted personal interviews with several restaurant managers & riders to learn from their stories & gain insights about their everyday experiences. We also created a customer surveys to learn about general perceptions of ethics of food delivery system. After completing all the interviews & survey we used affinity and empathy mapping to cluster key research insights. This gave a holistic idea of most important patterns & opportunities for the project.


Concepting & ideation was a critical phase for the project where we explored different ideation methods such as word-concept association to validate some of the key insights that came up from interviews & surveys. We then tried to cluster our key concerns into HMW questions. Our team wanted to visualize other ideas than a digital solution so we tried rapid paper prototyping to gain clarity on some of our initial thoughts. We created experience journey maps for all stakeholders to map their goals, challenges, needs and opportunities. We further use scenario mapping that helped us identify multiple possibilities that can happen in the project context.

To get some more clarity of on how the restaurant and delivery system works, we tried role playing and wizard of Oz in our group. Each group member in the team role played as separate actor in the system where one-person acted as the backend system relaying messages. This method was useful to identify some key design directions such as challenges of discovery location of rider and how it can affect drop off time, need for riders to take a break after completing a long route, etc.