• CLIENT: Starbucks
  • ROLE: Lead Product Designer
  • Conceptual Design
  • User Research
  • Personas & User Flows
  • Information Architecture
  • Heuristic Assessment
  • Wireframing
  • Rapid Prototyping
  • User Testing
  • Style Guide & Hi-Fi Comps
  • Rapid Prototyping
  • Front End Development
  • Delivery and Integration Support

What If?

What would it look like if we could view the systems that Starbucks uses in a Google Earth environment? What if we could use AR/VR to view the data and entities using Hololens? Now, with Hegemonikon (Greek for Directing Overmind) we have that chance and possibility to radically change how systems are viewed within Starbucks, with views at 10,000 feet, 1,000 feet and hyper local views to give VPs and other customers a holistic view of systems such as financial, ticketing, & supply lines.


  • Create Digital Twin of Starbucks systems
  • Visualize data, stores and entities in an easy to understand format with Augmented/Virtual Reality
  • Enable modular design and allow for implementation

Starbucks does things a little differently compared to some other organizations that I've been with. With the Emerging Technology department, the goal is to identify what technology is nascent and how it might help Starbucks. The end stage of this project is to build out a working prototype to showcase to VPs and get buy off to build it out.

Roles & Responsibilities

As the lead designer on this project, I worked with a fantastic dev team, a very talented 3D unity developer, a great PM, and sought the input of the design & dev team for feedback, especially to a/b test, to deliver this tool. For this project, the development work was handled in conjunction with ASU where I had the amazing opportunity to mentor a few junior designers.

Scope & Vision

Determining the scope of this project was the first thing to be considered. Showing data from a 10k foot view down to the store level was neccessary and having an intermediary regional view is important as well. In this case, each view was broken down into actions that could be taking by the user for each view. For example, at the global level, we'd want to see how decisions impacted at a high level, whereas at a store level, the scope changes to see how decisions impact a particular store.

Starting Point

Answering the question of "What actions may be taken at a given scope" was built out. For example, with a regional view, the regional manager may want to see how distribution warehouses inventory is in preparation of new product drink release. At a store level, the owner may want to check local shipments and coordinate with adjacent stores for load balance inventory. At a global view, the executive may want to check quarterly finances.

User Stories

I spent a good deal of time on researching happenings at the store level, whether it was standalone, or within a larger store, such as Safeway or Target. I sat down and discussed with store managers and regional managers what they would like to see in a tool like this and how it could be useful in day to day and long term strategic decision making. It was fascinating to see the different approaches taken and these discoveries were a stepping stone to my own ideas about how to best accomplish this task for anyone using this tool.

Design Breakdown

Breaking down the problem into solving for the needs of the data taggers, the data scientists & managers here revealed a third need: an admin to be able to have control over the system including all the capabilities of the data scientists. Breaking each persona out by task was imperative to understand and from there, I was able to build out a flow (above) for all parties.

Component Design & Function Mapping

As the backend was being completed in the process, this neccessitated function mapping where I reorganized the front end to be more in line with both the Material UI design language and more accessible and easier to use for the customer. This allowed dev to easily see where the new functions were and how best to use neccessary react components.

The style guide came together quickly, building off the exsiting Starbucks style guide, developing custom components and testing out different layouts, then a/b testing in small groups with the greater dev & design team. This resulted in aligning with the initial pitch, giving the user a high level overview of the current workload at any given time.

3D Interface

A parallel design and development phase was created for the Hololens interface and how the world would show up. Interestingly, one of the problems was with icons when using Hololens. Drawing on my experience of designing within videogames for Xbox, I suggested using flat 2D icons rather than 3D since svgs could be used and it would also increase comprehension for the users. Below are practical examples of utilizing mapping APIs and overlaying Starbuck stores on top of the data to show how the user could move through a city to select a store.

End Result

When the team showed this off to the VPs, they were absolutely blown away. After working with the dev team to create a working prototype that was polished and on point, the team was able to demonstrably show that not only was Project Hegenomikon a functional, informative and impressive way to show off large amounts of data in a Metaverse environment, but that this could scale out to any system.

Being build in a modular format, meant that Hegenomikon could be used for other 1st and 3rd party applications. Amazing tech, ingenuity and panache coming together from very talented people that will help Starbucks acheive greater heights.

Chad Rawlinson
Product Designer
Starbucks Emerging Tech
"Gaining a deeper knowledge of AI, Metaverse implications, and how it impacts building better tools has been inpsiring. I am proud to give my customers, who are my coworkers better tools to work with. Having seen how data in a 3D environment behaves fills me with optimism towards a future where research results are exponentially increased. It's been a fantastic project to work on Hegenomikon, and this tool has laid the groundwork towards how to use and visualize data in intelligent systems that deliver incredible results."
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