Timeline:
January 2023-July 2023
UX Design

Cookie.io

Physical systems engineering often feels like navigating a dense labyrinth. Engineers face challenges where hours quickly turn into days, and clear solutions can be elusive. This case study showcases my effort to unravel these complexities, with the goal of arming engineers with tools that optimize their product life cycles with efficiency and precision.

Background

In product research and development, complexity is a common challenge that extends the product life cycle and often hinders innovation. Engineers, much like bakers, spend significant time ideating, testing, and developing intricate subsystems, leaving little room for out-of-the-box thinking. As the sole product designer on this R&D initiative, I tackled this unique challenge of demystifying complex problems. Through data visualization, machine learning, and AI, I created a tool which sparks creativity, innovation, and shortens the development cycle from years to months.

Note: For the sake of confidentiality, and to provide a more relatable context, we'll delve deeper into this journey using the familiar metaphor of cookies 🍪.

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The Problem

The world of baking is much like that of design and engineering. Whether it's the pursuit of the perfect cookie or the blueprint for a groundbreaking aircraft, both journeys are paved with trials, errors, and countless iterations. The comfort of familiar recipes or designs often becomes a safety net, limiting the horizon of exploration.

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The Goal

Introducing COOKIE.IO: A cutting-edge, AI-powered tool designed to cut through these constraints. Much like engineers, bakers are experts in crafting delectable masterpieces after countless trials, errors, and scientific precision. The pursuit of a perfect cookie recipe often mirrors the journey of creating a novel physical subsystem - it demands time, resources, and numerous iterations. Consequently, bakers, similar to engineers, often rely on their tried-and-true recipes, limiting the scope for creativity and exploration.

Let's put this into perspective. Imagine a baker looking at three cookies: Double Chocolate Chip, Dark Chocolate Chunk, and Red Velvet. Each cookie has its own unique characteristics.

Primary User Persona

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The Cookie Workflow

‍Baker’s Note: While the following workflow captures the essence of the process, bear in mind it's a metaphorical depiction of a program aimed not at bakers, but at system engineers.

Baker's Current Journey

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Understanding the Cookie Mission

Traditional: A baker starts by defining a specific cookie goal – often referring to existing recipes while considering factors like cookie type, add-ins, and baking conditions.

COOKIE.IO: As bakers define their goal, every preference is captured via a user-friendly form, ensuring a seamless start, and setting the context for exploration.

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Ingredient Exploration: Conducting Trade Studies

Traditional: Bakers ideate potential recipes, often losing valuable insights about discarded variants.

COOKIE.IO: With a simplified visualization through Parallel Categories Plots, bakers get a holistic view and deep dive access, preserving every grain of insight. Bakers can effortlessly compare groups of similar cookies and individual cookies, using their findings as a springboard for ideation, exploration, and fine-tuning.

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Dough to Oven: Shaping and Baking

Traditional: Having chosen a recipe, bakers shape the dough, consider cookie dimensions, chilling periods, and baking temperatures. Next, they put the cookies in the oven to see if the final product aligns with the mission.

COOKIE.IO: Simplified through our match ranking score, bakers are offered the most suitable cookies based on their preferences.

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The Iterative Oven Ordeal

Traditional: An iterative process of trials and adjustments, ensuring the outcome remains true to the original mission.

COOKIE.IO: With Chippy, the AI Assistant, iteration becomes inspiration. Bakers receive real-time feedback, reducing trial cycles.

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A Guided Tour Through Cookie Comparisons

Traditional: Bakers manually compare cookies, weighing pros and cons based on memory and scribbled notes.

COOKIE.IO: The Side-by-Side and Pairwise Comparison tools guide bakers, offering an easy way to contrast cookies, delve into their attributes, and make an informed choice.

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Putting the Cookie to the Test

Traditional: After multiple attempts, the final cookie undergoes the all-important taste test.

COOKIE.IO: After their guided journey, bakers are seamlessly led to their desired cookie, complete with all the details to make their envisioned recipe come to life.

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The Workflow Bakers Knead

The majority of the baker's process is incredibly hands-on. While this hands-on approach is integral to the craft, advancements in technology and the rise of AI present opportunities to streamline the process and eliminate some of the more tedious aspects. That's where COOKIE.IO comes in.

COOKIE.IO leverages AI to automate several stages of the baking process, providing a more efficient and creative workflow. It helps to preserve and utilize the valuable insights from discarded dough variants and reduces the trial-and-error cycle, among other improvements.

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Baker's User Journey with Cookie.IO
Baker's Journey with COOKIE.IO

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A Dough-Namic Approach

Imagine a vast tray overflowing with an assortment of cookies, each holding a unique combination of flavors, textures, and ingredients.

Your objective: decipher the formula for The Ultimate Chewy Chocolate Chunk Cookie.

Assessing every cookie individually would be akin to identifying distinct melodies in a full-blown orchestra. Instead, a more efficient approach could involve:

1. Grouping: Organize the cookies into clusters by similarity, much like categorizing music into genres. Within each cluster, there's a representative cookie - a centroid - that embodies the essence of its group, similar to an iconic track representing its genre.

2. Detailed Comparison: By laying out these representative cookies side by side, we enable a thorough exploration of their nuances and characteristics.

In our journey to decode the intricate world of cookies, we employed two powerful tools. One mimics this intuitive act of sorting, grouping cookies by their similarities. The other lets us lay out these groups side by side, allowing for a detailed comparison and a deeper dive into the nuances of each group.

Your browser does not support the video tag.
The act of grouping these cookies is powered by Self Organizing Maps (SOMs). Without diving deep into the technicalities, think of SOMs as our expert cookie sorter, grouping vast arrays of cookies based on multiple intricate features.
With our cookies neatly grouped, Parallel Categories allow us to dive deeper into the characteristics of each cluster. By laying out each group side by side, we can easily compare features such as size, texture, and baking temperature.

This visualization prompts us to investigate:
  • How does texture vary across groups?
  • Is there a group that has a particularly high or low baking temperature?
  • How does baking temperature influence size or texture?
  • Which group is closest to our preferences for the Ultimate Chewy Chocolate Chip Cookie?

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A Recipe For Success

Below, you'll find key screens detailing a baker's mission to find the 'Ultimate Chewy Chocolate Chunk Cookie'. Once they've defined their cookie preferences and uploaded their cookie dataset, they're given the tools to explore relationships between different groups of cookies (clustered by SOMs) and the individual cookies within each group. Each cookie group and its constituent cookies are ranked based on how closely they align with the baker's target values.

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Cookie Samples

Preference Confirmation

Kickstarting the journey to the Ultimate Chocolate Chunk Cookie, bakers specify their preferences ensuring every chip and chunk is considered!

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Meet Chippy: Our Resident AI Expert

Bakers also have the opportunity to consult Chippy, our in-house AI assistant. Chippy is designed to adapt to the user's preferences and provide tailored insights that help bakers fulfill their cookie mission.

Chippy, AI Chat

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Choosing the Right Cookie

As the cookie saga advances, bakers shortlist their top contenders, each cookie vying for the title of The Ultimate. With our dual-pathway analysis, the decision-making becomes a piece of (cookie) cake.

Preference Confirmation

Kickstarting the journey to the Ultimate Chocolate Chunk Cookie, bakers specify their preferences ensuring every chip and chunk is considered!

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Lessons From the Oven

While we were successful in meeting the project deliverables, there were certain areas we identified for potential improvement. If I had another crack at the cookie jar, there are a few areas I would highlight for improvement.

I would prioritize
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    User Testing
    We had limited access to our target user group, leading to reliance on assumptions and the expertise of a few subject matter experts. In the future, we would strive to engage more extensively with our user base to validate our assumptions and refine our design based on their direct feedback.
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    Project Management
    Shifting priorities, leadership changes, and budget cuts disrupted the project's orderly progression. Next time, we aim to implement robust contingency plans and maintain clear communication lines to better manage such disruptions.
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    Strategic Planning
    The project leaned heavily towards exploratory design, which led to a focus on breadth rather than depth. In the future, we aim to strike a better balance between the breadth of exploration and the depth of the user-focused narrative. This would involve developing a more comprehensive strategic plan to ensure consistent narrative development throughout.