In 2017, IDEO acquired longtime partner Datascope and integrated the company’s data scientists and engineers. Datascope team members aren’t just passionate data scientists; they’re human-centered designers who happen to work with data, as illustrated by successful collaborations like this one:

If Procter and Gamble (P&G) were a city, it would be the size of Boulder, Colorado. The company employs more than 100,000 people in 70 countries. Its research and development team is made up of more than 20,000 specialists working across locations, languages, and areas of expertise, from cleaning chemicals to paper products to over-the-counter medications.

P&G approached Datascope to help the company connect these researchers to one another and the rest of the organization. In working with P&G leaders, Datascope found that the company needed a better way to access and leverage employee expertise. Managers routinely got requests from researchers looking to work with others in their subject areas, but didn’t know how to identify the right partners or set them up for fruitful collaboration.

Datascope gathered internal data, including unstructured research data on the scientists’ interests and who they partner with most often. The team used that information to develop two new systems that bridge the gap for P&G researchers and managers. The first is an internal search engine that lets managers quickly find and connect the right experts across P&G offices worldwide. The second is a data visualization tool that highlights subject areas ripe for more collaboration among experts and research teams, who may already be asking similar questions. This intelligent tool can surface relevant, timely information managers need to connect their teams.

P&G already had a practice of collecting information for product research, but it wasn’t until Datascope came on the scene that the company took advantage of large, multi-layered data sets and made them more intelligent, so leaders could expand P&G’s expertise through new global partnerships.

In 2017, IDEO acquired longtime partner Datascope and integrated the company’s data scientists and engineers. Datascope team members aren’t just passionate data scientists; they’re human-centered designers who happen to work with data, as illustrated by successful collaborations like this one:

The second a smartphone debuts, buyers, bloggers, and journalists begin writing comments and reviews—and users start troubleshooting. Motorola Mobility wanted to tap into this river of data, but didn’t have the right tools to collect and respond to it.

Motorola’s design, engineering, and service teams hoped to identify product problems early, address them quickly through customer support, and ultimately fix them in future releases.

So Datascope built a custom engine that aggregates and analyzes feedback from hundreds of millions of phrases and internet references, drawn from consumer sites, user forums, news coverage, social media feeds, and product reviews. The tool parses key, product-specific information and routes it to the right Motorola teams: hardware, software, connectivity, and interface design, to name a few.

The analytics and visualization engine not only studies product performance in real time, but it also uses algorithms to gauge customers’ emotional reactions: Do they like the phone or hate it? Do they have complaints? Are they recommending it to friends?

Datascope’s tool translates all this data into simplified to-dos that are sent to the correct service and repair staff before user issues can mar a product launch or even the company’s reputation. And as engineers discover more about how a phone performs in the real world, they learn how to avoid making similar mistakes in the future.

The tool proved valuable as soon as it launched in 2012: When Motorola released the RAZR M smartphone, customers had a hard time figuring out how to use wifi and voice features at the same time and lodged complaints online. The engine recognized the pattern of complaints and alerted Motorola's customer support team, which was able to post responses with clear instructions in every relevant forum, turning a potential customer satisfaction problem into a positive interaction.

Motorola continued to use the engine to address issues in later releases of the RAZR M. The advance warning made engineers’ lives easier, while better handsets and software made for a more seamless customer experience. Improvements were also evident in the RAZR M’s well-reviewed next generation, the RAZR MAXX.

Based on the tool’s success, Motorola used it to improve the company’s supply chain and product development process. And beginning in 2014, with the Moto 360 smartwatch, Datascope’s analytics engine has been used to gauge performance and public sentiment not just for new smartphones, but for Motorola Mobility’s entire line of products.

For most parents, ensuring their child’s proper nourishment is a top priority. But that’s not always easy, especially for parents on the go. Plum Organics, an organic baby food company, set out to solve that problem by providing families with pureed fruits and veggies in pouches, making it easy for them to feed their babies. Plum approached IDEO for help designing a non-pouch package that could showcase the vibrancy of the ingredients within.

By conducting research and in-person interviews with families, Plum set out to ensure that the new product was both desirable and functional for parents and their babies. By joining families in their homes, IDEO was able to gather essential insights that helped inform prototypes and the final design, like the fact that nothing can replace the feeling of making an intimate connection with a child through spoon feeding; that baby food is often wasted if a parent can’t remember how long a product has been in the fridge; that families struggle with how to spoon-feed their children on the go without making a mess, and that both parents and retailers were concerned that baby food jars don’t stack securely on shelves.

With those insights in mind, the team designed a transparent bowl that allows consumers to see the natural color of Plum’s vibrant, organic food. A resealable lid makes it easy for parents to store food between feedings, and the container includes a feature that allows them to track the day that they opened the pack to ensure that they don’t end up throwing away perfectly good food. Lastly, the new package is easily and safely stackable and includes a divot in the lid for parents to rest a spoon on, making for a much cleaner and more sanitary feeding experience.

Baby Bowls for Plum are now available at retailers nationwide and are a natural evolution for the brand, helping Plum continue to provide high-quality, organic baby food for consumers and their children, even if they’re eating on the go.

Accessing our genetic code is as easy as spitting in a tube, but how can we benefit from all that DNA data? IDEO surveyed more than 1,000 Americans about the gene sequencing services they want. "Give me things I can act on,” one respondent said. “Give me advice, action plans, apps, and tools. Information is just air until I can put it to use." As it turns out, tools that can translate our genetic information into better life choices—to improve our health, chart our family history, or even find an effective exercise routine—are hard to come by.

Inspired to organize and apply the wealth of genetic data in all of us, Helix envisioned the first online platform for products that offer insights based on a person’s unique DNA sequence. The startup’s founders approached IDEO to help them get to launch by identifying their future market segments and designing their brand and product offering.

Helix sequences all 22,000 of your genes from one saliva sample—sent in a mail-in kit—and hosts a marketplace of products developed by trusted brands and innovative developers that explore your health, ancestry, entertainment, family, fitness, and nutrition. Similar to the Apple app store, Helix lets you pay individually for the products you want and is a platform for developers to launch new offerings over time. After you've provided a DNA sample once, every product in the Helix store is made available to you on-demand. So, as new products are launched and new discoveries are made in the field of genomics, the data from your original sample is all you’ll need to keep exploring your personal genetic insights.

IDEO engaged a range of users, including early adopters of at-home genetic tests and “quantified self” enthusiasts, and surveyed potential Helix customers across the country. That qualitative and quantitative research validated Helix’s “app store” business model and provided key insights into the products people were most interested in.

Through the partnership, Helix uncovered what users need most from a genomics company:

• to prioritize the accuracy and privacy of DNA test results
• to encourage a sense of discovery and exploration of our genes
• to celebrate each individual’s unique qualities

A team of ethnographers, data scientists, and designers at IDEO helped direct the startup’s brand approach (including its name, Helix) and crafted a blueprint for how the company connects with customers and presents its product. The Helix store launched in July 2017.

Our DNA used to be a mystery—something we guessed at by observing our parents. Now, easy access to our genetic code—and the tools to truly understand it—arrives on our doorstep.

The toymaker came to us to figure out how to make the device safe and fun. We started thinking not just in terms of physical usability (though designing for tiny hands and making sure products can survive a drop on the ground is our bread and butter), but also about how we encourage healthy engagement patterns.

A lot of VR headsets are designed to be super sticky—so engaging that users don’t want to take them off. But when we design for kids, we spend a lot of time thinking about how we can create healthy interactions. We wanted the design of the View-Master to help children intuit when it was time to put the toy down. So, we decided not to include a head strap—or any other means of attaching the headset to little bodies. When kids felt their arms get tired or their eyes start to cross, they would know it was time to take a break.

Over the past four decades, the IDEO Play Lab has designed and licensed more than 250 toys and games, from classics like the Barbie Camper to the first set of Sesame Workshop smartphone apps for kids.

With every product, we think about how to design fun and engaging experiences that delight parents, entertain kids, and lead to success for our partners. But we also put a lot of thought into making design decisions that support healthy habits, and help kids—and their families—thrive. 

Here are a few examples of how we’ve navigated those design choices.

Designing for movement: Dusty Wing Control

Most of us have learned to use a joystick or a set of arrows to drive a remote-controlled toy or move a character around a screen. But when we set out to help bring the character “Dusty” from the popular Disney movie Planes to life in an action-oriented vehicle toy, we took a step back to rethink how littler kids would engage with it.

As we tested designs, we saw that small children not only struggled with small buttons and the spatial skills necessary to operate the typical remote control joystick, but also that there was no fun in sitting still and tapping buttons. Instead, during our design research sessions, kids pretended to be the characters: They went full airplane mode, hands stretched out, zooming around the living room, dodging furniture. 

Taking a cue from their play patterns, we put Dusty’s remote control mechanism in toy wing tips that fit on little hands, enabling them to interact in a way that is not only more fun, but also instinctive, better mirroring how they naturally play. Players drive Dusty forward by pressing and holding a controller button, enabling his propellers to spin. When they bank left and right, Dusty matches their every move. Dusty even calls out flying commands that they can perform together.  The toy is not just easy for them to operate; it also gets them off the couch and moving, playing the main character in their own stories.

Designing for confidence: Pictionary Air

When we set out to re-invent the classic drawing game for the digital age, we had to figure out how to bring the core interaction to life in a new way. During ethnographic research, we noticed that when players were under pressure, they would often stare at their drawings looking embarrassed, and hesitate to keep drawing. To get people out of their heads and back in the game, we designed a new interaction that keeps participants looking up and laughing with each other. We combined a light pen and a smart device’s camera to allow picturists to create life-size illustrations in the air in front of them, an early foray into AR for classic games. For another layer of fun—and another option for those with less confidence in their drawing skills—players could interact with their sketches to provide more clues, much like in charades. We also decided to make drawings disappear quickly after each round was finished, to lower the stakes for self-conscious players.

Designing for all ages: Twister Air

In classic Twister, the fun hits when players are frozen in contortionist poses, hovering and balancing over each other. Our challenge from Hasbro: What does Twister look like in the TikTok era? And how do we make it fun for everyone? As we tested out potential interactions, we observed that for younger kids and older adults (basically everyone but the teenagers), the choreography on most popular dances was a bit much to learn or to even attempt. While kids found it hilarious when parents messed up (you’ll see lots of dance flops posted online!), we also wanted to find a way to create a sense of achievement for all ages. We started looking for the sweet spot between silly fun and accessibility, stretching players just enough to make them feel challenged, but not too overwhelmed to keep trying. In our prototypes, we preserved the classic Twister interaction while building in opportunities for rockstar moments where players can flop or shine. The footage made for viral family group chat nuggets, helping everyone feel part of the fun.

Designing for development: Little People Klip Klops

Preschoolers love the action of cars zipping down racetracks. But typical matchbox cars move too quickly for their little hands and slow reaction times.  When we set out to create a similar action-oriented—but also character-driven—toy for Little People, we needed to figure out how to slow down the experience, without sacrificing the action. Through several rounds of prototyping, we built out Klip Klops, leveraging a very simple mechanism that allowed princesses on ponies to teeter back and forth down a ridged downward track. By centering  the “clip clop” sounds of the hooves and building out a multi-story castle setting where the princesses and their steeds would live, we created opportunities for kids to enjoy the intentionality of the movement and built in the space for layered storytelling, allowing little kids to practice multiple development skills at once.

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Navigating your own toy design journey, or trying to get your team at work to stretch its imagination? Get in touch at helloplaylab@ideo.com. We’d love to collaborate.

Almost a decade ago, when we were all exploring VR of the early aughts, Mattel set out to redesign its classic View-Master as an affordable VR headset for a new generation of kids.

Wagashi is a traditional Japanese dessert considered to embody a microcosm of time, space, and nature, typically made of agar, water, and sugar. In this coffee shop, each dessert features a main ingredient—berries, citrus, chocolate—that determines its primary flavor, with an added twist: the addition of a layer of coffee, which corresponds to the carbon footprint associated with producing this main ingredient. The higher the carbon footprint, the higher the level of coffee in the dessert, and the more bitter it tastes. You can see and taste it.

Making Data Feel Real

This is the concept behind DataWagashi, the design-tech project I collaborated on with Boston-based design technologist Iyang Huang. DataWagashi invites people to experience the future of data communication by bringing climate data to life through all the senses. We go beyond traditional visuals by incorporating taste, smell, texture, and physical interaction, expanding the vocabulary for how we understand and interact with data. With DataWagashi, data transforms from numbers on a screen to a vivd and engaging multisensory journey.

Fighting Data Fatigue

In today's world, the constant doom and gloom surrounding climate change can make it feel overwhelming and disconnected from our daily lives. The complexity of climate data, which is often presented through numbers, charts, and preaching, only adds to this detachment, making the information hard to relate to our senses and emotions. We wanted to find a new, better way to raise awareness about these important issues, and make data communication more intuitive, enjoyable, and fun. So we turned to food, a universally-loved and relatable medium, to make complex environmental data more accessible, foster empathy, and empower people to make better choices. But food is just one of many creative media we can use to overcome data fatigue and craft engaging data stories through design.

One way we can think about changing how we present information is by transforming text-based information into something capable of carrying multimodal information—like edible objects, but also, sounds, lights, responsive wearables, and much more. Instead of just making a deck that tells people there has been a 20-degree sea water temperature increase, why not design a way for people to directly feel the difference? Imagine experiencing wildfires not through statistics, but by tasting the severity of raging flames through a range of spicy dishes, hearing the before and after of dwindling forest chorus, and touching the roughness of the scorched grass. By physicalizing data, we translate numbers back into experiences that can be seen, touched, and felt, connecting more deeply with the real world.

Introducing the Phygital Experience

The integration of Generative AI into storytelling introduces a new blend across digital and physical platforms, enabling us to transform large-scale datasets into tangible Wagashi forms. Setting up a few lines of mapping rules allows the data—whether static, real-time, or customized by user input—to dynamically manifest across multiple formats such as graphics, text, sound, and food, bridging the gap between digital information and physical entities. These entities could be data-driven recipes, playlists that shift with real-time data trends, algorithmically-woven textiles, ambience gadgets that adapt to environmental changes, and vending machines that dispense data-inspired poems on bamboo paper, making abstract data interactively tangible. 

This approach opens up various real-world use cases and applications in everyday lives, from creating customized dessert recipes and generating climate sonatas to sending personalized gift packages.

The importance of data empathy

DataWagashi is also about democratizing data. By turning data into physical, sensory experiences, we can break down information barriers, ensuring that people with varying data literacy levels can grasp the complex concepts and join in on conversations about climate change and environmental impact. This redesign of data presentation fosters understanding among diverse groups across ages, cultures, and professional training, creating a fair environment for dialogue and learning, and making the intricate world of data an experience open to all.

Soon, you might walk into your favorite cafe and order desserts not by ingredients, but by picking up a menu called "Biodiversity Forecast in 60 years," and choosing from "Rainforest," "Desert," or "Ocean." Maybe you’ll have a weekly smoothie subscription that alters its formula based on a synthesis of the average air quality (climate data) and how active you are (personal health tracking data). The next day, a box of unique foods arrives, driven by your data choices, offering delightful surprises. This not only gives you a tasty treat but also connects you to a bigger data story, inspiring awareness and action.

Heading to SXSW 2024? Meet up with us at DataWagashi: Feeling Climate Data through New Design Medium, and learn more about how we can make the data tangible in the most flavorful way for a better climate future.

Picture this: You walk into your favorite coffee shop, check out the desserts, and choose which one to order based on its carbon footprint—just by looking at the confection itself.

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We interviewed dozens of leaders of innovation, design, and new product teams at multibillion-dollar companies in search of clues as to where the trouble starts: When funding was cut?  When teams were reassigned? When groups were dissolved? 

Our research uncovered five reasons that innovation portfolios fail—and tips for making sure it doesn’t happen at your company.

#1 The black hole of undefined strategy

In work we did with a Fortune 500 shipping company several years ago, executives decided that the company needed a global innovation team. They committed millions of dollars, hired a startup leader, and assigned 25 people to the team. The startup founder built them a venture based on a new technology that tracks packages. In its first year, that innovation alone made the shipping company tens of millions of dollars.

But when review time came around, executives told the leader they were dissatisfied. Why hadn’t this team done anything to evolve the company’s core offerings? Why had they broken rules inside the company? They fired the leader, even though the higher-ups hadn’t articulated to the team—or to each other—what successful innovation looked like. 

Often, this misdirect starts with undefined strategy at the top. Innovation strategy requires a different type of conversation: less focused on big-picture goals; more focused on strategic planning, like how to invest and pursue goals over the next year. It starts with this question: What are the outcomes we want from this work?

#2 The peril of orphaned innovations

All too often, a company creates an innovation team, but doesn’t connect it with the company’s core business. That can create an innovation orphanage: ideas developed in isolation that lack the necessary resources and support to be successful. 

We witnessed this on a project with a large automotive company. It had recently acquired a startup that offered private work shuttles.  They brought IDEO in to lead an innovation lab around new product possibilities. Together, we built a new venture: a commute benefit that the company could sell to employers to better leverage the startup’s fleet of private work shuttles. But after six months of generating revenue and trying to sell it to the broader startup, it still wasn’t in their pipeline.

The problem was misaligned incentives: The CEO of the automotive company had tasked the innovation to a standalone team, without bringing in the decision makers at the startup. When there’s no ownership or investment from the departments that the innovation is meant to serve, great ideas go nowhere. Instead, leaders need to create a process for identifying and nurturing promising innovations, and define who owns the outcomes and makes implementation decisions before the innovation even begins. 

#3 The risk of the wrong talent

By definition, innovation requires new approaches. It often requires new talent, too. Think of the classic example of IBM, often taught by professors Charles O’Reilly and Michael Tushman in their work on ambidextrous organizations. Throughout the 1980s and 1990s, the technology giant would invest in new innovation efforts, like the personal computer, but the company was never able to commercialize or scale the product. IBM’s business leaders didn’t have an entrepreneurial mindset—the company needed talent who had experience taking big swings.

We recently saw this play out at a food manufacturing company. They wanted to try an agile approach to developing new products and tasked a team of operators from the core business to make it happen. The team developed a new breakfast product, which tested well with consumers. But they didn’t feel confident enough to advance to piloting it without further data. Why? The internal team had never launched a new product from scratch, and they were terrified of screwing up. 

To avoid the talent trap, it helps to think about three different roles in a workplace: explorers, scalers, and optimizers (with credit to Bud Caddell and Simon Wardley). Optimizers make up about 90 percent of employees; they drive growth and improve operations across the core of an established business. Explorers work in departments like R&D and product development, and are good at spotting new opportunities and developing ideas. Scalers iterate on ideas until they find the right product-market fit. All three roles are essential, but shine at different parts of the innovation process. Explorers work best within innovation teams, until they can pass off an idea to scalers for development; scalers can then institute new processes and tools for optimizers to use within the workplace. 

#4 The troubles of a bad handoff 

When company leaders get excited about an innovation, it can be tempting to go for an ad hoc implementation, rather than moving through clear internal steps. But the wrong handoff can lead to inconsistencies and inefficiencies. The baton gets dropped. That’s why it’s necessary to design a clear innovation process for how to generate, evaluate, and implement ideas. Here’s a guide to the handoff models we see most often—and when to use them:

‍The Owner’s Manual: After months (sometimes years!) of work, an innovation team hands extensive documentation over to a new team, which is meant to execute their vision. But be honest: When is the last time you actually read an owner’s manual cover-to-cover? Exactly. This model can work if the innovation doesn’t need to be directly developed by others (insights from a research group, for example), but it doesn’t work well for a new product, where it can turn into a knowledge dropoff.

The Architect: The future owner of the work embeds with the innovation team. That way, they can share the insights from the development process with the new team. This model works well for industries like consumer packaged goods, where a brand manager is responsible for product development from beginning to end.

The Ambassadors: Members from each stage of the innovation embed throughout the project, ensuring that no learning is lost and each phase of work feeds smoothly into the next. This model also builds an awareness of what downstream teams most need.

The Hive: Each project functions as a microcosm of the business, where multidisciplinary teams tackle a challenge from beginning to end. This is common in accelerators and incubators, since they often set up new organizations as microcosms of a parent company, made up of people from every major function.

#5 The danger of short-term metrics

In our experience, innovation teams often have a three-year lifespan. During the first year, everyone is excited, encouraging the innovation team to swing big. By the second year, company leaders are asking, what are your results so far? By the third year, a lot of the top executives have changed seats, and the new leadership doesn’t see a meaningful effect on their core business, so they decide to shut it down.

It’s a short-sighted move: This kind of work often takes years to show impact on metrics like revenue, loyalty, or customer satisfaction. The labs can still show value in the short-term, though, by demonstrating how the work drives efficiency or changes behavior.

This brings us back to the head of innovation at the shipping company, the one who created a startup that netted millions, but got fired because the team hadn’t evolved the company’s core offerings. To avoid this trap, companies need to establish clear metrics to assess progress over time—the number of prototypes a team develops, experiments they run, employee retention or external reputation. Otherwise, you’re cutting down the tree you planted three years ago, before it even had a chance to bear fruit.

Falling into an innovation trap of your own? We’d love to chat with you about it.

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(Images created with Midjourney)

A few years ago, we led a project to investigate a question: Where does innovation go wrong?

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At a time when everyone was concerned about kids using AI to cheat, they wanted to discover how it could enhance learning and teaching for the better.

While we immersed ourselves in the traditional design process—sketching, interacting with students and teachers, and finding inspiration out in the world—it became clear that understanding the AI that underpinned the product was critical to our success. So we dove into using the underlying technology ourselves.

The data scientist on our team started by constructing a simplified Python version of one of Ethiqly's significant features—structured feedback for teachers to share with students—allowing it to interface with a language learning model (LLM). Then, with the help of software designers, we rebuilt and evolved this proof-of-concept prototype to be a real, usable, multi-featured demo of two of the core interaction loops, so that we could test it in research sessions with students and teachers. 

The demo became an invaluable tool to uncover student and teacher feedback, to test the look and feel of a new product, and to glean the real capabilities of the underlying technology. In creating the demo, we realized the importance of being able to prototype generative AI products as quickly and as collaboratively as possible.

At IDEO, we believe in augmented intelligence—that it’s possible to bring more delight, ease, creativity, and impact to human work through technology, including AI. To do this responsibly, it’s important to bring a multiplicity of perspectives to the design of these tools. By building a lightweight system that allows designers without technical backgrounds to prototype with LLMs, we could bring more voices, eyes, and hands into the AI-driven product design process. We also shortened our time to first prototype from weeks to days. 

ChatGPT: A Tool, Not Just a Trend

Using ChatGPT’s interface can be powerful on its own, but what’s not as well known is that the systems behind it can smooth the process for product development. But for casual users of ChatGPT’s browser or app-based interface, there’s little opportunity to learn about how it works on the back end. It also comes with privacy concerns. It’s clear that more and more of our clients need us to understand firsthand what creating LLM-enabled products feels like, and it’s equally clear that we need to explore how LLMs can push the edges of our own creative process.

So, I designed a simple prototyping interface that shows a little more of the guts behind the chatbox. The goal? To help IDEOers better understand how LLMs, and OpenAI’s APIs in particular, work behind the scenes, building their intuition about what the current spate of AI tools are good at, and what they’re not.  

The prototyper interface also adds convenient features like saving a  conversation state—allowing designers to download and share their conversation history and rewind to earlier states to try out new content—to encourage the development and sharing of useful and delightful patterns. I named the tool GPT Prototyper.

Teaching Through Prototyping

While using GPT Prototyper’s interface doesn’t involve any coding, it does show its users more about the parts and pieces that can be configured to refine and expand OpenAI’s conversational abilities, from the system note (background information that shapes the LLM’s responses), to the temperature (the sampling scheme that controls the randomness of the responses), and even accessing an external service through function calls (commands the LLM can send that connect it to abilities beyond text prediction).

We’ve created comprehensive video tutorials, interactive Q&A sessions, and embedded usage hints within the Prototyper to make these capabilities more understandable to everyone at IDEO. Every designer, irrespective of their technical proficiency, can now contribute to the evolution of intelligence platforms, thereby ushering in a new era of digital product behavior.

If it sounds theoretical—it’s not. We’ve used customized versions of the Prototyper to demonstrate how LLMs can work within product and service concepts for work in industries ranging from finance to consumer goods. 

Since its debut last June, the prototyper has also helped us explore more future-facing ideas, like when we gave a pair of vintage Levi’s jeans a personality and history, letting prospective customers learn about how the jeans were made and where they were worn through conversation. We’ve also used it in service of our ongoing research into Gen Z’s relationship to GenAI.

Having the GPT Prototyper means that teams no longer have to wonder if an interaction is possible–they simply build it and give it a try. 

A Glimpse into Tomorrow

Pushing beyond simple productivity gains and into innovation and creativity requires understanding—at least to some degree—of how LLMs work. Tools like the GPT Prototyper are bringing intentionality and speed to our explorations, helping our clients push farther and faster into new possibilities for growth. The tool is also making it possible for us to explore client work without sharing confidential information with unvetted tools—something both we and our clients care deeply about.

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Want to learn more about creating a tool for your organization? Get in touch.

Last spring, my team and I partnered with Ethiqly, an education startup looking to explore how AI might help students learn how to be better writers.

I help organizations cut through complexity by shaping how they show up, through brand strategy, identity, and storytelling.

Working at the intersection of brand and business, I bring an editorial eye and a bias toward making—turning ideas into tangible experiences that people can understand, trust, and believe in.

My work spans government, healthcare, financial services, media, and consumer goods, from launching Gen Z-focused ventures to building innovation labs and reimagining legacy brands. I relish moments of ambiguity and enjoy translating across teams, perspectives, and priorities to move ideas forward.

I started my career in editorial and digital design, shaping cross-platform experiences and identity systems in publishing and agency environments. That foundation still shapes how I work today: I’m detail-oriented, collaborative, and overreliant on the Oxford comma. I hold a BFA in Visual Communication from the School of the Art Institute of Chicago.

For 25 years, I've asked the same question: Who does this design exclude—and what are we going to do about it?

My work spans human-centered strategy, inclusive design, and qualitative research, with clients ranging from Microsoft, Google, and Verizon to the National Science Foundation, and San Francisco Unified School District.

Before IDEO, I taught elementary school in East Palo Alto and spent a decade doing design work with social service organizations—where I learned firsthand what it costs people when systems are built without them in mind.

I am currently writing User Error, a nonfiction book about digital access and the design decisions behind it. I live in Oakland, California.

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My expertise spans brand, communication, and product design across tech, education, the arts, and social impact.

I believe great work demands both high-level vision and obsessive attention to detail, and only happens through collaboration.

I bring an inclusive, hands-on approach and a deep understanding of business, which enables me to consistently deliver excellence while always asking why.

Before joining IDEO, I worked at the brand firms Pentagram and VSA Partners. I began my career as a designer, leading teams at the School of the Art Institute of Chicago and the Milwaukee Art Museum. I hold an MFA in graphic design from Maryland Institute College of Art and a BFA in communication design from the Milwaukee Institute of Art & Design, and have taught at some of the best design schools in the US.

I am responsible for IDEO’s long-term success in China and working with clients to use design as a tool to enable growth. Specifically, I have helped Chinese companies design holistic brand solutions through the development of their products, communication, services, and innovation teams, and I have helped multinationals expand their presence and influence in China.

I advise global leaders on developing China-led innovation and capabilities.

In over 15 years in IDEO Shanghai, I have worked on projects that use design to elevate the quality of the experience of healthcare products and services, streamline processes that increase productivity, create spaces and programs that promote and enable inclusive communities, and build next generation mobility solutions that are planet-positive.

Before joining IDEO, I worked at Philips Electronics and the Electrolux Group in Italy, the Netherlands, and Singapore on a number of breakthrough commercial products. I am a member of the Young President Organization in Shanghai.