Globally, the European Commission reports, a truckload of textiles heads to landfills or is incinerated every single second.

The fashion industry accounts for some 10 percent of greenhouse gas emissions worldwide.

Less than 1 percent of the materials used to make clothing is recycled, according to a report by the Ellen MacArthur Foundation.

The best way to keep clothes out of a landfill? Don’t make them.

Picture this: Not long ago, it wasn’t unusual for a customer to walk into an H&M store and not be able to find a basic white t-shirt in their size. Why? Like most long-established retail operations, H&M was operating with a push model—placing seasonal bets on what the demand for a given item of clothing might be, locking orders far in advance, and hoping that they were able to sell out. Make a mistake in that kind of model, though, and you can end up with customers unable to find the basics they rely on, or excess inventory you can’t sell. That’s a problem for the business, but for the environment as well—and one that doesn’t fit H&M’s aggressive sustainability goals.

Though H&M had tried to tackle the problem before, the launch of the H&M Group Design Studio, co-created with IDEO, gave the retailer the confidence to go after it again. The team started out by mapping out the complex network of people that make up its supply chain across the globe, meeting with everyone from designers to garment suppliers, logistics managers, and even folks selling the final product in H&M stores. 

They then created an algorithm for more precise ordering, as well as a tool that provides a shared view of information. Instead of placing orders, the new automated flow—dubbed “Cruise Control"—allows staff to work with a demand forecast that gives them more time to focus on customer-centric operations, like providing guidance and inspiration. It also makes it easier for H&M to follow the demands of the market, and place much more accurate bets on what consumers will want, when. Already, H&M has significantly increased sales while cutting excess inventory—a result that improves its bottom line, as well as its environmental impact.

Estimates project that by 2030, global apparel consumption will hit 102 million tons.

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22%

reduction in stock during a pilot program

34%

increase in sales during a pilot program

To foster creative projects that spoke to the needs of local communities and environments, the BSA began to engage its members in collaborative, user-led design. The organization launched its first-ever innovation challenge, putting out a call for all members to pitch their ideas for projects in the built environment.

The BSA expected those pitches to have dollar signs attached. To the organizer’s surprise, only one asked for funding. The rest requested less tangible, but equally meaningful support: advice, connections, specific expertise. Those are resources that the BSA has aplenty, but hadn’t learned how to leverage well.

From that first go at an innovation challenge, the BSA learned how to better support its members. It also learned that to lead with purpose and make strategic choices, one must develop the confidence to say no. Instead of spreading itself thin across many projects, the organization decided to take small steps, focusing on one initiative at a time, so that it can deliver focused impact and stay true to its evolving mission.

With 36% of global energy going to buildings and 8% of global emissions caused by cement alone, the architectural community is inextricably intertwined with both the causes and solutions related to climate change.

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According to a survey conducted by the AIA, the architecture profession in the US is less diverse than the population as a whole. This lack of diversity can contribute to a disconnect between architects and the communities they serve.

31

submissions received from innovators in the Boston region working on equity and sustainability challenges

5

innovation teams invited to pitch ideas

The resources that NYU students needed were organized by administrative department, and buried on disparate websites and calendars. But students don’t think in terms of departments—they just need to know where their classes are.

All of this became patently clear as IDEO shadowed students. Team members visited classrooms, walked with them through their days, and hosted pop-ups in highly trafficked areas to get ideas from passersby. That helped the team develop a common understanding of the overall student journey and grounded employees in the key moments that can either make or break a student’s experience. Visualizing their journey helped departments gain a shared understanding of the fractured communications challenge and develop possible solutions.

To synthesize those insights, we formed cross-functional action learning groups, challenging existing practices at the university and coming up with new ways of working. Participants came from a diverse set of departments, including enrollment management, student affairs, marketing and communications, IT, global inclusion, student services, the provost’s office, digital communications, and more. The cohorts sketched early hypotheses and got feedback from faculty, administrators, and students from all of NYU's undergraduate schools to refine initial concepts.

Collaborating with students gave staff a first-hand look at what students were struggling with and a way to engage students directly in addressing those challenges. Just as importantly, there was an overall culture shift at NYU: Administrators started with questions instead of agendas, came together around a table, and reached beyond their job descriptions to meet the needs of students.

First-year students reported receiving hundreds of paper forms, and email from more than 70 unique senders.

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NYU needed to offer students the right resources at the right time—and collaborate to serve them as a unified administration.

New services

in-production include centralized calendars, dynamic campus mapping, and customized notifications

Design-thinking cohorts

now support the student experience

Diversity alone isn’t enough—in marketing or any other facet of business. Today’s brands must authentically engage with and create the conditions for co-design with existing communities.

That sort of deep, meaningful engagement with customers doesn’t happen over Instagram. It requires a playbook, a prototype, and a healthy amount of trust. So, IDEO worked with Athleta and Gap to tap into the wisdom of a council of women who represent intersectional identities and lived experiences. The council surfaced powerful insights for the brand, like the fact that active women don’t need a brand to empower them—they already feel powerful.

After only a few weeks, Athleta experienced the difference between research and a truly reciprocal relationship. The way their brand engages with communities is adding depth, understanding, and authenticity to Athleta’s content, products, and experiences. And women can feel the difference.

76% of US adults say that the media promotes an unattainable body image for women.

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Fewer than 1 in 10 businesses review for inclusion as part of product design and marketing campaigns.

>2X

user growth in 2022

13,000+

Athleta WellPro well-being providers active on the platform

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If you missed the first installment of our Gen Z + Gen AI prototyping series, you can catch up here.

“I could see myself starting up a business someday,” one high-school senior told us. “So say I wanted to make visuals, or ads for that—I'll want to have an AI guide me through the creative process.”

To find out what that really means in practice, we prototyped a set of creative AI tools and asked a cohort of young people between 13 and 24 to test them in their own work and lives. 

AI Creator vs. AI Collaborator

We built two contrasting prototype experiences to test the breadth of roles, capabilities, and personalities that a creative AI might have. On one end of this spectrum, we have an AI that is designed around speed and efficiency. Its interface is meant to feel highly-optimized to get you the best, most suitable output possible in minimal time.

On the other end, we created a hyper-collaborative creative partner more focused on helping you express your own unique style. This AI can not only create content, but share inspiration—helping Gen Zs discover new styles, see what’s trending, narrow down likes and dislikes, and gain insight into their own personal tastes.

We then customized our prototypes to fit each participant’s life context.

Exploring the values behind our designs 

In testing our range of prototypes, we found that no AI creative tool will work for everyone in every moment. Gen Zs have a wide spectrum of values when it comes to what they want from creative tools—some value speed and efficiency, while others value deeper collaboration and personal expression, and their values may fluctuate as they go from one context to another.

For quick, everyday creative needs—efficiency is key.

We heard from Gen Zs whose lives are extremely busy—from managing social media for multiple school groups to starting and running their own businesses, and keeping up with school, family, and social circles. There isn’t always a lot of time or energy left over for lengthy creative processes. "Social media doesn't feel meaningful to me, only the end goal,” a college freshman told us. “So I love that this AI can help me reach that end goal faster.”

To design for users like this one, the challenge lies in getting to a satisfying creative output faster, in minimum time. The distance between prompt and output should be short, and UX should offer visual templates and clear parameters that help people to create quickly in a well-defined style.

For creators, aspiring professionals, and artists, AI should show up as a more nuanced collaborator—offering tools for inspiration, personal expression, and a greater depth of creative control.

On the flip side, we heard from Gen Zs who aspire to create original and expressive work. "I think the ability to re-edit to make it have a more human touch and connection makes it a good tool. I want a good combination of AI and human—in graphic design at least,” Cole, one of our Gen Z collaborators, told us.

For Gen Zs who value craft and personal expression, the distance between prompt and output needs to be longer. Future collaborative AI interfaces will need to allow for more rounds of feedback, create more opportunities for humans to give direction, and be capable of working with multi-modal inputs—such as reference images, sketches, font files, CAD files, and more. These more collaborative AI experiences should still offer tools for humans to create and customize by hand. The challenge here is not to replace human craft and creativity, but to design interfaces that help AI augment our creativity to deliver output nuanced enough to match the richness of personal expression that Gen Zs want, alongside tools for them to add their unique vibe by hand, too. 

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An AI-enabled creative future 

So what does all this mean for the future of AI? AI experiences themselves should continuously work to establish user intent, and to understand what good means in different moments—does a user need a quick solution, or a creative partner? As a rule, designers should offer multiple options for how their AI shows up in terms of tone, role, capabilities, and suggestions to users, and put in the work to continually listen, discover, and elevate the most relevant options for their audience. 

Creativity is just one of the many spaces where we are listening, discovering, and experimenting with how to prototype future AI experiences; we are also exploring how AI should show up in education, mental health, work, social media, and more. Stay tuned for our next piece, which dives into how Gen Z feels about AI personal assistants entering the group chat.

Parts of the images in this article were created/altered using generative AI.

When we first started exploring the possibilities of creative AI products with a group of Gen Zs, they were clear about what they want: tools that scaffold the creative process, lower the barriers to entry, and connect creative communities.

To monitor how use cases have shifted over time, we developed a social listening tool to scrape AI hashtags on TikTok, creating a visualization of conversations and communities.

In the spring of 2023, much of the positive sentiment around AI was associated with productivity-related hashtags—activities like homework and writing. By October, AI music became its own distinct community, and hashtags for AI fanfiction, AI anime, and memes grew. Our most recent scrape in early 2024 showed us that AI is shifting from a predominantly solo activity to one centered on community. Hashtags like #aiart and #aiartcommunity are growing in size and in connections, suggesting that AI-generated art isn’t created in a silo—people are sharing their experiences.

In just a matter of months, Gen Zs have evolved their use cases to align with their priorities—sharing their passions and connecting with communities in playful and imaginative ways.

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AI companies are also moving fast. The race to create the most impressive and jaw-dropping AI products is adding frenetic urgency, and companies are spending millions of dollars on development resources, then quick-launching new products with the hopes that they will be well received. Often, launch is the first time companies are able to test out their products in the real world. 

We are seeing rapid technological progress, but also backlash against irresponsible designs and technologies that have real potential to clash with human values and cause harm. We believe AI has potential for revolutionary experiences and capabilities that improve the ways we live, connect, and play. But we also believe this future requires a foundation of trust and responsible design. 

To that end, we are experimenting with a different way of developing AI products—one that doesn’t compromise speed but also aligns with human values. By designing experiential prototypes that mimic real-world scenarios, we can create tight feedback loops that get us better user feedback, sooner. These prototypes are run in contained settings where we can look for unintended consequences. (Picture two people with paper scripts, role-playing what it feels like to interact with AI in a particular scenario.) We don't need to build the technology needed for the experience to work—our first step is to test for emotional value. That way, we focus our development resources on building the most impactful and responsible products and experiences possible.

In an earlier phase of our research, we used the results of our social listening experiments to work directly with members of Gen Z between the age of 13-24,  talking through potential product concepts and gathering their reactions. This time, we’re going deeper, prototyping products that have AI taking on different personalities and roles with a group of Gen Zs who are coming of age, gaining life skills, and forming their sense of identity as AI is also taking shape in our society. With their help, we’re learning how to build future AI experiences that center their values and needs. 

Growing up with social media, members of this generation have already felt the potential impact irresponsible technologies can have on their mental health and relationships, and they have a critical eye for both opportunity and responsibility. While they are strong proponents of the products and brands that they believe in, they're also not shy about making their voices heard when products clash with their values systems.  

In this series, we will put eight AI prototypes to the test. By leaning into immersive research tools like experiential testing and imaginative playtesting, we are focusing our learning objective on measuring how these young people feel when they are using AI products, and how the products would impact their perception of themselves and their relationships. For us, understanding the value of the product in the context of the user’s life, their value systems, and relationships is a crucial step that helps us identify the features and technical capabilities that are worth investing in. Join us as we dive into new prototyping methods for designing and testing the edges of what future users really want from AI.

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Parts of the images in this article were created/altered using generative AI.

The ways Gen Z is using AI are evolving almost as fast as the technology itself.

 It’s a way to optimise and improve inefficient and wasteful processes and accelerate emissions compliance—and it’s a great one. But when we leverage AI to shape demand for sustainable solutions, it's also an incredible collaborator.

After all, design is about integrating perspectives, and doing it in a systemic, inclusive way. AI can give us the ability to make our eyes and ears go further while managing exponential complexity. Paradoxically, it can even make us more human centred by making it feasible to access and include more user, employee, and community perspectives. 

At Economist Impact’s recent Sustainability Week in London, we discussed how this approach can succeed, but only when CEOs see sustainability and innovation as one interrelated competitive advantage—and bring them together with a shared remit, adequate bandwidth, and complementary skills. AI can then act as a powerful accelerator, helping to create solutions that meet climate commitments and business objectives. 

Unlocking nature’s perspective with data

This was the case in our work with H&M, which allowed us to delve into its data warehouse as part of its aggressive pursuit to be climate positive by 2030. The fashion giant was dealing with a problem that so many clothing manufacturers face: Traditional supply chain models make it very hard to predict the demand for a specific item of clothing several months in the future. Siloed teams along a supply chain made solving that problem even more complex.

By leveraging machine learning, we were able to incorporate the perspectives and needs of those teams and create an algorithm that could better predict demand and shorten the interval between sales and production. H&M didn’t just reduce excess inventory (and therefore waste), but also better anticipated which products might sell out. The result: In a pilot programme, which has since been scaled more widely, the company improved sales of specific lines by a third while reducing stock by a fifth, a change that was better for its bottom line, and the environment. 

Nature doesn’t appear on balance sheets, and yet most businesses depend on it.

With advances in AI, gains like these can come faster and be more complete—particularly if we take that kind of approach a step further and use nature metrics to train AI models. One of the best ways to approach this is to think of nature as a critical part of your infrastructure and start measuring it as you would any other element. Nature doesn’t appear on balance sheets, and yet most businesses depend on it. In most cases, that data—metrics around land use, water regeneration, forestation, net biodiversity gain, etc.—is available, but simply isn’t being collected and put to use. That means one of the chief perspectives we should consider, that of nature, isn’t being voiced. AI can provide the vocal cords.

Tequila companies, for instance, don't include information about the health of bat populations in their investor reports. But as bat conservationists will tell you, without bats to pollinate agave, there's no tequila. Imagine how bat conservation and food security would improve if tequila manufacturers started tracking bats’ habitat loss and used AI to spot trends, monitor for diseases, or determine effective and cost-efficient conservation strategies.

Solve for desirability down the chain

The data that powers AI is crucial, but it’s just part of the equation. The quality of the output depends just as much on the quality of the prompt. AI can act as a growth engine if we ask it to do so: to behave as a collaborator and surface the needs of more stakeholders in order to help designers create innovative, desirable products with better user experiences. And amid the race to net zero, desirability is key. 

Mature technologies like electric vehicles (EVs) and photovoltaics (PVs) can help us curb emissions, but their “hockey sticks” are already showing signs of fatigue very early on in the race. The European EV market was almost flat in 2023, and PVs’ growth is forecasted to slow in 2024. What is going on?

We have been pushing the supply side—tech and regulation—without paying enough attention to the desirability side. PVs are still more expensive at the moment of purchase and cumbersome to install and use. It remains much easier to just pay your monthly electric bill and let the energy company worry about powering your home.

Ease was a major consideration in our work with Sage, a multinational accounting and business software company. Its visionary Chief Sustainability Officer and innovation team knew that the small and medium enterprises (SMEs) it serves often don’t know how they’re going to reach net zero, and lack the resources to do so. Yet, in the UK alone, they account for about 50 percent of business emissions. Together, we developed Sage Earth, an AI-powered platform that uses Sage’s deep accounting insights to calculate its customers’ emissions, both direct and indirect, easing their transition to net zero.

To achieve scale, we need people to adopt green products because they are better, easier, and more exciting, not because they are green.

To achieve scale, we need people to buy green products because they are better, easier, and more exciting, not because they are green. We need to be more demanding about the quality of the sustainable products and submit them to the same standards as any other product. AI can help us on that journey.

Recently, a fashion retailer described to us the challenges of using recycled cotton, which has a rougher texture. Trying to make T-shirts that maintain the same level of softness as those made from first-use cotton is impossible. Gen AI can use data about existing materials to formulate new ones, consider how to make them more regenerative, determine their best applications, and explore which users those products will most resonate with. 

And there are many more users to design for in a regenerative world. To make our world more circular, we must consider all the humans that follow the first user: the second user, the person who will repair the item, the person who will redistribute it, the third user. Everyone has to desire the resulting product; otherwise, it ends up in a landfill. Thankfully, AI can help us empathise more systemically, not just with the first customer of a product and the subsequent ones, but also with the communities that will be at the receiving end of those products. 

AI can help us empathise more systemically, not just with the first customer of a product and the subsequent ones, but also with the communities that will be at the receiving end of those products.

Think about the design for a new circular appliance, for instance. You aren’t always able to factor in the representation of local repair shops, local recyclers, and the whole ecosystem that will have to deal with the consequences of a new product landing in their community.

Now we can train GPTs that amplify previously-overlooked viewpoints, ask questions, and offer critique to the designers in ways that wouldn't be available otherwise. It provides us with more valuable real-world views and constraints and reduces the number of assumptions we have to make. 

AI shouldn’t substitute for human intelligence but it can do some of the heavy lifting: giving us artificial patience, artificial thoroughness, artificial persistence, and artificial long perspective.

AI can help us capture more of what it is to be human by feeding all the nuances, needs, desires, and concerns that different communities have back to us. It can help us find insights in more of the data nature holds. It can bust through our limitations and complement our shortcomings. AI shouldn’t substitute for human intelligence, but it can do some of the heavy lifting: giving us artificial patience, artificial thoroughness, artificial persistence, and artificial long perspective. It can help us ensure the best choice is the easiest one to make, helping us navigate to a crucial, often overlooked lever in the climate fight: desirability.

‍We discussed “How Organisations Can Use Artificial Intelligence to Boost Sustainability” as part of a panel at Economist Impact’s 9th annual Sustainability Week in London. This piece captures some of what was discussed and our broader thoughts on the subject.

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Parts of the images in this article were created/altered using generative AI.

Often, when we think about how AI can help us solve problems, we think of it as an efficiency driver.

Think back: Starting from the camaraderie of chat rooms in the '90s which created space for gay men to safely build community, to the social media boom of the mid-’00s that redefined global interactions, we've witnessed seismic shifts in how we connect with others and explore our identities. The proliferation of smartphones further catalyzed this transformation, embedding digital interactions into the fabric of our daily lives and birthing the attention economy that dominates today's tech landscape. Influencer culture cemented larger narratives that shape trends, fashion, and societal norms.The 2020s have centered Web3, XR, and AI in the global techno-sphere, creating new mediums for us to convene with others, rethink the design patterns of the past, and creatively express ourselves. 

As designers, we are often tasked with navigating the complex interplay between individuality and collectivity. The question becomes: How can we leverage technology to enhance personal expression while fostering a rich, diverse cultural landscape premised on care, understanding, and communal values? This challenge is not just about creating functional designs, but about understanding the broader implications of our work on the cultural ecosystem.

The good news? Technology is entirely made up, by humans, and all of it can be evolved.

When it’s done well

The positive aspects of this convergence are manifold. The spread of digital tools and platforms has led to an unprecedented explosion of creativity. Now, more than ever, global voices can find and scale messages, meshing our shared cultural fabric. 

Projects like Carne y Arena, a virtual reality installation that immerses participants in the harrowing journey of refugees crossing the US-Mexico border, exemplify the power of technologies like XR to foster understanding, transcending physical and cultural boundaries to tap into the human condition. In the installation, you take off your shoes, feel wind blowing against your skin, and then find yourself in the 360 sight, sound, and touch of the experience, thanks to VR and a body pack. 

As the director, Alejandro Iñárritu, explains, "My intention was to experiment with VR technology to explore the human condition in an attempt to break the dictatorship of the frame—within which things are just observed—and claim the space to allow the visitor to go through a direct experience walking in the immigrants' feet, under their skin, and into their hearts.”

4D experiences like Carne y Arena offer new, visceral ways of activating senses and emotional tones that we are far less able to access in 2D. VR is an incredible storytelling mechanism, and it can be an incredible tool anywhere we are designing for human experiences—like policy implications in government, or caregving in hospitals. Projects like this underscore the potential for design to bridge individual and collective experiences in meaningful ways.

Similarly, during Goliath: Playing With Reality, I immediately felt like every school curriculum should be filled with VR experiences. Through this VR-enabled, animated storyline, we delve into the life of Goliath, a person experiencing schizophrenia. Goliath's narrative highlights years of seclusion in psychiatric facilities and his journey toward finding community in online multiplayer games. The experience invites viewers into his mental world, showcasing the significant role digital communities play in fostering friendships and support, often beyond their initial design intent.

Project Common Voice by Mozilla stands as a beacon of how AI can be harnessed for cultural preservation. At its core, this project is a crowd-sourced database that gathers voice recordings from people around the world, aiming to share voice recognition technologies widely. By encouraging contributions in a multitude of languages, dialects, and accents, Common Voice plays a crucial role in safeguarding linguistic diversity. This effort not only supports the development of more inclusive voice recognition systems that can understand and respond to a broad spectrum of human voices, but also illustrates the capability of technology to support preservation of languages and dialects. In the broader context of design and technology's impact on culture, Project Common Voice exemplifies a commitment to using AI to respect cultural and linguistic diversity, thereby enriching the collective cultural landscape.

As a design tool, Common Voice pushed me to reconsider how AI can be used to design for inclusion at scale. The ability to plug in a service like this means that products can rapidly support more users in more contexts, removing some of the barriers and gatekeeping in many of our existing design paradigms for technology.

And as a final example: Someone close to me has long-term depression and anxiety. She found major collaborative iPhone games, like Clash of Clans, are a way to playfully connect with new people. For her, those friendships moved from online to real life, for life. She and her friends started to travel together—she even dated one for a while. Previously isolated, she ended up moving across the world, from the US to Europe, to live near her new friends. Her life has shifted for the better. She’s healthier, happier, and more connected in real life, as well as online.

As designers, we need to remember that the platforms that we design will be used in many ways outside of our intentions–for better and for worse. In my work at IDEO, I pay attention to how people make what we design their own; often, I fold those use cases in as the real value propositions, even if they are outside of the vision we start with as designers.

The flip side

The rapid integration of individual contributions into the collective domain has also caused irreparable damage. The accelerated pace at which personal expressions become part of the cultural lexicon compromises the depth and authenticity of cultural evolution. The risk of a homogenized, polarized, and defaulted monoculture, shaped by trends, algorithms, and the endless dopamine loops they feed, rather than organic self-understanding and cultural diversity, means that design needs to take on new values. The potential of powerful technologies to be used as surveillance arms means we need to put extra care and intention in how and what we build. The spectrum of ethical issues and social needs invite us to consider how we might use the mediums that come next–AI, XR, robotics, etc.–to preserve the richness of our personal, cultural, and social perspectives in a fast-paced digital world. That’s an opportunity for design.

As designers, we have a broader responsibility to the cultural zeitgeist. We need to advocate for designs that not only resonate on a personal level, but also contribute positively to the collective narrative. We are shaping the levers that culture will build and flow upon, and that’s a major responsibility. This dual focus on the individual and the collective calls for a nuanced approach to design, one that balances innovation with care, and personal expression with cultural nuance.

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Parts of the images in this article were created/altered using generative AI.

Over the past 30 years, technology has converged individual creativity with our collective cultural experience, reshaping our personal realms and redefining the broader cultural tapestry in which we all participate.

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.