April 2, 2024
6 min

Clara Kliman-Silver: AI & design: imagining the future of UX

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In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:

  • With enthusiasm for how they can use it to make their jobs easier
  • With skepticism over how reliable it is, or even fear that it could replace their jobs

Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.

Clara’s background 

Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.

In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.

Contact Details:

You can find Clara in LinkedIn or on Twitter @cklimansilver

What role should artificial intelligence play in UX design process? 🤔

Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.

As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.

Access for all 🦾

There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.

For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason. 

Research and testing 🔬

Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:

  1. Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems. 
  2. Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.

The design partnership 🤝🏽

Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application. 

Why it matters 💡

AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.

Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:

  • Adherence is about how AI helps designers follow best practice
  • Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible

The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.

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Optimal vs. UserTesting: A Modern, Streamlined Platform or a Complex Enterprise Suite

The user research landscape has evolved significantly in recent years, but not all platforms have adapted at the same pace. UserTesting for example, despite being one of the largest players in the market, still operates on legacy infrastructure with outdated pricing models that no longer meet the evolving needs of mature UX, design and product teams. More and more we see enterprises choosing platforms like Optimal, because we represent the next generation of user research and insight platforms: ones that are purpose-built for modern teams that are prioritizing agility, insight quality, and value.

What are the biggest differences between Optimal and UserTesting?

Cost

Optimal has Transparent Pricing: Optimal offers flat-rate pricing without per-seat fees or session units, enabling teams to scale research sustainably. Our transparent pricing eliminates budget surprises and enables predictable research ops planning.

UserTesting is Expensive: In contrast, UserTesting has very high per user fees annually plus additional session-based fees, creating unpredictable costs that escalate the more research your team does. This means that teams often face budget surprises when conducting longer studies or more frequent research.

Return on Investment

The Best Value in the Market: Optimal's straightforward pricing and comprehensive feature set deliver measurable ROI. We offer 90% of the features that UserTesting provides at 10% of the price.

Justifying the Cost of UserTesting: UserTesting's high costs and complex pricing structure make it hard to prove the ROI, particularly for teams conducting frequent research or extended studies that trigger additional session fees.

Technology Evolution

Optimal is Purpose-Built for Modern Research: Optimal has invested heavily over the last few years in features for contemporary research needs, including AI-powered analysis and automation capabilities. Our new Interviews tool exemplifies this innovation, transforming hours of manual video analysis into automated, AI-powered insights that surface key themes, generate highlight reels, and produce timestamped transcripts in a fraction of the time.

UserTesting is Struggling to Modernize: UserTesting's platform shows signs of aging infrastructure, with slower performance and difficulty integrating modern research methodologies. Their technology advancement has lagged behind industry innovation.

Platform Integration

Built by Researchers for Researchers: Optimal has built from the ground up a single, cohesive platform without the complexity of merged acquisitions, ensuring consistent user experience and seamless workflow integration.

UserZoom Integration Challenges: UserTesting's acquisition of UserZoom has created platform challenges that continue to impact user experience. UserTesting customers report confusion navigating between legacy systems and inconsistent feature availability and quality.

Participant Panel Quality

Flexibility = Quality: Optimal prioritizes flexibility for our users, allowing our customers to bring their own participants for free or use our high-quality panels, with over 100+ million verified participants across 150+ countries who meet strict quality standards.

Poor Quality, In-House Panel: UserTesting's massive scale has led to participant quality issues, with researchers reporting difficulty finding high-quality participants for specialized research needs and inconsistent participant engagement.

Customer Support Experience

Agile, Personal Support: At Optimal we pride ourselves on our fast, human support with dedicated account management and direct access to product teams, ensuring fast and personalized support.

Impersonal, Enterprise Support: In contrast, users report that UserTesting's large organizational structure creates slower support cycles, outsourced customer service, and reduced responsiveness to individual customer needs.

The Future of User Research Platforms

The future of user research platforms is here, and smart teams are re-evaluating their platform needs to reflect that future state. What was once a fragmented landscape of basic testing tools and legacy systems has evolved into one where comprehensive user insight platforms are now the preferred solution. Today's UX, product and design teams need platforms that have evolved to include:

  • Advanced Analytics: AI-powered analysis that transforms data into actionable insights
  • Flexible Recruitment: Options for both BYO, panel and custom participant recruitment
  • Transparent Pricing: Predictable costs that scale with your needs
  • Responsive Development: Platforms that evolve based on user feedback and industry trends

Platforms Need to Evolve for Modern Research Needs

When selecting a vendor, teams need to choose a platform with the functionality that their teams need now but also one that will also grow with the needs of your team in the future. Scalable, adaptable platforms enable research teams to:

  • Scale Efficiently: Grow research activities without exponential cost increaeses
  • Embrace Innovation: Integrate new research methodologies and analysis techniques as well as emerging tools like AI 
  • Maintain Standards: Ensure consistent participant, data and tool quality as the platform evolves
  • Stay Responsive: Adapt to changing business needs and market conditions

The key is choosing a platform that continues to evolve rather than one constrained by outdated infrastructure and complex, legacy pricing models.

Ready to see how leading brands including Lego, Netflix and Nike achieve better research outcomes? Experience how Optimal's platform delivers user insights that adapt to your team's growing needs.

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How to conduct a user interview

Few UX research techniques can surpass the user interview for the simple fact that you can gain a number of in-depth insights by speaking to just a handful of people. Yes, the prospect of sitting down in front of your customers can be a daunting one, but you’ll gain a level of insight and detail that really is tough to beat.

This research method is popular for a reason – it’s extremely flexible and can deliver deep, meaningful results in a relatively short amount of time.

We’ve put together this article for both user interview newbies and old hands alike. Our intention is to give you a guide that you can refer back to so you can make sure you're getting the most out of this technique. Of course, feel free to leave a comment if you think there’s something else we should add.

What is a user interview?

User interviews are a technique you can use to capture qualitative information from your customers and other people you’re interested in learning from. For example, you may want to interview a group of retirees before developing a new product aimed at their market.

User interviews usually follow the format of a guided conversation, diving deep into a particular topic. While sometimes you may have some predefined questions or topics to cover, the focus of your interviews can change depending on what you learn along the way.

Given the format, user interviews can help you answer any number of questions, such as:

  • How do people currently shop online? Are there any products they would never consider purchasing this way?
  • How do people feel about using meal delivery services? What stops them from trying them out?
  • How do ride sharing drivers figure out which app to use when they’re about to start a shift?

It’s important to remember that user interviews are all about people's perception of something, not usability. What this means in practical terms is that you shouldn’t go into a user interview expecting to find out how they navigate through a particular app, product or website. Those are answers you can gain through usability testing.

When should you interview your users?

Now that we have an understanding of what user interviews are and the types of questions this method can help you answer, when should you do them? As this method will give you insights into why people think the way they do, what they think is important and any suggestions they have, they’re mostly useful in the discovery stages of the design process when you're trying to understand the problem space.

You may want to run a series of user interviews at the start of a project in order to inform the design process. Interviews with users can help you to create detailed personas, generate feature ideas based on real user needs and set priorities. Looked at another way, doesn’t it seem like an unnecessary risk not to talk to your users before building something for them?

Plan your research

Before sitting down and writing your user interview, you need to figure out your research question. This is the primary reason for running your user interviews – your ‘north star’. It’s also a good idea to engage with your stakeholders when trying to figure this question out as they’ll be able to give you useful insights and feedback.

A strong research question will help you to create interview questions that are aligned and give you a clear goal. The key thing is to make sure that it’s a strong, concise goal that relates to specific user behaviors. You don’t want to start planning for your interview with a research question like “How do customers use our mobile app”. It’s far too broad to direct your interview planning.

Write your questions

Now it’s time to write your user interview questions. If you’ve taken the time to engage with stakeholders and you’ve created a solid research question, this step should be relatively straightforward.

Here are a few things to focus on when writing your interview questions:

  • Encourage your interviewees to tell stories: There’s a direct correlation between the questions you write for a user interview and the answers you get back. Consider more open-ended questions, with the aim of getting your interviewees to tell you stories and share more detail. For example, “Tell me about the last car you owned” is much better than “What was the last car you owned”.
  • Consider different types of questions: You don’t want to dive right into the complex, detailed questions when your interviewee has barely walked into the room. It’s much better to start an interview off with several ‘warm-up’ questions, that will get them in the right frame of mind. Think questions like: “What do you do for work?” and “How often do you use a computer at home?”. Answering these questions will put them in the right frame of mind for the rest of the interview.
  • Start with as many questions as you can think of – then trim: This can be quite a helpful exercise. When you’re actually putting pen to paper (or fingers to keyboard) and writing your questions, go broad at first. Then, once you’ve got a large selection to choose from, trim them back.
  • Have someone review your questions: Whether it’s another researcher on your team or perhaps someone who’s familiar with the audience you plan to interview, get another pair of eyes on your questions. Beyond just making sure they all make sense and are appropriate, they may be able to point out any questions you may have missed.

Recruit participants

Having a great set of questions is all well and good, but you need to interview the right kind of people. It’s not always easy. Finding representative or real users can quickly suck up a lot of time and bog down your other work. But this doesn’t have to be the case. With some strategy and planning you can make the process of participant recruitment quick and easy.

There are 2 main ways to go about recruitment. You can either handle the process yourself – we’ll share some tips for how to do this below – or use a recruitment service. Using a dedicated recruitment service will save you the hassle of actively searching for participants, which can often become a significant time-sink.

If you’re planning to recruit people yourself, here are a few ways to go about the process. You may find that using multiple methods is the best way to net the pool of participants you need.

  • Reach out to your customer support team: There’s a ready source of real users available in every organization: the customer support team. These are the people that speak to your organization’s customers every day, and have a direct line to their problems and pain points. Working with this team is a great way to access suitable participants, plus customers will value the fact that you’re taking the time to speak to them.
  • Recruit directly from your website: Support messaging apps like Intercom and intercept recruiting tools like Ethnio allow you to recruit participants directly from your website by serving up live intercepts. This is a fast, relatively hands-off way to recruit people quickly.
  • Ask your social media followers: LinkedIn, Twitter and Facebook can be great sources of research participants. There’s also the bonus that you can broadcast the fact that your organization focuses on research – and that’s always good publicity! If you don’t have a large following, you can also run paid ads on different social platforms.

Once a pool of participants start to flow in, consider setting up a dedicated research panel where you can log their details and willingness to take part in future research. It may take some admin at the start, but you’ll save time in the long run.

Note: Figure out a plan for participant data protection before you start collecting and storing their information. As the researcher, it’s up to you to take proper measures for privacy and confidentiality, from the moment you collect an email address until you delete it. Only store information in secure locations, and make sure you get consent before you ever turn on a microphone recorder or video camera.

Run your interviews

Now for the fun part – running your user interviews. In most cases, user interviews follow a simple format. You sit down next to your participant and run through your list of questions, veering into new territory if you sense an interesting discussion. At the end, you thank them for their time and pass along a small gift (such as a voucher) as a thank-you.

Of course, there are a few other things that you’ll want to keep in mind if you really want to conduct the best possible interviews.

  • Involve others: User interviews are a great way to show the value of research and give people within your organization a direct insight into how users think. There are no hard and fast rules around who you should bring to a user interview, just consider how useful the experience is likely to be for them. If you like, you can also assign them the role of notetaker.
  • Record the interview: You’ll have to get consent from the interviewee, but having a recording of the interview will make the process of analysis that much easier. In addition to being able to listen to the recording again, you can convert the entire session into a searchable text file.
  • Don’t be afraid to go off-script: Interviewing is a skill, meaning that the more interviews you conduct, the better you’re going to get. Over time, you’ll find that you’re able to naturally guide the conversation in different directions as you pick up on things the interviewee says. Don’t be discouraged if you find yourself sticking to your prepared questions during your first few interviews.
  • Be attentive: You don’t want to come across as a brick wall when interviewing someone – you want to be seen as an attentive listener. This means confirming that you’re listening by nodding, making eye contact and asking follow-up questions naturally (this last one may take practice). If you really struggle to ask follow-up questions, try writing a few generic questions can you can use at different points throughout the interview, for example “Could you tell me more about that?”. There’s a great guide on UXmatters about the role empathy has to play in understanding users.
  • Debrief afterwards: Whether it’s just you or you and a notetaker, take some time after the interview to go over how it went. This is a good opportunity to take down any details either you may have missed and to reflect and discuss some of the key takeaways.

Analyze your interview findings

At first glance, analyzing the qualitative data you’ve captured from a user interview can seem daunting. But, with the right approach (and some useful tools) you can extract each and every useful insight.

If you’ve recorded your interview sessions, you’ll need to convert your audio recordings into text files. We recommend a tool like Descript. This software makes it easy to take an audio file of your recording and transform it into a document, which is much faster than doing it without dedicated software. If you like, there’s also the option of various ‘white glove’ services where someone will transcribe the interview for you.

With your interview recordings transcribed and notes in-hand, you can start the process of thematic analysis. If you’re unfamiliar, thematic analysis is one of the most popular approaches for qualitative research as it helps you to find different patterns and themes in your data. There are 2 ways to approach this. The first is largely manual, where you set up a spreadsheet with different themes like ‘navigation issue’ and ‘design problem’, and group your findings into these areas. This can be done using sticky notes, which used to be a common ways to analyze findings.

The second involves dedicated qualitative research tool like Reframer. You log your notes over the course of several interview sessions and then use Reframer’s tagging functionality to assign tags to different insights. By applying tags to your observations, you can then use its analysis features to create wider themes. The real benefit here is that there’s no chance of losing your past interviews and analysis as everything is stored in one place. You can also easily download your findings into a spreadsheet to share them with your team.

What’s next?

With your interviews all wrapped up and your analysis underway, you’re likely wondering what’s next. There’s a good chance your interviews will have opened up new areas you’d like to test, so now could be the perfect time to assess other qualitative research methods and add more human data to your research project. On the other hand, you may want to move onto quantitative research and put some numbers behind your research.

Whether you choose to proceed down a qualitative or quantitative path, we’re pulled together some more useful articles and things for you to read:

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Meera Pankhania: From funding to delivery - Ensuring alignment from start to finish

It’s a chicken and egg situation when it comes to securing funding for a large transformation program in government. On one hand, you need to submit a business case and, as part of that, you need to make early decisions about how you might approach and deliver the program of work. On the other hand, you need to know enough about the problem you are going to solve to ensure you have sufficient funding to understand the problem better, hire the right people, design the right service, and build it the right way. 

Now imagine securing hundreds of millions of dollars to design and build a service, but not feeling confident about what the user needs are. What if you had the opportunity to change this common predicament and influence your leadership team to carry out alignment activities, all while successfully delivering within the committed time frames?

Meera Pankhania, Design Director and Co-founder of Propel Design, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, on traceability and her learnings from delivering a $300 million Government program.

In her talk, Meera helps us understand how to use service traceability techniques in our work and apply them to any environment - ensuring we design and build the best service possible, no matter the funding model.

Background on Meera Pankhania

As a design leader, Meera is all about working on complex, purpose-driven challenges. She helps organizations take a human-centric approach to service transformation and helps deliver impactful, pragmatic outcomes while building capability and leading teams through growth and change.

Meera co-founded Propel Design, a strategic research, design, and delivery consultancy in late 2020. She has 15 years of experience in service design, inclusive design, and product management across the private, non-profit, and public sectors in both the UK and Australia. 

Meera is particularly interested in policy and social design. After a stint in the Australian Public Service, Meera was appointed as a senior policy adviser to the NSW Minister for Customer Service, Hon. Victor Dominello MP. In this role, she played a part in NSW’s response to the COVID pandemic, flexing her design leadership skills in a new, challenging, and important context.

Contact Details:

Email address: meera@propeldesign.com.au

Find Meera on LinkedIn  

From funding to delivery: ensuring alignment from start to finish 🏁🎉👏

Meera’s talk explores a fascinating case study within the Department of Employment Services (Australia) where a substantial funding investment of around $300 million set the stage for a transformative journey. This funding supported the delivery of a revamped Employment Services Model, which had the goal of delivering better services to job seekers and employers, and a better system for providers within this system. The project had a focus on aligning teams prior to delivery, which resulted in a huge amount of groundwork for Meera.

Her journey involved engaging various stakeholders within the department, including executives, to understand the program as a whole and what exactly needed to be delivered. “Traceability” became the watchword for this project, which is laid out in three phases.

  • Phase 1: Aligning key deliverables
  • Phase 2: Ensuring delivery readiness
  • Phase 3: Building sustainable work practices

Phase 1: Aligning key deliverables 🧮

Research and discovery (pre-delivery)

Meera’s work initially meant conducting extensive research and engagement with executives, product managers, researchers, designers, and policymakers. Through this process, a common theme was identified – the urgent (and perhaps misguided) need to start delivering! Often, organizations focus on obtaining funding without adequately understanding the complexities involved in delivering the right services to the right users, leading to half-baked delivery.

After this initial research, some general themes started to emerge:

  1. Assumptions were made that still needed validation
  2. Teams weren’t entirely sure that they understood the user’s needs
  3. A lack of holistic understanding of how much research and design was needed

The conclusion of this phase was that “what” needed to be delivered wasn’t clearly defined. The same was true for “how” it would be delivered.

Traceability

Meera’s journey heavily revolved around the concept of "traceability” and sought to ensure that every step taken within the department was aligned with the ultimate goal of improving employment services. Traceability meant having a clear origin and development path for every decision and action taken. This is particularly important when spending taxpayer dollars!

So, over the course of eight weeks (which turned out to be much longer), the team went through a process of combing through documents in an effort to bring everything together to make sense of the program as a whole. This involved some planning, user journey mapping, and testing and refinement. 

Documenting Key Artifacts

Numerous artifacts and documents played a crucial role in shaping decisions. Meera and her team gathered and organized these artifacts, including policy requirements, legislation, business cases, product and program roadmaps, service maps, and blueprints. The team also included prior research insights and vision documents which helped to shape a holistic view of the required output.

After an effort of combing through the program documents and laying everything out, it became clear that there were a lot of gaps and a LOT to do.

Prioritising tasks

As a result of these gaps, a process of task prioritization was necessary. Tasks were categorized based on a series of factors and then mapped out based on things like user touch points, pain points, features, business policy, and technical capabilities.

This then enabled Meera and the team to create Product Summary Tiles. These tiles meant that each product team had its own summary ahead of a series of planning sessions. It gave them as much context (provided by the traceability exercise) as possible to help with planning. Essentially, these tiles provided teams with a comprehensive overview of their projects i.e. what their user needs, what certain policies require them to deliver, etc.  

Phase 2: Ensuring delivery readiness 🙌🏻

Meera wanted every team to feel confident that we weren’t doing too much or too little in order to design and build the right service, the right way.

Standard design and research check-ins were well adopted, which was a great start, but Meera and the team also built a Delivery Readiness Tool. It was used to assess a team's readiness to move forward with a project. This tool includes questions related to the development phase, user research, alignment with the business case, consideration of policy requirements, and more. Ultimately, it ensures that teams have considered all necessary factors before progressing further. 

Phase 3: Building sustainable work practices 🍃

As the program progressed, several sustainable work practices emerged which Government executives were keen to retain going forward.

Some of these included:

  • ResearchOps Practice: The team established a research operations practice, streamlining research efforts and ensuring that ongoing research was conducted efficiently and effectively.
  • Consistent Design Artifacts: Templates and consistent design artifacts were created, reducing friction and ensuring that teams going forward started from a common baseline.
  • Design Authority and Ways of Working: A design authority was established to elevate and share best practices across the program.
  • Centralized and Decentralized Team Models: The program showcased the effectiveness of a combination of centralized and decentralized team models. A central design team provided guidance and support, while service design leads within specific service lines ensured alignment and consistency.

Why it matters 🔥

Meera's journey serves as a valuable resource for those working on complex design programs, emphasizing the significance of aligning diverse stakeholders and maintaining traceability. Alignment and traceability are critical to ensuring that programs never lose sight of the problem they’re trying to solve, both from the user and organization’s perspective. They’re also critical to delivering on time and within budget!

Traceability key takeaways 🥡

  • Early Alignment Matters: While early alignment is ideal, it's never too late to embark on a traceability journey. It can uncover gaps, increase confidence in decision-making, and ensure that the right services are delivered.
  • Identify and audit: You never know what artifacts will shape your journey. Identify everything early, and don’t be afraid to get clarity on things you’re not sure about.
  • Conducting traceability is always worthwhile: Even if you don’t find many gaps in your program, you will at least gain a high level of confidence that your delivery is focused on the right things.

Delivery readiness key takeaways 🥡

  • Skills Mix is Vital: Assess and adapt team member roles to match their skills and experiences, ensuring they are positioned optimally.
  • Not Everyone Shares the Same Passion: Recognize that not everyone will share the same level of passion for design and research. Make the relevance of these practices clear to all team members.

Sustainability key takeaways 🥡

  • One Size Doesn't Fit All: Tailor methodologies, templates, and practices to the specific needs of your organization.
  • Collaboration is Key: Foster a sense of community and collective responsibility within teams, encouraging shared ownership of project outcomes.

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