Radical Collaboration: how teamwork really can make the dream work

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:

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• 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

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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.

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Clara’s background 

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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.

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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.

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Contact Details:

You can find Clara in LinkedIn or on Twitter @cklimansilver

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

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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.

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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.

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Access for all 🦾

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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.

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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. 

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Research and testing 🔬

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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:

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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.

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The design partnership 🤝🏽

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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. 

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Why it matters 💡

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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.

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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:

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• 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

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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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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. 

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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?

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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.

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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.

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Background on Meera Pankhania

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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.

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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. 

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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.

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Contact Details:

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Email address: meera@propeldesign.com.au

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Find Meera on LinkedIn  

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

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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.

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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.

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

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Phase 1: Aligning key deliverables 🧮

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Research and discovery (pre-delivery)

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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.

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Traceability

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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!

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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. 

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Documenting Key Artifacts

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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.

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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.

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Prioritising tasks

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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.

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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.  

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Phase 2: Ensuring delivery readiness 🙌🏻

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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.

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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. 

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Phase 3: Building sustainable work practices 🍃

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

Some of these included:

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• 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.

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Why it matters 🔥

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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!

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Traceability key takeaways 🥡

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• 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.

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Delivery readiness key takeaways 🥡

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• 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.

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Sustainability key takeaways 🥡

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• 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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Knowing and understanding why and how your users use your product is invaluable for getting to the nitty gritty of usability. Delving deep with probing questions into motivation or skimming over looking for issues can equally be informative. 

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Put super simply, usability testing literally is testing how usable your product is for your users. If your product isn’t usable users often won’t complete their task, let alone come back for more. No one wants to lose users before they even get started. Usability testing gets under their skin and really into the how, why and what they want (and equally what they don’t).

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As we have been getting used to video calling regularly and using the internet for interactions, usability testing has followed suit. Being able to access participants remotely has allowed us to diversify the participant pool by not being restricted to those that are close enough to be in-person. This has also allowed an increase in the number of participants per test, as it becomes more cost-effective to perform remote usability testing.

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But if we’re remote, does this mean it can’t be moderated? No - remote testing, along with modern technology, can mean that remote testing can be facilitated and moderated. But what is the best method - moderated or unmoderated?

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What is moderated remote research testing?

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In traditional usability testing, moderated research is done in person. With the moderator and the participant in the same physical space. This, of course, allows for conversation and observational behavioral monitoring. Meaning the moderator can note not only what the participant answers but how and even make note of the body language, surroundings, and other influencing factors. 

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This has also meant that traditionally, the participant pool has been limited to those that can be available (and close enough) to make it into a facility for testing. And being in person has meant it takes time (and money) to perform these tests.

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As technology has moved along and the speed of internet connections and video calling has increased, this has opened up a world of opportunities for usability testing. Allowing usability testing to be done remotely. Moderators can now set up testing remotely and ‘dial in’ to observe participants anywhere they are. And potentially even running focus groups or other testing in a group format across the internet. 

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Pros of moderated remote research testing:

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- In-depth gathering of insights through a back-and-forth conversation and observing of the participants.

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- Follow-up questions don’t underestimate the value of being available to ask questions throughout the testing. And following up in the moment.

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- Observational monitoring noticing and noting the environment and how the participants are behaving, can give more insight into how or why they choose to make a decision.

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- Quick remote testing can be quicker to start, find participants, and complete than in-person. This is because you only need to set up a time to connect via the internet, rather than coordinating travel times, etc.

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- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing. This broadens your ability to broaden the pool, and participants can be either within your country or global. 

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Cons of moderated remote research testing:

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- Time-consuming having to be present at each test takes time. As does analyzing the data and insights generated. But remember, this is quality data.

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- Limited interactions with any remote testing there is only so much you can observe or understand across the window of a computer screen. It can be difficult to have a grasp on all the factors that might be influencing your participants.

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What is unmoderated remote research testing?

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In its most simple sense, unmoderated user testing removes the ‘moderated’ part of the equation. Instead of having a facilitator guide participants through the test, participants are left to complete the testing by themselves and in their own time. For the most part, everything else stays the same. 

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Removing the moderator, means that there isn’t anyone to respond to queries or issues in the moment. This can either delay, influence, or even potentially force participants to not complete or maybe not be as engaged as you may like. Unmoderated research testing suits a very simple and direct type of test. With clear instructions and no room for inference. 

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Pros of unmoderated remote research testing:

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- Speed and turnaround,  as there is no need to schedule meetings with each and every participant. Unmoderated usability testing is usually much faster to initiate and complete.

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- Size of study (participant numbers) unmoderated usability testing allows you to collect feedback from dozens or even hundreds of users at the same time. 

- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing, which broadens your participant pool.  And unmoderated testing means that it literally can be anywhere while participants complete the test in their own time.

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Cons of unmoderated remote research testing:

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- Follow-up questions as your participants are working on their own and in their own time, you can’t facilitate and ask questions in the moment. You may be able to ask limited follow-up questions.

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- Products need to be simple to use unmoderated testing does not allow for prototypes or any product or site that needs guidance. 

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- Low participant support without the moderator any issues with the test or the product can’t be picked up immediately and could influence the output of the test.

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When should you do moderated vs unmoderated remote usability testing?

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Each moderated and unmoderated remote usability testing have its use and place in user research. It really depends on the question you are asking and what you are wanting to know.

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Moderated testing allows you to gather in-depth insights, follow up with questions, and engage the participants in the moment. The facilitator has the ability to guide participants to what they want to know, to dig deeper, or even ask why at certain points. This method doesn’t need as much careful setup as the participants aren’t on their own. While this is all done online, it does still allow connection and conversation. This method allows for more investigative research. Looking at why users might prefer one prototype to another. Or possibly tree testing a new website navigation to understand where they might get lost and querying why the participant made certain choices.

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Unmoderated testing, on the other hand, is literally leaving the participants to it. This method needs very careful planning and explaining upfront. The test needs to be able to be set and run without a moderator. This lends itself more to wanting to know a direct answer to a query. Such as a card sort on a website to understand how your users might sort information. Or a first click to see how/where users will click on a new website.

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Planning your next user test? Here’s how to choose the right method

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With the ability to expand our pool of participants across the globe with all of the advances (and acceptance of) technology and video calling etc, the ability to expand our understanding of users’ experiences is growing. Remote usability testing is a great option when you want to gather information from users in the real world. Depending on your query, moderated or unmoderated usability testing will suit your study. As with all user testing, being prepared and planning ahead will allow you to make the most of your test.