Optimal Blog

There is strong backlash about the perceived failures of Human Centred Design (HCD) and its contribution to contemporary macro problems. There seems to be a straightforward connection: HCD and Design Thinking have been adopted by organizations and are increasingly part of product/experience development, especially in big tech. However the full picture is more complex, and HCD does have some issues.

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Dan Dixon, UX and Design Research Director and Stéphan Willemse, Strategy Director/Head of Strategy, both from the Digital Arts Network, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about the evolution and future of HCD.

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In their talk, Dan and Stéphan cover the history of HCD, its use today, and its limitations, before presenting a Post HCD future. What could it be, and how should it be different? Dan and Stéphan help us to step outside of ourselves as we meet new problems with new ways of Design Thinking.

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Dan Dixon and Stéphan Willemse bios

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Dan is a long-term practitioner of human-centred experience design and has a wealth of experience in discovery and qual research. He’s worked in academic, agency and client-side roles in both the UK and NZ, covering diverse fields such as digital, product design, creative technology and game design. His history has blended a background in the digital industry with creative technology teaching and user experience research. He has taken pragmatic real-world knowledge into a higher education setting as well as bringing deeper research skills from academia into commercial design projects. In higher education, as well as talks and workshops, Dan has been teaching and sharing these skills for the last 16 years. 

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Stéphan uses creativity, design and strategy to help organizations innovate towards positive, progressive futures. He works across innovation, experience design, emerging technologies, cultural intelligence and futures projects with clients including Starbucks, ANZ, Countdown, TradeMe and the public sector. He holds degrees in PPE, Development Studies, Education and an Executive MBA. However, he doesn’t like wearing a suit and his idea of the perfect board meeting is at a quiet surf break. He thinks ideas are powerful and that his young twins ask the best questions about the world we live in.

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Contact Details:

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Email: dan.dixon@digitalartsnetwork.com

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Find Dan on LinkedIn  

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HCD IS DEAD, LONG LIVE HCD 👑

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Dan and Stéphan take us through the evolving landscape of Human Centred Design (HCD) and Design Thinking. Can HCD effectively respond to the challenges of the modern era, and can we get ahead of the unintended consequences of our design? They examine the inputs and processes of design, not just the output, to scrutinize the very essence of design practice.

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A brief history of HCD

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In the 1950s and 1960s, designers began exploring the application of scientific processes to design, aiming to transform it into a systematic problem-solving approach. Later in the 1960s, design thinkers in Scandinavia initiated the shift towards cooperative and participative design practices. Collaboration and engagement with diverse stakeholders became integral to design processes. Then, the 1970s and 1980s marked a shift in perspective, viewing design as a fundamentally distinct way of approaching problems. 

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Moving into the late 1980s and 1990s, design thinking expanded to include user-centered design, and the idea of humans and technology becoming intertwined. Then the 2000s witnessed a surge in design thinking, where human-centered design started to make its mark.

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Limitations of the “design process”

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Dan and Stéphan discuss the “design squiggle”, a concept that portrays the messy and iterative nature of design, starting chaotically and gradually converging toward a solution. For 20 years, beginning in the early 90s, this was a popular way to explain how the design process feels. However, in the past 10 years or so, efforts to teach and pass down design processes have become common practice. Here enter concepts like the “double diamond” and “pattern problem”, which seek to be repeatable and process-driven. These neat processes, however, demand rigid adherence to specific design methods, which can ultimately stifle innovation. 

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Issues with HCD and its evolution

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The critique of such rigid design processes, which developed alongside HCD, highlights the need to acknowledge that humans are just one element in an intricate network of actors. By putting ourselves at the center of our design processes and efforts, we already limit our design. Design is just as much about the ecosystem surrounding any given problem as it is about the user. A limitation of HCD is that we humans are not actually at the center of anything except our own minds. So, how can we address this limitation?

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Post-anthropocentric design starts to acknowledge that we are far less rational than we believe ourselves to be. It captures the idea that there are no clear divisions between ‘being human’ and everything else. This concept has become important as we adopt more and more technology into our lives, and we’re getting more enmeshed in it. 

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Post-human design extends this further by removing ourselves from the center of design and empathizing with “things”, not just humans. This concept embraces the complexity of our world and emphasizes how we need to think about the problem just as much as we think about the solution. In other words, post-human design encourages us to “live” in our design problem(s) and consider multiple interventions.

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Finally, Dan and Stéphan discuss the concept of Planetary design, which stresses that everything we create, and everything we do, has the possibility to impact everything else in the world. In fact, our designs do impact everything else, and we need to try and be aware of all possibilities.

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Integrating new ways of thinking about design

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To think beyond HCD and to foster innovation in design, we can begin by embracing emerging design practices and philosophies such as "life-centered design," "Society-centered design," and "Humanity-centered design." These emerging practices have toolsets that are readily available online and can be seamlessly integrated into your design approach, helping us to break away from traditional, often linear, methodologies. Or, taking a more proactive stance, we can craft our own unique design tools and frameworks. 

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Why it matters 🎯

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To illustrate how design processes can evolve to meet current and future challenges of our time, Dan and Stéphan present their concept of “Post human-centered design” (Post HCD). At its heart, it seeks to take what's great about HCD and build upon it, all while understanding its issues/limitations.

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Dan and Stéphan put forward, as a starting point, some challenges for designers to consider as we move our practice to its next phase.

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Suggested Post HCD principles:

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• Human to context: Moving from human-centered to a context-centred or context sensitive point of view.
• Design Process to Design Behaviour: Not being beholden to design processes like the “double diamond”. Instead of thinking about designing for problems, we should design for behaviors instead. 
• Problem-solutions to Interventions: Thinking more broadly about interventions in the problem space, rather than solutions to the problems
• Linear to Dynamic: Understand ‘networks’ and complex systems.
• Repeated to Reflexive: Challenging status quo processes and evolving with challenges that we’re trying to solve.

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The talk wraps up by encouraging designers to incorporate some of this thinking into everyday practice. Some key takeaways are: 

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• Expand your web of context: Don’t just think about things having a center, think about networks.
• Have empathy for “things”: Consider how you might then have empathy for all of those different things within that network, not just the human elements of the network.
• Design practice is exploration and design exploration is our practice: Ensure that we're exploring both our practice as well as the design problem.
• Make it different every time: Every time we design, try to make it different, don't just try and repeat the same loop over and over again.

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As information professionals, we work with the “stuff” of information in our everyday work. We search for information, we spend time analyzing and synthesizing it, and we carefully create and structure it. Whether you elicit information from users and stakeholders, explore large data sets, design ‘journeys’ or interfaces, or create information architectures, understanding the information you are using and creating as information can help you do your work better.

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Kat King, Business Intelligence Analyst at the University of Michigan Library, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about understanding exactly what information is, and where it is, in our work.

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In her talk, Kat uses simple examples to teach you to “see” the information around you and understand what makes something “information” in the context of working as a human to accomplish something.

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Kat King bio 🎤

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Kat King is an Information Architect interested in language, meaning, and the things we make. She currently works as a Business Intelligence Analyst for the University of Michigan Library.

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Contact Details:

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Email: Katalogofchaos@gmail.com

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Where is the information? 📍🗺️

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Information theory can be dense and jargon-filled, and discussions in academic texts can feel divorced from the practice of actually working with information. We’re all told that information architecture is much more than website navigation. So, what is it? IA has a reputation for being difficult to understand, and in her talk, Kat attempts to help us understand what it is, where the information is, and what is it that we’re doing when we use IA methods.

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Kat defines IA as “the practice of ensuring ontological alignment”. ‘Ontological’ relates to concepts, categories, properties, and relationships. ‘Alignment’ means arrangements into appropriate relative positions. Therefore, information architecture is “the practice of ensuring concepts, categories and their properties and relationships are arranged into appropriate relative positions.”

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To align information then, you need to begin by sorting it into concepts and categories, which is difficult because information can sometimes be “slippery and abstract”. Kat argues this is the real reason that IA is sometimes hard to wrap our heads around. So, getting to the heart of the question, what is information? 

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Kat defines information as “a patterned relationship between differences that reduces uncertainty”. The key word here is ‘differences’. The trick to understanding and taming information is to identify what is different about sets of information. The next trick is to identify consistencies between these differences.

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This can be a little confusing, so Kat uses the example of picking fruit. We tend to use color (the difference) to identify when fruit is ripe and sweet. We know for a fact that, at some point, the fruit will be at its sweetest and, while there is a scientific way of identifying this point, we have to use the information we have at our disposal instead i.e. the colour of the fruit. The skin of the fruit in this example is like an interface - allowing a flow of information from the fruit’s ripening process to our eyes.

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Information categories 🧺🧺🧺

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The relationship between the information described in the fruit example can be split into two categories. “Information 1” is a factual, objective description of when the fruit is ripe (i.e. the science of why the fruit is the color that it is right now), whereas our subjective observation, based on color, is “Information 2”.

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• Information 1: Matter and energy, and their properties and interactions i.e. the laws of physics and universal truth or rules

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Information 1 poses challenges for us because we have a narrow range of perception, attention, and aggregation, which means we, as humans, can’t possibly understand the laws of nature just by observing. We have evolved to be simple, efficient observers of what is important to us. In other words, we don’t need to understand everything in order to get things right. We see patterns and generalize. Going back to the fruit example – we only need to know the color of ripe fruit, not the exact chemistry of why it is ripe.

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• Information 2: This is Information 1 that is given meaning by humans. This is done via processing semantic information, or “differences and structures that create meaning for people”.

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We use semantic information by processing concepts, patterns, categories, mental models, and even language as inputs to form our understanding. As social animals, we tend to reinforce general ‘truths’ about things because we’re constantly cooperating using shared information. General ‘truths’ are good enough.

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Kat uses the following interaction to demonstrate the interplay of different information.

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• Person 1: If the raspberries look good, can you get some for me?
• Person 2: How can tell is they’re good?
• Person 1: Get the ones that are the most red.

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In this interaction, the different pieces of information can be broken down by category:

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• Semantic information = Words and concepts
• Information 1 = Meaningful signs
• Information 2 = Perceptible differences
• Real life information = Raspberries

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Using our ability to communicate and understand concepts (words “red”, “good”, and “raspberries”) helps us to understand Information 2 (processing the words and concepts to understand that a red berry is good”), which aligns with Information 1 (the evolutionary science and ongoing consistency of red/ripe berries being sweet) that helps us decide when processing all of this information.

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So, now that we understand a little more about information, how does this influence our roles as designers?

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Why it matters 👀

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Thanks to our individual lived experiences, people have many different inputs/concepts about things. However, Kat points out that we’re pretty good at navigating these different concepts/inputs.

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Take conversations, for example. Conversations are our way of getting a “live” alignment of information. If we’re not on the same page we can ask each other questions to ensure we’re communicating semantic information accurately. 

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When we start to think about technology and digital products, the interfaces that we design and code become the information that is being transmitted, rather than words in a conversation. The design and presentation become semantic information structures, helping someone to understand the information we’re putting forward. This highlights the importance of aligning the interface (structure and semantic information) and the users' ontology (concepts and categories). For the interface to work, IA practitioners and designers need to know what most people understand to be true when they interact with information, concepts, and categories. 

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We need to find some sort of stability that means that most users can understand what they need to do to achieve a goal or make a decision. To do this, we need to find common ground between the semantic information (that might vary between users) so that users can have successful Information 2 style interactions (i.e. absorbing and understanding the concepts presented by the interface).

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To wrap up, let’s remind ourselves that information architecture is “the practice of ensuring concepts, categories and their properties and relations are arranged into appropriate and relevant positions”. As IA practitioners and designers, it’s our job to ensure that concepts and categories are arranged in structures that can be understood by the nuance of shared human understanding and semantic information – not just in some physical diagram.

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We need to present stable, local structures that help to reduce uncertainty at the moment of interaction. If we don’t, the information flow breaks and we aren’t reducing uncertainty; instead, we create confusion and disappointing user interactions with our digital products. Making sure we present information correctly is important (and difficult!) for the success of our products – and for better or worse, it’s the work of information architecture! 

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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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At Optimal Workshop, we're dedicated to building the best user research platform to empower you with the tools to better understand your customers and create intuitive digital experiences. We're thrilled to announce some game-changing updates and new products that are on the horizon to help elevate the way you gather insights and keep customers at the heart of everything you do. 

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What’s new…

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Integration with Figma 🚀

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Last month, we joined forces with design powerhouse Figma to launch our integration. You can import images from Figma into Chalkmark (our click-testing tool) in just a few clicks, streamlining your workflows and getting insights to make decisions based on data not hunches and opinions.  

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What’s coming next…

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Session Replays 🧑‍💻

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With session replay you can focus on other tasks while Optimal Workshop automatically captures card sort sessions for you to watch in your own time.  Gain valuable insights into how participants engage and interpret a card sort without the hassle of running moderated sessions. The first iteration of session replays captures the study interactions, and will not include audio or face recording, but this is something we are exploring for future iterations. Session replays will be available in tree testing and click-testing later in 2024.  

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Reframer Transcripts 🔍

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Say goodbye to juggling note-taking and hello to more efficient ways of working with Transcripts! We're continuing to add more capability to Reframer, our qualitative research tool, to now include the importing of interview transcripts. Save time, reduce human errors and oversights by importing transcripts, tagging and analyzing observations all within Reframer. We’re committed to build on transcripts with video and audio transcription capability in the future,  we’ll keep you in the loop and when to expect those releases. 

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Prototype testing 🧪

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The team is fizzing to be working on a new Prototype testing product designed to expand your research methods and help test prototypes easily from the Optimal Workshop platform. Testing prototypes early and often is an important step in the design process, saving you time and money before you invest too heavily in the build. We are working with customers and on delivering the first iteration of this exciting new product. Stay tuned for Prototypes coming in the second quarter of 2024.   

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Workspaces 🎉

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Making Optimal Workshop easier for large organizations to manage teams and collaborate more effectively on projects is a big focus for 2024. Workspaces are the first step towards empowering organizations to better manage multiple teams with projects. Projects will allow greater flexibility on who can see what, encouraging working in the open and collaboration alongside the ability to make projects private. The privacy feature is available on Enterprise plans.

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Questions upgrade❓

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Our survey product Questions is in for a glow up in 2024 💅. The team are enjoying working with customers, collecting and reviewing feedback on how to improve Questions and will be sharing more on this in the coming months. 

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Help us build a better Optimal Workshop

We are looking for new customers to join our research panel to help influence product development. From time to time, you’ll be invited to join us for interviews or surveys, and you’ll be rewarded for your time with a thank-you gift.  If you’d like to join the team, email product@optimalworkshop.com

The Ministry for Primary Industry’s (MPI) customers have some of the most varied information needs — possibly the most varied in New Zealand. MPI provides information on how to follow fishing rules, what the requirements are to sell dairy products at the market, and how to go about exporting honey to Asia. Their website mpi.govt.nz has all the information.

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However the previous website was dense and complicated, and MPI’s customers were struggling to find the information they needed, often calling the contact center instead — one of several indicators that people were lost and confused on the website.

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Ruth Hendry, Head of Strategic Growth at Springload, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about how new IA helped MPI’s broad range of customers find the information they needed.

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In her talk, Ruth takes us through the tips and techniques used to create an IA that met a wide variety of user needs. She covers the challenges they faced, what went well, what didn’t go so well, and what her team would do differently next time.

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Background on Ruth Hendry 💃🏻

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Ruth was Springload’s Content Director; now she’s Head of Strategic Growth. She has broad experience in content, UX, and customer-led design. A data nerd at heart, she uses analytics, research and testing to drive decision-making, resulting in digital experiences that put the customer at the forefront.

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At Springload Ruth has worked on large-scale content and information architecture projects for organisations including Massey University, Vodafone and Air New Zealand. She got into the world of websites in her native UK, working on Wildscreen's ARKive project. After she arrived in Aotearoa, she spent four years looking after Te Papa's digital content, including the live broadcast of the colossal squid dissection. She's Springload's resident cephalopod expert.

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She finds joy in a beautiful information architecture, but her desk is as messy as her websites are tidy.

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Contact Details:

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Email address: ruthbhendry@gmail.com

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LinkedIn URL: https://www.linkedin.com/in/ruth-hendry-658a0455/

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Food recalls, fishing rules, and forestry: creating an IA strategy for diverse audience needs 🎣

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Ruth begins her talk by defining IA. She says, “If IA is the way information is organized, structured, and labeled, then an IA strategy is the plan for how you achieve an effective, sustainable, people-focused IA.”

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Considering this, applying an IA strategy to the Ministry of Primary Industries (MPI) website was a challenge due to its diverse user groups. MPI is responsible for a range of things, such as publishing food recalls, looking after New Zealand’s biosecurity, outlining how much fish can be caught, how to export products, and even how to move pets between countries. Needless to say, the scope of this IA project was huge.

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The current state of the website was challenging to navigate. In fact, one customer said, “It’s hard to find what you need and hard to understand”. MPI Contact Center staff often found themselves simply guiding customers to the right information online over the phone. 

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So, in solving such a massive problem, does having an IA strategy work? Ruth says yes! And it can have a huge impact. She backs up her strategy with the results of this project before broadly outlining how she and her team achieved the following improvements.

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The project achieved:

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• 37% decrease in time spent on the home page and landing pages
  • Customers found where they needed to go, faster, using the new IA and navigation elements
• 21% decrease in on-page searches
  • People could find the content they need more easily
• 53% reduction in callers to MPI saying that they couldn’t find what they needed on the website
  • Users could more easily get information online

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Developing an IA strategy 🗺️

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Ruth attempts to summarize 14 weeks' worth of work that she and her team delivered in this project.

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Step one: Understanding the business

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During this step, Ruth and her team looked at finding out exactly what MPI wanted to achieve, what its current state is, what its digital maturity is, what its current IA was like (and the governance of it), how the site got to be in the way that it was, and what their hopes and aspirations were for their digital channels. They conducted:

• Stakeholder interviews and focus groups
• Reviewing many, many documents
• Domain and analogous search
• Website review

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Step two: Understand the customers

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In this step, the team looked at what people want to achieve on the site, their mental models (how they group and label information), their main challenges, and whether or not they understood what MPI does. They conducted:

• A review on website analytics and user needs
• In-person interviews and prototype testing
• Card sorts
• Intercepts
• Users surveys
• Treejack testing

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Step three: Create the strategy

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This talk doesn’t cover strategy development in depth, but Ruth shares some of the most interesting things she learned (outlined below) throughout this project that she’ll take into other IA strategy projects.

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Why it matters 🔥

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Throughout the project, Ruth felt that there were eight fundamental things that she would advise other teams to do when creating an IA strategy for large organizations with massively diverse customer needs. 

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1. Understand the business first: Their current IA is a window into their soul. It tells us what they value, what’s important to them, and also the stories that they want to tell their customers. By understanding the business, Ruth and her team were able to pinpoint what it was about the current IA that wasn’t working.
2. Create a customer matrix: Find the sweet spot of efficient and in-depth research. When an organization has a vast array of users and audience needs, it can often seem overwhelming. A customer matrix really helps to nail down who needs what information.
3. Card sort, then card sort again: They are the best way to understand how people’s mental model works. They are critical to understanding how information should be organized and labeled. They are particularly useful when dealing with large and diverse audiences! In the case of the MPI project, card sorts revealed a clear difference between business needs and personal needs, helping to inform the IA.
4. Involve designers: The earlier the better! User Interface (UI) decisions hugely influence the successful implementation of new IA and the overall user journey. Cross-discipline collaboration is the key to success!
5. Understand the tech: Your IA choice impacts design and tech decisions (and vice versa). IA and tech choices are becoming increasingly interrelated. Ruth stresses the importance of understanding the tech platforms involved before making IA recommendations and working with developers to ensure your recommendations are feasible.
6. Stakeholders can be your biggest and best advocates: Build trust with stakeholders early. They really see IA as a reflection of their organization and they care a lot about how it is presented.
7. IA change drives business change: You can change the story a business tells about itself. Projects like this, which are user-centric and champion audience thinking, can have a positive effect throughout the business, not just the customer. Sometimes internal business stakeholders' thinking needs to change before the final product can change.
8. IA is more than a menu: And your IA strategy should reflect that. IA captures design choices, content strategy, how technical systems can display content, etc.

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Your IA strategy needs to consider

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• Content strategy: How is content produced, governed, and maintained sustainably going forward?
• Content design: How is content designed and does it support a customer-focused IA?
• UI and visual design: Does UI and visual design support a customer-focused IA?
• Technical and functional requirements: Are they technically feasible in the CMS? And what do we need to support the changes, now and into the future?
• Business process change: How will business processes adapt to maintain IA changes sustainably in the long term?
• Change management and comms plan: How can we support the dissemination of key changes throughout the business, to key stakeholders, and to customers?

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Finally, Ruth reemphasizes that AI is more than just designing a new menu! There’s a lot more to consider when delivering a successful IA strategy that meets the needs of the customer - approach the project in a way that reflects this.

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Every month we have fun and informative “bite sized” presentations to add some inspiration to your lunch break.  These virtual events allow us to partner with amazing speakers, community groups and organizations to share their insights and hot takes on a variety of topics impacting our industry. 

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Join us at the end of every month for Lunch n' Learn.

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Eniola Abioye

Join us for a FREE Fireside chat on Jan 31st @ 12-1pm PST (Jan 30th at 9am NZT) with Eniola. You’ll learn about her career journey from integrative biology to UX, 3 things that are changing about the industry, and what you need to know to transition into UX this year. This is a casual, Q/A style conversation so bring your questions and get excited to meet Eniola!

Eniola Abioye, Founder of UX Outloud and UX Researcher at Meta will be hosting a HYBRID masterclass to help you uplevel your UX career. This event will take place on Feb 24th in the SF Bay Area & virtually worldwide!

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Speaker Bio

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I help UX Researchers improve their research practice. Whether you’re seasoned and looking to level up or a new researcher looking to get your bearings in UX, I can help you focus and apply your skillset.

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Now, I am a UX Researcher at Meta and speak to all different types of users their experience on the platform. I take an agile approach and often employ Rapid Iterative Testing and Evaluation. I am innately curious, a self-starter, adaptable and communicative with a knack for storytelling.

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Grab your lunch, invite your colleagues and we hope to see you at our next Lunch n’ Learn! 🥗