IA, a fundamental function of the UX process, is not effectively addressed
Why is information architecture important?
Information Architecture (IA) is the discipline that focuses on making information findable and understandable. The concept has evolved significantly since the late 1970s, when Richard Saul Wurman first coined the term in his book Information Anxiety. Unfortunately, information overload and its consequent information anxiety is a defining feature of our modern digital lives. If we are to reclaim the initial promise of the digital era, we must improve IA.
At the beginning of the web era, the IA discipline was exclusive to a specific role within a design team. Today, IA has become part of the UX process on all projects, from the simple to the complex, and is a consideration for nearly all members of a team. While it has become one of the foundations for designing digital experiences, it has also become common for designers to overlook the fundamental principles of IA. This leads to the design of UX journeys without sufficient consideration for their underlying information architecture. In reality, that architecture plays a fundamental role in creating systems and services with a consistent and understandable structure.
The problems IA addresses
In his book Architecture of the Information, Peter Moville cites a famous example of how strong IA can improve customers’ experiences with a brand. When Disneyland was built in the 1950s, there was a distribution map of the attractions similar to a sitemap, with each group of attractions organized into a category. For example, Adventure Land had several attractions, Fantasy Land had another group. Because this sort of park was first of its kind, it was necessary to label these categories to evoke people’s emotions and fantasies so they could become easily recognizable and generate the appropriate context. Years later, when the park expanded throughout the world, the same scheme was maintained with small variations to adapt to the cultural environment, this scheme of organization of the attractions generated consistency between the different channels and was scalable to include more facilities. The IA became not only a matter of helping people navigate the park, it became an important branding moment for Disney that has lasted for decades.
If we go back to past decades, we can see that the information has traditionally been tied to physical formats at a 1:1 ratio. Consider vinyl records, for example: you could organize your record collection either alphabetically or by genre, but not both at the same time; and in order to access the information stored on the record, its physical architecture must be maintained. Thanks to digital technology, we now access information in multiple ways. Consider iTunes: it is a tool that has evolved over time, including more types of content and multiple access routes. This evolution of this type of tool has produced the appearance of others with streaming services that work in a similar ways, such as Spotify.
Information Architecture examples
There are many key IA components that we use all the time when designing websites and desktop / mobile applications. Some of them are widely understood as IA features, such as filters and sorting tools. Others are components we use without identifying them properly as IA components. Here are a few examples of the ones we tend to overlook:
Organization Systems: These are the largest categories into which we group and organize content, providing the user with the context and structure necessary to locate information.
Labeling Systems: This involves describing categories, options and links in the most appropriate way to generate meaning for the user.
Navigation Systems: This is how users move through content. It is made up of the global menu, local menu and contextual navigation.
Search Systems: This is how users search for content, as well as find lists of suggestions that may appear with possible connections to the searched term.
When articulating any design proposal, remember that IA consists of all the content and organizational structures within a given system. Those structures will be determined by business logic and cultural factors.
How do people perceive information environments?
Information environments are very different between the digital and physical realm. In physical spaces, we can quickly deduce where we are and what we can do inside them. Mental models for processing the information in our physical environments have been around for a very long time. For example, when we enter a bathroom, it is easy to visualize elements and their uses. We know that we can do with the objects inside of them (i.e., shower, sinks, etc.). In a kitchen, we know exactly where we are and what we can do with a refrigerator, an oven, a dishwasher. At a bank, we know where to deposit money, how to access help from an agent.
In digital spaces, it is not always clear how to access the information we encounter. A result of technological advancements and our propulsion into the digital era has been a progressive dematerialization of information environments, However, what has been retained is the organization of and content contained in these environments. When we enter the website of a bank, for instance, it is easy to know that we are in a bank from the content shared on these spaces, such as ads for financial products. If we look at a hospital website, we can see labeling and navigation systems that mention the familiar elements of medicine and facilities. We see images of patients, health workers and doctors, among others faces you’re likely to see in an actual hospital.
The keys to good IA
When developing IA strategies during the UX process, it is good to consider all the outputs of UX research. This could include heuristic evaluations, content analysis, organizational analysis, evaluations of use cases, benchmarking, user interviews and many other data sets. This is important because having a good understanding of your outputs will help tailor the IA strategy to the specific business context, existing system content and intended audience.
The principles below will help refine your IA strategy even further:
Structure: IA is meant to generate structured systems, such as sitemaps. That means the success of your organizational and navigational systems depends on your ability to maintain order and proper hierarchy amongst your ideas.
Typologies: Use processes like benchmarking to understand the market for your specific product or service. Research any existing websites or apps that have similar or identical business objectives. Do they use similar types of features or organizational structures? This can help define core features as well as opportunities for differentiation.
Consistency and Scalability: Our duty here is to generate consistency between channels in order to scale properly, which is specific to each organization. Organizations have a business logic that will influence how their digital channels behave and connect with one another, as well as how they connect to physical environments.
Metaphors: Metaphors can evoke physical spaces in order to better describe digital environments. This is especially useful for helping stakeholders who have limited technical knowledge improve their understanding.
Communicate and Test: Keep your team members up to date on the articulation of your ideas through shared files. Whichever methodology you are using try to test rapid prototypes as early as possible with your audience.
Of course, it is a good idea to stop and evaluate IA over time. Review the principles above to be sure they effectively serve the business and the user. To do this well, you must attempt to switch between your creative and analytical sides. When done right, your IA will reflect the needs of the organization, while helping customers to navigate your information with ease and confidence.
