Data is everywhere. It can be a powerful source of insights for your business, your project, or your personal goals. But how do you make sense of all the information you have? How do you turn data into decisions? In this article, we'll show you how to use information architecture (IA) to organize, structure, and present your data in a clear and meaningful way.
Information architecture is the practice of designing and arranging the elements of an information system, such as a website, an app, a dashboard, or a report. IA helps users find, understand, and use the information they need, and helps creators communicate their message and purpose. IA involves creating categories, labels, navigation, search, and layout that suit the content and the context of the data.
In an IT landscape, ideally, data flows from left to right, with the left side primarily handling intake and the right side focused on consumption and sharing. Information architecture ensures that this flow is as transparent as possible, and that the data flowing from the left to the right is as efficient, robust, and flexible as required by the landscape. Information architecture differs from data architecture in that the latter delves much deeper into the modeling aspect, whereas information architecture focuses more on data democratization and the availability of information throughout the landscape, with proper authentication and authorization.
Data with no context is useless. Accessing the right information at the right time by the right person enables data to be analysed and turned into insights. For these insights to be actionable there needs to be a definition of what outcomes are required or desirable, and which actions will enable these outcomes, by specific individuals, at specific times. The value of these outcomes can determine the importance of the insights needed, which determines the hierarchy and availability of the data required to deliver such insights. Information architecture is the structuring and labeling of content (data) in an effective and sustainable way, so that it can be analysed and used to disseminate information, or take action.
Information architecture can help you manage the complexities of dealing with data, such as data overload, fragmentation, ambiguity, and complexity. It can also provide a way to turn data into actionable insights that are relevant, reliable, and easy to access and understand. Data overload can be overwhelming and confusing for users, making it hard to find what they need and trust what they see. Data fragmentation can come from different sources, formats, and systems, making it difficult to integrate and compare. Data ambiguity may have multiple meanings, interpretations, and implications depending on the perspective and the goal of the user. Additionally, data complexity can have many dimensions, relationships, and patterns which require advanced analysis and visualization. Applying information architecture principles and techniques can help you make sense of all this data.
Information architecture provides a comprehensive view that enables the creation of actionable insights. When coupled with robust data governance and management practices, information architecture ensures that data of the right quality and model is accessible to the appropriate stakeholders (and IT platforms) when needed. This, in turn, enables the generation of timely and relevant insights aligned with defined OKRs, KPIs, and KDIs. Furthermore, information architecture elucidates the flow of data through the technology landscape and the significance underlying that flow.
Before you begin designing your information system, it's important to plan your information architecture. This involves defining the scope, goals, and users of your data. To do this, consider the purpose and context of your data, as well as the needs and expectations of your users. Additionally, think about the characteristics and requirements of your data, such as how much data you have, how often it changes, and how accurate it is. You should also consider how you store, process, and update it. All of these questions can help guide your planning process.
Organizing, labeling, and linking your data in a logical and intuitive way is essential when structuring your information architecture. Categorization is one method to do this, which involves grouping data into meaningful and distinct categories that reflect the main topics, themes, or types of the data. Additionally, labeling each category and other elements of the information system with clear and consistent labels that describe the content and the function of each element is important. Lastly, providing navigation paths and options such as menus, tabs, breadcrumbs, buttons or links will help users find the data they need. All of these methods will help build an effective information system.
Once you have a well-structured information architecture, it is time to present your information system. This involves designing and arranging the visual and interactive elements of your data in a way that is both organized and attractive. To do this, you should focus on clarity, consistency, and feedback. Clarity can be achieved by using appropriate fonts, colors, icons, and images while avoiding clutter. Consistency should be maintained by using the same style, format, and language throughout your information system. Feedback should be provided to users with cues, hints, and confirmation through animations, transitions, and sounds. Following these principles will make your data easy to read, recognize, and interact with.
The way to present your information architecture will depend on your audience, the nature of the project and the type of information that needs to be communicated. For examples, you can have a data layer present in sitemaps, wireframes, flowcharts, Entity-Relationship Diagrams (ERDs), priority guides, Data Flow Diagrams (DFDs), content blueprints, Content Inventories and Audits, Concept Maps... and more.
Finally, you need to evaluate and improve your information architecture. This involves testing, measuring, and refining your information system based on the feedback and the performance of your data. To do this, you can use user testing to observe and interview your users as they use your information system. Collect their opinions, comments, and suggestions with scenarios, tasks, and questions that reflect the real use cases and goals of your data. Additionally, track and analyze the behavior and the outcomes of your users with analytics. Collect data on their actions, interactions, and conversions with metrics, reports, and dashboards that reflect the key performance indicators and objectives of your data. Finally, implement and experiment with changes and improvements to your information system based on the insights from user testing and analytics. Use prototypes, mockups, and wireframes to test and validate ideas before launching them.
Edward Tufte is a pioneer in data visualization, where any of his books provides examples and a masterclass in how to make the insights and inner relationships of data obvious and understandable by the reader. Information architecture is busy with organizing information; but making the insights understood (and actionable) is a matter of visual communication.