UX Audit & Insights
As for most Ontario dashboards, the relevant data is presented in a way that is rather confusing and not intuitive to use. The data insights were more focused on the general overview of COVID-19 and its main indexes in the province (including data on hospitalization and death) rather than on the presentation of the data that may be useful to a user in order to respond to the situation in a certain area.
Understanding what people are talking about regarding the pandemic, I took a brief method to unearth some useful insights from the word cloud from public Twitter data about COVID-19 in Ontario. From this dive into the data, I was able to understand what’s really troubling people the most – things like public health measures, economic impact, and restrictions.
INSIGHT CLUSTERING
Based on the findings, I organized the major issues, turning them into potential opportunities to be explored and grouping the topics by similarity so that the requirements could be analyzed later in the project.
User Profiles
To characterize the exponential behavior of the pandemic was taken as a reference for this project the Susceptible-Infected-Removed (SIR), an epidemiological model based on socio-behavioral factors.
This model allowed me to categorize users into three distinct segments: Susceptible, Infected and Recovered.
User Goals, Tasks, and Actions
Having gained a full understanding of user profiles and having applied the Goals, Tasks and Actions approach I was able to determine the user’s intent, what tasks are required to achieve that intent and what actions the user should take to complete the task and what path they should follow. It was crucial to state these elements for the Susceptible, Infected and Recovered user profiles to steer the dashboard design in the right direction and make sure that the features of the platform are in line with the specific requirements and goals of each of the user profiles.
This way of using data from actions according to user profiles helped me check whether the dashboard was complicated and, therefore, confusing for users or if users had no problems with navigating through it. Out of the available key metrics, we have selected Task Completion Rate and Time Spent on Tasks because these metrics are practical in assessing users' interaction with the dashboard and the efficiency of the dashboard’s features.
Information Architecture
Through a comprehensive understanding of each user profile I was able to identify pertinent features which impacted how our dashboard for information was structured. The dwellers' frequent questions dealt with the new rules, not just receiving updated information about the pandemic. Thus, it was necessary to create a visual representation to facilitate lay users' understanding of the correlation between the pandemic and lockdown rules based on the main insights.
Data representation
Based on the findings made in the first and second phases it was possible to enable users to easily puzzle through several variables in the data sets and to understand how certain data points stand in relation to the general picture. Thus, having found a link between the users’ needs and the data visualization, we were able to effectively present both the relative and absolute values to help users make the right decisions and understand the correlation between pandemic data and lockdown rules.
Defining the containers
I designed the layout of the containers in a continuous flow to facilitate scanning on the dashboard, prioritizing the information in a natural reading pattern, and adhering to the Western left-to-right, top-to-bottom progression on the desktop version. The continuous flow can also improve the user experience by promoting retention, allowing the user to absorb and remember the information presented more effectively. As a result, I sketched a compelling visual approach to represent complex data sets.
Sketches
I first looked at various interests and then started designing, assuming that minimalist design can be easily ported over to the new information. I have chosen to develop different menus as this approach helps to distinguish the data and makes the navigation process smoother, and user can only pay attention to certain data sets. The main goal was to make the navigation between these information blocks smooth and easy, and to make the key performance indicators easy to find. I then created the sketches on the Remarkable 2 after learning the principles of data visualization for data storytelling. Also, I established the visual hierarchy to emphasize the key information in relation to the needs stated. Therefore, it was about the time to move on to the interface once the style guide and the dashboard structure were established.
Style Guide
Applying the principles of Gestalt, this project's style guide has a streamlined and user-friendly aesthetic. Reducing the design to a minimum and using a card navigation also helps to maintain the focus on the key details and to help learn the pattern of the content's relationships easily. The design also includes the modified icons from the Streamline library, to make the navigation through the pages smooth and easy. The monochromatic color scheme with accent of bright colors enhances the contrast and enhances the readability.
User Interface
To potentially reduce cognitive load in order to maximize usability I designed an interface that use monochromatic components to organize information and decrease decision making timing, and hence, emphasize on priority content. Also, for the layout design I also considered one of the Principles of Calm Technology, which is the principle of requiring a minimal amount of attention from the user and making the user not to be overwhelmed with data. Given this, I have reduced the number of elements per session and only highlighting the essential.
DESKTOP VERSION (OVERVIEW)
DESKTOP VERSION (EXPANDED MENU)
MOBILE VERSION (OVERVIEW)
The concept project was fully responsive and customized for viewing on desktops, tablets, and mobile devices, prioritizing access to the essential elements of the dashboard through a visual hierarchy.
MOBILE VERSION (MENU)
Measuring outcomes
To illustrate the potential effect of the COVID-19 Dashboard, I developed an Impact Map by Ryan Scott that shows the relationship between design choices and business and financial outcomes.
At the user level, the dashboard is a tool that helps people make sense of local COVID-19 data more quickly and with less effort. It displays key statistics to enable informed decisions and good community safety behaviors.
From a business point of view, the design should be easy to use so that users are able to find the information they need without having to contact support. This reduces operational pressures and increases trust in the data. Furthermore, the dashboard architecture fosters frequent visits as people come back for the latest information.
From the financial side, the predicted effect includes the costs of reducing the number of unnecessary hospitalizations and the need for additional assistance. Improved public compliance leads to fewer preventable cases, which in turn lead to more effective use of public health spending. These connections are depicted in order to ensure that design decisions are in line with strategic objectives and thus support a user-centred approach.
Refinement and ongoing improvements
Having gone through the needs assessment of the people of Ontario, my initial hypothesis was that a minimalist design in a multi-page dashboard could easily manage the increasing amount of information. This was partly true; however, it was crucial to apply a more systematic and modular strategy for such an extensive and specific dataset.
In the process of this work, I have found several ways in which the result could be improved:
✔ Examining a potential desktop version that would let each chart expand to fill the entire screen, giving the user a better opportunity to study the data in more detail and depth.
✔ Thinking about the process of users’ adaptation to new information and dashboard elements because it can influence how people use the interface and, therefore, how they perform tasks and set goals. To this end, it may be useful to carry out more in-depth interviews in order to reduce cognitive biases and gain more understanding of how to improve the design in future iterations.
The COVID-19 dashboard is an sample design project done for the available dashboards in Ontario, Canada. The topic is still incipient and is being constantly updated, thus, it is an iterative work.
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