How to create effective dashboards
Based on our experience in digital product design and development, we propose four steps to create interfaces capable of making data visualization easy and useful.
The term “dashboard” has its roots in automotive tradition, where it refers to the dashboard that displays key information related to vehicle operation. With this information, those driving the car can make the right decisions to get to their destination in the best way possible.
In the context of digital products, the concept of a dashboard is similar: it is a graphical display of important data and information that users can use to monitor the performance and progress of a given system.
Although the context of use is different, the fundamental purpose of a dashboard remains the same: to let users know at a glance what deserves their attention and what action, if any, to take.
However, the importance of proper design has never been greater than it is today. With an ever-increasing amount of data at our disposal, good dashboard design is critical to ensure that users can take full advantage of the potential of this type of visualization without feeling overwhelmed or confused.
As a team at Moze, we have helped companies in a variety of industries present their data in a clear and understandable way, creating dashboards tailored to the specific needs of their users.
In this guide, we will describe how to design effective digital dashboards, focusing on how to make the most important information accessible and understandable, and achieve an intuitive and usable interface.
Here are the key steps we will address in our guide:
- Define the purpose of the dashboard
- Make it easy to understand the data
- Design a usable interface
- Test the dashboard with users
1. Define the purpose of the dashboard
The first crucial step in creating an effective dashboard is to clearly define the purpose of the dashboard. In other words, you need to understand what goal you want to achieve with the dashboard and what information will be presented. This will depend on the type of dashboard you want to create, and generally three basic types can be identified: strategic, analytical, and operational dashboards.
Strategic dashboards are designed to provide a high-level overview of company performance or certain aspects of the business. These dashboards are usually used by executives or corporate strategy managers to make important decisions about the company’s future, so they must provide clear and concise information.
Analytical dashboards, on the other hand, are designed to analyze and interpret collected data in depth to identify trends, patterns, and relationships among the data. These dashboards are often used by data analysts or data scientists to drill down into business performance or to identify areas for improvement.
Finally, operational dashboards are designed to monitor daily business activities and help users identify any issues or situations that require immediate action. These dashboards are often used by operators or technicians to monitor the operation of systems or processes and make timely decisions.
A hybrid dashboard is a combination of the three types of dashboards described above. This type of dashboard is particularly useful for those who need to make decisions quickly and informally, as it provides detailed and immediate information on multiple levels, allowing them to examine and act on situations that require immediate attention, but also to delve into more strategic aspects of the company.
For example, a hybrid dashboard might provide a general view of the company’s financial metrics, such as revenue and profit margin, but also detailed operational information such as production, inventory, sales, and costs. In this way, those using it can quickly identify any problems and make informed decisions in a timely manner.
Regardless of the type of dashboard you intend to create, it is important to clearly define the purpose and objectives of the dashboard from the outset to ensure that the information presented is relevant and useful to end users.
2. Make data easy to understand
The main goal of a dashboard is to make it easier for users to understand the data so that they can make effective and informed decisions with as little effort as possible.
This goal can be achieved through a combination of solutions, including using comparisons, using explicit evaluation indicators, choosing the right level of detail, using appropriate charts and graphs, and using user language.
In this section of the article, we will explore these design techniques in more detail, looking at how they can be applied to create effective and easy-to-understand dashboards.
Choose the right level of detail
Choosing the right level of detail for a dashboard’s data is a key element for its easy understanding. If the level of detail is too high, the dashboard may become too confusing and unclear. On the other hand, if the level is too low, the data may be insignificant and not help the user in understanding the information.
A good way to identify the appropriate level of detail is to think about the type of dashboard you are creating: an operational dashboard will require a much more granular level of detail than a strategic dashboard, and vice versa.
Take, for example, the administration panel of an e-commerce site, with which different users often interact:
- A strategic dashboard intended for managers and administrators will require a high-level view of overall sales. In this case, we might express the value of sales through a line graph showing growth over time, without too many specific details.
- An analytical dashboard intended for marketing and sales teams will need to provide more detail on sold products, customers, and sales strategies. In this case, we might use a bar graph to show sales by product or category, along with a pie chart to represent the breakdown of sales by geographic area.
- An operational dashboard intended for logistics and order management teams, on the other hand, will need to provide specific information on individual orders, shipping times, and products in stock. In this case, we could use an interactive table that allows employees to filter and view only the information that pertains to the orders for which they are responsible.
In summary, in order to identify the most appropriate level of detail, we need to start with the needs of the end users of the dashboard so that the data can be displayed in a way that best suits
Comparing data is often an effective way to help users correctly interpret the information available within a dashboard. Conversely, if data are presented without a defined reference, users may have difficulty understanding the overall trend of the metrics they are interested in and possible areas for improvement.
For example, if a dashboard shows the number of visits to the company’s website without a definite benchmark, users may not have a clear idea of the site’s performance. Conversely, if the data are compared based on defined benchmarks such as visits from the same period in the previous year or targets set as a result of marketing activities, users can make more accurate assessments and make useful decisions to increase visits.
Another example may be the conversion rate of visits into purchases. In this case, comparison with the industry average can provide an indication of the company’s competitiveness in the target market. Similarly, comparison with the set goals allows one to assess the effectiveness of the strategies adopted and possibly improve them.
In both cases, the lack of clear references for comparison can hinder understanding of the data and make it difficult for users to make informed decisions.
Provide explicit evaluation
Another important element in making data easier to understand is to add an explicit evaluation of key information, using clear and easy-to-understand indicators. The goal is for the user to quickly understand whether a particular value is performing well or poorly.
For example, an up arrow icon next to a numerical value may represent a positive increase, while a down arrow may represent a negative decrease.
Evaluative indicators should not be limited to binary distinctions between good and bad, but if they exceed the limit of more than a few distinct states (e.g., very bad, bad, acceptable, good, and very good), they risk becoming too complex for effective understanding.
Use appropriate charts and diagrams
Using charts and graphs is essential to make complex information easily understandable. However, not all charts are suitable for all use cases, and choosing the right type of chart to represent certain data can make all the difference in user understanding.
In order to make it easier to choose the most suitable graph, we can categorize the various types of graphs according to the most common use cases, namely:
Relationship: to show the relationship between variables, such as the relationship between the weight and height of a group of individuals. Some examples of relationship graphs are the scatter plot, bubble plot, and network plot.
Comparison: to compare values between different categories, such as comparing sales of different products in a specific period. Some examples of comparison graphs are the bar graph, line graph, and radar graph.
Composition: to show the division of a whole into categories, such as the division of the business budget among different activities. Some examples of composition charts are pie chart, stacked bar chart, and tree chart.
Distribution: to represent the distribution of data, such as the income distribution of a population. Some examples of distribution graphs are histogram, box-and-whisker plot and density plot.
Use the language of users
When designing a dashboard, it is important to use the user’s language to create an intuitive experience. This means using terms and phrases that your users know and easily understand.
First, it is important to ask what the users’ level of knowledge is with respect to the dashboard domain. If your audience is unfamiliar with technical terms, it is important to explain the concepts in simple, clear language. Otherwise, more technical and specialized language can be used.
Second, it is important to use the same words and terms that users use on a daily basis. This helps make the dashboard more familiar and easy to use. For example, if the company team uses a specific term to refer to a piece of data, it is important to use the same term in the dashboard.
3. Design a usable interface
One of the key elements in creating effective dashboards is usability. A well-designed dashboard must be easy for the user to use and understand, facilitate access to relevant information, and allow for quick data analysis. In this section of the guide, we will discuss some of the best practices for designing a usable interface for dashboards.
Use a single screen
The strength of a dashboard is to show the most important information side by side, allowing the user to get a complete picture of the situation at a glance. This makes it easier for the user to analyze data, detect trends, and reach conclusions, without the need to navigate through different screens or product sections.
Using a single screen is therefore essential to immediately show the user the most significant data and, above all, avoid forcing the user to rely on memory to remember what information was displayed in previous screens.
For example, think of a dashboard representing a company’s performance in different markets. By efficiently using the space of a single screen, the user would be able to see the data for the various markets (such as revenue, sales, profits, etc.) displayed in charts or tables side by side, without having to switch between screens to see the data for each market.
In this way, the dashboard would fully realize its purpose, which is to enable the user to compare different markets with as little effort as possible and to quickly identify any discrepancies or emerging trends.
Use a clear visual hierarchy
As we said at the beginning, before starting to design the interface of a dashboard, it is essential to carefully select the information to be displayed. A dashboard should include only those elements that are essential and relevant to the specific purpose for which it was created, and avoid adding superfluous or redundant information.
Once the information to be shown in the dashboard has been identified, it is important to organize it in a clear visual hierarchy so that the user can devote time to reasoning about the data rather than deciphering how it is presented.
Here are some elements and strategies that can be used to display data in a readable and intuitive hierarchy:
Arrangement of elements by importance: place the most important information, such as the title and key metrics, at the top of the dashboard so that it is immediately visible to the user.
Organizing elements into groups: organize elements into groups based on their relationship. For example, group sales-related metrics separately from marketing-related metrics, using borders and spacing so that the grouping is visually evident.
Using different sizes and styles for typography: use different font sizes and styles to highlight the importance of information. For example, larger, bold fonts for primary information, slightly smaller font sizes for secondary information, and even smaller fonts with larger spacing for numerical data.
Using an appropriate color scheme: use a color scheme that allows users to easily distinguish information based on its importance or significance. In an online sales dashboard, the color green can be used for information about available products, while red can be used to indicate out-of-stock products.
Use of icons: we can use different icons to represent different sections, categories, and states of the data. For example, we could use a bar graph for the sales section, a product icon for the product category, and an arrow icon to represent the increase or decrease in sales. This helps to save space and make the dashboard less monotonous and more intuitive.
Help users drill down
The dashboard plays a central role within many digital products, as it allows the user to get an overview of the most relevant information it contains. For this reason, it must be designed in a way that guides the user to go deeper into the information and thus stimulate interaction with the product.
For example, a dashboard for a fitness app might display the user’s workout statistics such as the number of steps taken, calories burned, and distance traveled. From there, the user could select one of these statistics to get more detailed information, such as the average time taken to cover a given distance. In addition, the dashboard could offer the ability to set workout goals, allowing the user to monitor their progress and stay motivated.
In this way, the dashboard becomes the starting point forthe userstoward discovering the various features of the product and learning more about the data that matter most to them, transforming from a simple static report to an important reference for user navigation.
Send notifications and summaries
Sending notifications and summaries to users of a dashboard is an important practice to keep users informed of the most relevant and up-to-date data. This can be especially useful for organizations that manage large amounts of information, where users may have difficulty keeping track of it by frequently accessing the product.
For example, an e-commerce site might send notifications to users when products are put back in stock or when product prices change significantly. In this way, users can be informed in real time and make informed decisions about their purchasing actions.
Similarly, a financial services company could send daily summaries to its customers, summarizing their account balances and transactions. This can help customers monitor their balances and prevent any suspicious or erroneous transactions.
4. Test the dashboard with users
The dashboard is a key element in the overall experience of a digital product because it provides a concise visualization of the information essential to meet users’ needs.
For this reason, only by directly engaging users, through User Research activities, you can identify the design best suited to meet their needs. Interviews, usability testing, surveys, and analysis of quantitative and qualitative data are some of the most common research tools for gaining this kind of knowledge.
Suppose we want to develop a customer dashboard for an e-commerce site. The testing phase could help discover that users need to see at a glance order history, shipping details, and real-time order status.
These features would help users manage their purchases more efficiently and have a complete view of their shopping activities, thereby improving their site experience and increasing the likelihood of long-term retention.
In conclusion, designing an effective dashboard is an iterative process that requires constant evaluation of the individual interfaces produced, always keeping in mind what the overall end result will be.
At Moze, we are aware that there is no perfect dashboard: every user has different needs and preferences, and every dashboard can always be improved.
For this reason, it is important not to just follow best practices or the latest industry trends. You need to create channels to continuously receive feedback from users and always be open to gathering ideas and experimenting with innovative solutions.
We know the complexity of these types of projects, and we know that it can be easy to feel overwhelmed by the amount of information you have to visualize while trying to design an appropriate user experience.
Need to design a new digital dashboard? Let’s talk. Our team of designers and developers is ready to work alongside you.
As our clients say, effective collaboration and open communication can lead to excellent results.