Dashboard design: Examples and best practices

Dashboards, or Liveboards, as we call them, are essential for understanding data, sharing insights, and making data-driven decisions. But the art of building a successful dashboard requires more than just picking the right charts, graphs, and colors. 

To create a useful tool for your organization, you have to have the right data, serve the right insights, and build it all in a way that will leave users coming back for more—instead of wasting your time building a dashboard that will never see the light of day. These are the dashboard design best practices you need to follow to ensure your data designs deliver valuable insights every time. 

Table of contents:

The first step is identifying who will be using the dashboard and how they will interact with it. Your user persona should include their technical backgrounds and relevant use cases. This foundational understanding helps you tailor the dashboard to the user and deliver valuable insights. 

For instance, no two sales executives will use data in the same way. One may seek a high-level overview of sales performance to identify growth opportunities, while another may investigate specific regional trends to optimize sales tactics. A one-size-fits-all dashboard design won't meet their needs; they require tailored dashboards that deliver relevant insights.

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Because each dashboard serves a unique purpose and audience, it is crucial to choose the type of dashboard that best aligns with your user’s specific needs. The four most common dashboard types include:

Operational dashboard

Operational dashboards help leaders and managers keep a pulse on day-to-day business activities. These dashboards are typically generated weekly or monthly, helping executives understand what’s happening across business functions to support faster, smarter decision-making. 

Tactical dashboard

Tactical dashboards help managers and executives oversee the performance of specific projects, departments, or processes. They offer granular insights into project progress, team performance, or departmental efficiency.

Analytical dashboard

Analytical dashboards are built to facilitate detailed data analysis, allowing users to explore various dimensions and metrics. They’re typically used by data analysts who dig deep into the data to uncover insights, trends, and patterns. 

Executive dashboard

Executive dashboards offer leaders a near real-time view of their organization’s performance, focusing on high-level metrics that reflect strategic goals and objectives. They provide a holistic view of how well business activities are going, helping leaders identify innovation opportunities and improvement areas.

Too many data points and KPIs on your dashboard can distract users and cause "information overload," making it hard to focus on insights. To avoid these pitfalls, it's important to identify the right set of KPIs to guide users to the information they need. 

For example, if you’re planning to build a customer experience dashboard, tracking KPIs related to product usage data, sales data, and customer feedback makes sense. However, you wouldn’t include a metric on employee experience because it doesn’t fit the context.  

With the most relevant KPIs identified, the next step is choosing the right type of charts to present information in an accessible and understandable way. Identifying the right visualizations will allow you to craft a compelling narrative and ensure your messaging resonates with users. However, with dozens of data visualizations out there, it’s best to understand the nuances of each type so you can choose the one that suits your dataset. Here are five main chart and graph categories: 

Comparison Charts

These charts are ideal for comparing values, trends, and performance across different groups or time periods. Typical examples include bar charts, line charts, and bullet charts. 

Composition charts

Composition charts display data in compositions or proportions. Users can understand the proportionate distribution of data and how components contribute to the total. Common examples include pie charts, tree maps, and stacked bar charts. 

Distribution Charts

Distribution charts show how data is spread across a range of values. They generate shapes and patterns communicating key insights, such as mean, median, range, outliers, data tendencies, variabilities, and skews. Some examples include histograms, scatter plots, and box plots. 

Time series charts

This type of visualization illustrates data points at successive intervals of time, helping users identify trends, patterns, and seasonal variations. Common examples include Gantt charts, area charts, and time-series plots. 

Relationship charts

Relationship charts are ideal for exploring relationships and patterns between two continuous variables. Users can identify trends, correlations, or potential clusters in the data. Top examples include heat maps, bubble charts, and network diagrams. 

When designing a dashboard, it’s important to follow UI/UX principles so users can easily spot what matters most at first glance. By taking these steps, you can ensure that your data story is easy to understand and interpret.

Here are some important design principles you should consider integrating into your layout:

Use white space effectively

Too much white space can make the data difficult to read, while too little can make the layout busy. The goal is to create just enough breathing space while highlighting your most important points. 

Take a look at this Liveboard. By drawing the viewer's attention to the most critical data elements, it doesn’t overwhelm users with visual “noise.”:

Consider visual hierarchy

Visual hierarchy is the principle of arranging elements to show their order of importance. To do this, use alignment and composition to add adequate spacing between elements and highlight important visual elements through size or color. 

The example below showcases a clear visual hierarchy, which makes it easier for users to grasp critical KPIs and make informed decisions about churn trajectory:

Choose a consistent color palette 

Colors influence our perception in more ways than we think. Consider both the message you're trying to communicate and the type of data you're working with.

For instance, visualizations with red, yellow, and green coding can help users identify strengths and problem areas. On the flip side, using trend lines with different colors will reflect whether performance is improving or worsening. However you decide to leverage color, the most important quality is consistency.

Timeliness, accuracy, and trust are the pillars of an effective dashboard design. But to achieve these, you need modern dashboard tools that facilitate effective communication and collaboration. 

For instance, using ThoughtSpot, analysts like you can leverage features such as Notes to collaborate and share important context or takeaways with stakeholders. You can also share Liveboards across business teams to verify data or present it as a slideshow to tell the data story interactively. This easy sharing enables faster cross-functional collaboration and alignment on shared goals. 

 

Having explored various dashboard design principles, it’s time to look at how they can be applied across industries using these dashboard design examples:

From preventing stockout costs to optimizing sales performance, retailers have to stay on top of critical KPIs. That’s why they need an intuitive dashboard design that offers a clear, dynamic snapshot of their online store performance.

With ThoughtSpot Liveboards, you can consolidate various sales-related data points into a single, comprehensive store performance dashboard. This empowers busy retailers to identify performance gaps and gain insights into customer behavior. The user experience is further enhanced with built-in interactive features such as drill-down, filtering, and AI-assisted analysis, allowing retailers to explore data in more detail.

In the finance world, numbers matter. But just crunching numbers is not enough, it’s also critical to identify trends, patterns, and anomalies to understand what’s impacting the bottom line. A well-designed dashboard offers a clear visual representation of KPIs to help finance leaders know which data points to focus on in order to analyze the economic health of their company.  

In this example, leaders can leverage Liveboards to gain real-time insights into important metrics such as the growth of clients and total asset value to assess overall financial position.

 

Efforts to optimize manufacturing processes rely heavily on real-time data visualization. Luckily, modern solutions like ThoughtSpot empower manufacturers to monitor real-time KPIs through interactive visualizations and search for insights just as they would ask questions on a search engine. 

For instance, visualizing monthly spending data across departments can offer manufacturers valuable insights. With visibility into the breakdown of expenses by department and category, users can identify cost-saving opportunities and maximize profitability.

 

For the past three decades, legacy dashboard solutions have turned capable data teams like yours into operationalist specialists—taking up valuable time that could be better spent as strategic business advisors. Luckily, in this GenAI-powered data world, analysts can finally break free of the BI backlog and automate tedious tasks. With ThoughtSpot as your analytics partner, you maintain granular governance controls and build Liveboards that deliver smarter insights.

This was the case for Matillion. The implementation of ThoughtSpot led to an 80% elimination of report requests that were previously burdening the data team. It also enabled analysts to redirect their efforts towards strategic endeavors, creating £75,000+ in annual cost savings. 

See for yourself how ThoughtSpot can make power users more productive and help business users serve themselves—schedule a ThoughtSpot demo.