Effective Data Dashboards

1. Introduction to Dashboards

A dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored. Dashboards are used in various fields, including business, healthcare, and education, to track performance, identify trends, and make data-driven decisions.

There are several key components of a dashboard, and they include:

Drill-down allows users to click on a data point to view more detailed information. For example, clicking on a bar in a sales chart might reveal sales data broken down by product or region. It helps users explore data hierarchies and gain deeper insights without cluttering the main dashboard with too much information. Hover-over (or tooltips) displays additional information when the user hovers their mouse over a data point. This information can include data values, descriptions, or other relevant details. Hover-over elements provide context and additional insights without requiring clicks, keeping the dashboard clean and user-friendly. For example, in a profit margin chart, hovering over a data point might show the exact profit margin percentage and additional notes about that period.

Below is an example of a dashboard titled “Banking Loan Report” for a fictitious bank named MAD Banking, which provides a comprehensive overview of loan data. The key performance indicators (KPIs) are:

• Offered Amount: $15,002,000
• Accepted Amount: $15,882,489
• Number of Loans: 7,937
• Average Accepted Rate: 5.9%

• Map: Displays loan amounts by state, with varying shades of orange indicating loan offered amounts. The darker the orange, the higher the loan amount for that state.
• Bar Chart (Top 10 States): Shows the offered amount by state, with California having the highest amount.
• Heatmap (Loan Term and Risk Rate): Categorizes loans into four risk levels (low (1) to high (4)) and the loan term. The color gradient represents the loan amount, with darker shades of orange indicating higher loan amount. The heatmap shows that the largest amount of loans are in a risk category of 1 with an 11–20-year term.

The type of dashboard you construct should be tailored to the specific needs and preferences of your audience. Here are some considerations based on different types of audiences:

terms to know

Dashboard

A visual display of key information and data points, typically presented in a way that is easy to read and interpret in a single view.

Key Performance Indicators (KPIs)

Numerical values that demonstrate how effectively an organization is achieving its key business objectives.

Drill-Down

The ability to explore more detailed data by clicking on a summary or high-level data point.

Hover-Over

Refers to the interactive feature that displays additional information when a user moves their cursor over a specific element in a dashboard, such as a data point, bar, or line.

2. Poorly Designed Dashboard

Sometimes the best way to determine how or why a dashboard has a poor design is to look at an example of a poorly designed dashboard. The dashboard below is designed to visualize different aspects of business data, such as sales, expenses, and profit.

think about it

Before you continue, take a few moments and examine the dashboard that is presented above. Ask yourself these questions.

• What is the primary purpose of this dashboard? Does it clearly convey this purpose?
• Are the data visualizations clear and easy to understand? Are there any confusing elements?
• Is the design aesthetically pleasing? Does it help or hinder the understanding of the data?

The list below provides you with several design flaws in this dashboard, such as:

• Inconsistent colors: Different colors are used for the same type of data (e.g., sales data is brown in one chart and blue in another), which can be confusing.
• Poor data-to-visualization pairing: A pie chart isn’t ideal when you have many categories with similar percentages because it becomes difficult to distinguish between the slices (categories). When slices are too similar in size, it becomes hard to see the differences between them. This can make the chart look cluttered and confusing.
• No clear hierarchy: There is no clear visual hierarchy, making it difficult to determine which information is most important.
• Busy design: The overall design is cluttered, with too many elements crammed into a small space.
• Annotation: There is very little labeling or guidance for the audience. For example, the side-by-side bar chart has no legend, so the audience does not know what the colors mean. The pie chart does not have a legend for its colors.

3. Principles of Effective Dashboard Design

Hopefully seeing a poorly designed dashboard has motivated you to learn about techniques that can be used to improve the design of the dashboard you saw in the last section. You are going to be introduced to simple yet effective dashboard design concepts in this section. In the next section, you will see the revised dashboard with several of these techniques applied for a better designed dashboard.

Below are several techniques to consider when designing a dashboard.

1. Understand Your Audience

• Identify stakeholders: Know who will use the dashboard and their data needs.
• User proficiency: Consider the analytical/technical skills of your audience.
• Decision-making needs: Understand what decisions will be made using the dashboard.

• Purpose: Determine the primary goal of the dashboard (e.g., monitoring performance, tracking KPIs, etc...).
• Key metrics: Identify the most important metrics to display.
• Actionable insights: Ensure the dashboard provides insights that lead to action.

• Charts and graphs: Use appropriate visualizations (for example, bar charts, line graphs, scatter plots, etc...) based on the data type.
• Avoid clutter: Keep the design simple and avoid unnecessary elements.
• Consistency: Use consistent colors, fonts, and styles.

• Logical flow: Arrange elements in a logical order, usually from top-left to bottom-right.
• White space: Use white space effectively to avoid a crowded look.
• Responsive design: Ensure the dashboard is accessible on different devices (laptops, cell phones, and tablets).
• Clarity and context: Utilize annotations such as titles, appropriately labeled axes, legends, and any short descriptions that help provide context to the data being presented. They can explain trends, highlight key points, or provide additional information that might not be immediately obvious from the data alone.

• Filters and drill-downs: Allow users to filter data and drill down into details.
• Tooltips: Provide additional information through tooltips.
• Interactive elements: Use interactive elements like filters, tooltips, sliders, and buttons for better user engagement.

4. Redesigned Dashboard

Let’s return to our poorly designed dashboard and implement some of the design methods discussed in the previous section. Below is the redesigned dashboard.

The following improvements have been made.

Consistent Colors: The same colors are used for the same type of data across all charts (e.g., blue for sales, orange for expenses, green for profit).

Appropriate Data-to-Visualization Pairing: Bar charts are used for categorical data (sales and expenses by month), and a line chart is used for time series data (profit by month).

Proper Annotation: Legends and titles are added to provide context and guidance for the audience.

Clear Hierarchy: If you want the user to focus on sales, then put sales in the top-left corner of the dashboard. Your audience will read and consume a dashboard in the same way they read a book. The audience will start in the upper left corner and scan to the right. In the poorly designed dashboard, the sales, expenses, and profit were all arranged in the same locations as in the redesigned dashboard. Now the layout is more strategic, meaning with all the design changes described above, the layout is organized to highlight key metrics and trends, making it easier to understand the most important information at one glance.

In addition, you could add tooltips and a filter for some interactive functionality. The dashboard below shows the same dashboard as above, but with some interaction added. You notice the drop-down functionality so that the user can select a certain month or months to focus on. The dashboard will update to only show the months selected. When the user toggles over a data element in the dashboard, a tooltip displays the exact value of that data element (bar, point, line, etc).