Dashboard design: a view sufficient for action
A dashboard is not a place to hold all data. It is where viewers immediately know what they need to do next.
A good dashboard is one that helps viewers grasp the situation and detect anomalies at first glance, not one with the most charts. To achieve this, you need to clearly identify who the viewers are, what decisions they need to make, and which metrics truly need to appear on that screen. The rest, including layout, visual hierarchy, and alert thresholds, serves a single question: can the viewer look at it and understand immediately?
- The goal is to monitor periodically to detect anomalies at a glance.
- need thresholds and visual signals for viewers to immediately know what is noteworthy
- turn the monitoring dashboard into a detailed analysis tool, losing both objectives
- stuffing too many charts and excessive decorations drowning out key metrics
A well-designed dashboard does not come from intuition. According to Stephen Few in Information Dashboard Design, the skill to handle the unique challenges of dashboards is learned. This is also why many dashboards look beautiful but are ineffective in practice. Sinh Vũ approaches the issue from the decision-making question first, then considers layout and form.
Who does the dashboard serve and for what purpose?
Before drawing any box, you need to answer: who is the viewer of this dashboard and what decisions will they make based on what they see? An operations manager needs to see different information compared to a CFO or a customer service representative. The same data set requires different perspectives, priorities, and alert thresholds for each role.
Skipping this step often results in a dashboard that tries to serve everyone and ultimately does not clearly help anyone. Each dashboard should have a primary user group with a clear monitoring goal.
Choose the correct indicators and order of priority.
Not every metric needs to be present on the monitoring dashboard. The important metric is the one that, if it changes unusually, the viewer needs to know immediately to take action. Other metrics can be kept in a separate analysis table or opened upon request.
The order of priority is equally important. The human eye scans from top to bottom, left to right. The most important elements must be in the first visible position, not hidden in the middle of the screen or at the bottom corner.
- Which indicators signal the overall health of the system or business operations?
- Which indicators require immediate action when there is a fluctuation?
- Which indicators should be reviewed periodically, rather than continuously monitored?
Select the correct chart type for each type of data.
One of the most common technical errors is choosing the wrong type of chart. Charts are communication tools, not for decoration. Each type is suitable for a different kind of question.
Comparing between categories: A horizontal bar chart is often easier to read than a pie chart when there are more than three categories, as the human eye finds it easier to read lengths than angles.
When data is a simple ratio with only two parts, a pie chart can be used. But when there are many parts, switch to a bar chart or a table with color highlights.
Threshold and signals: help the eye recognize quickly
A standalone number does not convey anything. Viewers need context: is 500 orders today good or bad compared to last week, the monthly target, or the same period last year? Thresholds and comparisons turn numbers into signals.
A well-designed dashboard harnesses the power of visual perception to effectively and clearly convey a dense set of information.
Stephen Few, Information Dashboard Design
Color is the strongest signaling tool, but it must be used with principles: green means normal, yellow means to monitor, red means immediate action is needed. Do not use color merely for decoration, as it loses its warning value.
Common mistakes when designing dashboards
- Stuffing too many charts: Eyes don't know where to look first, and important metrics get lost in the crowd.
- Transforming a monitoring dashboard into an analytical tool: when trying to cram both functions into one screen, users cannot quickly grasp the situation. They also cannot analyze thoroughly.
- Lack of visual hierarchy: everything has the same font size, color, and visual weight. Viewers spend extra time sorting priorities in their minds before they can read the content.
- Excessive interaction: filters and drill-down features are useful when they truly serve decision-making. However, if added just because "it would be nice to have," they dilute the main message and make the dashboard unnecessarily complex.
The viewpoint of Sinh Vũ
Sinh Vũ designs the part that people look at and understand immediately: layout, visual hierarchy, alert thresholds, and how to choose and place charts. The data pipeline and technical systems at the backend are the responsibility of your technical team. Sinh Vũ collaborates with that team to ensure the dashboard runs on real data, but the division of responsibilities needs to be clear from the start to avoid misaligned expectations.
The starting point is always the decision-making question: what does the viewer need to see to take action? The answer to that question will lead to all remaining design choices: which metrics appear first, which colors are used for alerts, and what needs to be hidden to avoid clutter.
Decision checklist
Topic: Designing dashboards and data control panels. Sinh Vũ guide, sinhvu.com
Tick each item that applies or that you can already answer, then print or save as PDF to take with you.
If you have marked most of the signs above, this is the time to discuss in more detail. Sinh Vũ can help you review and propose a direction.
References
Stephen Few, Information Dashboard Design (ISBN 978-1938377006). Practical experience from Sinh Vũ Studio.
Frequently asked questions
Is there a difference between a monitoring dashboard and an analytical reporting dashboard?
The difference is clear. A monitoring dashboard serves to quickly grasp the situation and detect anomalies without needing to dive deep on the spot. Analytical reports, on the other hand, require users to take time to read, filter, and delve into each number. Combining both into one screen often undermines both objectives.
How many metrics are appropriate for a dashboard?
There are no hard numbers, but the principle is to include only those metrics that, if missing, would prevent the viewer from making the right decision. If you are hesitating between 'necessary' and 'nice to have,' keep the 'nice to have' in a separate table or an extended filter.
This article is for reference. The scope, pricing, and specific commitments of Sinh Vũ are detailed in the proposal and signed contract.