How to build FABULOUS analytics dashboards

In 2004 Stephen Few, a data visualization expert, wrote an article for Intelligent Enterprise magazine that defined a dashboard as “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 at a glance.”

So – how do you design and build fabulous analytics dashboards?

The following is a collection of principles that I have learned from others, and from experience in my dream job as an analytics solution engineer.

Design Philosophy

  1. Actionable Insights
    1. Analytics are only as good as the insights they create and the decisions they facilitate.
    2. The path from visual to action must be short, simple, intuitive, and easy.
    3. People ask for “analytics”, but what they really need to do their job are insights.
    4. Your dashboard should be user-friendly and constitute a basic aid in the decision-making process. Users must simply enjoy using it and consider it an essential tool.
    5. “Two of the greatest challenges in dashboard design are to make the most important data stand out from the rest, and to arrange what is often a great deal of disparate information in a way that makes sense, gives it meaning, and supports its efficient perception.” Stephen Few
    6. “Work smarter, not harder” is a common axiom in the business world. It is also what process-driven business intelligence does for an organization through the automation of decision-making. This automation is accomplished by embedding event-driven business intelligence functions into business processes to reduce the need for a physical action or increase the timeliness of a response. Some key business intelligence elements that can be embedded are data visualization, analytics, alerts, and reports.
  2. Business understanding
    1. A proper quantitative analysis starts with recognizing a problem or decision and beginning to solve it.
    2. Data analytics + Business understanding = Business insights
    3. Wrong questions never produce right answers.
    4. Analytics is all about a business result. It is never about pretty charts or clever science. Data analysis and visualization must lead to accurate insights that generate meaningful action.
    5. Ask, “Who, what, why?” Once you have identified your target user base, it is important to know their intentions, goals, targets, pain points, and success criteria.
    6. It is the nature of feature requests to contain the what, but not the why. But without understanding the why, you risk building an incoherent set of features that address very specific use cases or the needs of vocal customers, without solving the real problems that are common to the majority of your user base.
    7. Self-discovery questions to ask include:
      1. Why does our business exist?
      2. What are our current pain points?
      3. What are our business goals for the next 12 months and 3 years?
      4. What top metrics are currently used in making key business decisions?
      5. What numbers come up regularly for discussion at leadership meetings?
    8. Begin with the business in mind, and maintain this focus all the way through the analytics build process. The analytics engineering team (whether internal or internal) must maintain constant collaboration with the relevant managers, executives and team members right throughout the analytics project.
    9. Successful analytics projects are never turn-key builds. Rather, they are built on a philosophy of continuous development and improvement.
  3. Storytelling
    1. Great analytics tell a story. This story will contain all or some of the following:
      1. Characters. Who is involved?
      2. Plot. What is the story being told?
      3. Surprise. Many analytics stories cause surprise for the audience.
      4. Stress. Sometimes analytics stories create stress for the audience.
      5. Conflict. Conflict may arise over data accuracy; conclusions; blame; strategy;
      6. “Ah-ha” moments. This is when the data story results in discovery. Eureka!
    2. Good design should tell a story with data that does not become overwhelming with way too much information, clutter or noise. Limit content to fit entirely on one screen.
    3. The story should be able to be distilled into one sentence, or even 6-8 words.
    4. A great analytics story will result in clear, actionable strategy.
    5. If the user looks at a dashboard and cannot identify the story being told, it’s time to redesign your dashboard!
  4. Simplicity
    1. Less is more.
    2. It is often tempting to load up a dashboard with lots of important charts and metrics. But:
      1. Too much data on one screen detracts from the story.
      2. A busy, cluttered dashboard causes confusion and hinders comprehension.
      3. The user should be able to get a basic understanding of the data in twenty seconds or less.
    3. It might be better to:
      1. Break up the dash board into multiple pages.
      2. Add toggles that replace two or three charts with one.
      3. Simply remove charts that are not top priority, or add buttons that link to lenses.
      4. Be more ruthless about what stays and what goes!
  5. Intuitiveness
    1. A well-designed dashboard is self-explanatory; it does not require someone to guide the user experience.
    2. Good dashboard flow makes the user experience easy, pleasant and intuitive. Bad flow results in a confused, frustrated user, and that kills adoption.
    3. Intuitive design means that when a user sees it, they know exactly what to do.
    4. Intuitive design is invisible. Intuitive designs direct people’s attention to tasks that are important. In the end, an intuitive design focuses on experience.
    5. If a dashboard is hard to use and confusing to navigate, it won’t get used.
  6. Creativity
    1. An effective and efficient dashboard doesn’t have to be a dull and boring dashboard!
    2. Employ creativity and ingenuity in the areas of:
      1. Colours
      2. Backgrounds
      3. Chart types
    3. Be careful that form does not trump function.
  7. Excellence (International Business Communication Standards)
    1. S AY – Convey a message
    2. U NIFY – Apply semantic notation
    3. C ONDENSE – Increase information density
    4. C HECK – Ensure visual integrity
    5. E XPRESS – Choose proper visualization
    6. S IMPLIFY – Avoid clutter
    7. S TRUCTURE – Organize content

Best Practice

1. W.A.V.E. framework:

  1. Who, Why and What
    1. Get into your audience’s head
    2. Dig deep into how your audience wins
    3. Help them win more
  2. Architecture
    1. Flow – A well-designed flow maps well to how users want to navigate within the analytics app. Once you have a list of dashboards, you need to think about how they all fit together.
    2. Charts – Our brains are wired to interpret visual representations of data more efficiently than a list of numbers. However, to ensure that these visualizations display the right insights, you need to choose charts wisely. Start by asking, “What will provide the most important insights for a particular situation?”
    3. Drill Paths – As you define your layouts and charts, it is important to think how the end user will interact with dashboards to act on the insights they see. An effective drill path aligns with the target user’s mental models.
  3. Visual Communication
    1. Layout – Layout refers to the structure of the dashboard.
      1. Layout is extremely important to visual communication because it guides information organization. We recommend qualifying your dashboard with a “20-second rule”: A target user must be able to get key insights within 20 seconds of looking at the dashboard. This rule will help you prioritize and organize information properly on the dashboard. To create a good layout, we recommend that you focus on sections, order, and size.
      2. Users will read the dashboard from left to right and top to bottom. This is why it makes more sense to place action features like filters on the left or top of the dashboard, and results like charts and tables on the right or bottom. Similarly, if there is a formula or relationship between multiple numbers, it is best to order numbers in the right way to reduce the time required for users to infer and connect these numbers.
    2. Graphic Design – Graphic design is the process of visual communication and problem solving through the use of typography, space, image, and color. Graphic design elements are used to communicate branding, visual identity, emotions, priority, and connections.
      1. Color – Color plays a critical role in graphic design. We recommend considering the four C’s when choosing colors: consistency, context, contrast, and constraint.
      2. Space – White space, by definition, is the space that is not occupied by text, numbers, charts, or other graphic elements. Although it is often neglected, white space can actually provide a significant aesthetic and usability value to your dashboards. It is important not to clutter your dashboards with too much information because high data density reduces the ability to gather insights from the visual and data noise. White space provides a good separator between sections, columns, and charts, and also helps in creating a grid for laying out various dashboard elements. Additionally, white space can help direct a viewer’s eye through the intended flow.
      3. Type – Typeface or font is a key graphic design element that helps highlight important information and also provides a visual hierarchy for written content.
  4. End User Engagement
    1. Embedding Dashboards
    2. Adding Action
    3. Collaborating with Your Team
    4. Collaborating with Distribution Partners
    5. Sharing Externally with Partner Community

2. Ten Dashboard Design principles:

    1. Use the right type of chart: It is important to understand what type of information you want to convey and choose a data visualization that is suited to the task.
    2. Don’t try to put all information on the same page: Don’t create one-size-fits-all dashboards and don’t cram all the information into the same page.
    3. Choose a few colors and stick to them: You can choose 2-3 colors, and then play with gradients.
    4. Make it as easy as possible: If you make the charts look too complex, the users will spend even more time on data analysis than they would without the dashboard.
    5. Good layout choices: If your dashboard is visually organized, users will easily find the information they need; start with the big picture, and ensure that the major trend is visible at a glance.
    6. Provide context: Without comparison values, numbers on a dashboard are meaningless for the users.
    7. Make it simple: Don’t try to be too clever; K.I.S.S.
    8. Be fun and creative: The modern dashboard is minimalist and clean; flat design is really trendy nowadays.
    9. Don’t go over the top with real-time data: In some cases information displayed in too much detail can only be a distraction.
    10. Consider how your dashboard will be viewed: The context and device on which users will regularly accesses their dashboards will have direct consequences on the style in which the information is displayed.

3. Data Integration

  1. Designers must consider what data to use and how to make it available and integrate it into a dashboard solution.
  2. The following aspects of data integration are paramount to the effectiveness of dashboards:
    1. Data access
    2. Data quality and consistency
    3. Data consolidation
    4. Data latency
    5. Impact on operational systems
    6. Implementation time and cost

4. Consider Your Audience:

  1. Ask how a dashboard will be used and designed for next step actions.
  2. What information does the reader need to be successful?
  3. How much detail does the reader need?
  4. What action can be taken and how?
  5. How are exceptions or insights that need action highlighted?
  6. What learned or cultural assumptions may affect design choices?
  7. What do colors mean and can they be visually interpreted?
  8. Which icons are familiar?
  9. Don’t forget to use color blind friendly palettes or icons.

Design ideas:

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