Dashboarding Fundamentals — Prerequisites, Process & Designing Best Practices
Are you someone starting with your very first dashboard? Feeling hard to streamline your thoughts and take the very first step? Well, you are at the right place! No matter what visualisation tool you use, whether Looker, Tableau, Data Studio, Power BI, or any other tool, I am confident this article would be a great help!
PREREQUISITES
Like all celebrated best-seller writers, who give a deep thought about the topic at hand before even picking up that pen, it is crucial to think about what you are trying to portray on your dashboard. Before you start with your dashboard design -
Ask yourself these questions!
- What is the purpose/ business use case we are trying to achieve?
For example, a business use case can be to create a dashboard to show “FY 2021 PERFORMANCE SNAPSHOT” for your firm. At this point, you can start thinking about KPIs like revenue, headcount, clients signed, etc.
2. Who is the audience?
Your audience can be CEO/Founder, Senior Leadership, or even your team. If you create a Performance Snapshot for a CEO, they might not have more than 30 -60 seconds to grasp all the important KPIs; you need to keep your dashboard crisp and to the point! While a functional leader handling a department in a firm might look for granular details!
3. What are the data requirements to achieve the purpose?
A dashboard is simply a visual representation of data! So having answered the above two questions, you need to assess your data sources and select the relevant ones that serve the purpose and audience.
4. Do you know the ‘BIG PICTURE’?
Purpose — Check!! Audience — Check!! Data — Check!! At this point, you should start visualising in mind the rough draft of how the dashboard should look like, i.e., the ‘BIG PICTURE!’
PROCESS
Having given an initial thought and understanding of the dashboard you want to make, it’s time to understand the process.
Step 1 — Create a BRD (Business Requirement Document)
Have a thorough discussion with your team or end-users to enlist the initial set of KPIs, Layouts, ACL(Access control list), data sources used, usage guidelines, etc. This step is essential to have a consensus among you as a developer and the end-users before moving to step 2.
Step 2 — Create a Prototype
It’s time to put your creative mind to the test! Start creating the prototype version as per the BRD. Play with all possible charts and visualisation options made available by the visualisation tool. Remember, the first version does not have to be perfect! There would be enough revisions, so embrace yourself for the iterations and have patience!
Step 3 — Review & Re-iterate
Review your draft with your dashboard audience. More importantly, tell your story of how the different charts connect with the business use-case at hand! Work on the feedback, update the BRD, revise your dashboard draft, and re-iterate this cycle to get the final approved version!
Congratulations you made so far! One last piece to go with — Designing Best Practices!
DESIGNING BEST PRACTICES
“Know what you are designing!”
A good dashboard design -
- Tells a clear story — Not sure about one? Try ‘SQUINT TEST’
- Helps the audience grasp important information in not more than 30–60 seconds — A CEO might not have more than 30 sec to spare!
- Is easy to navigate and moderately interactive — For example, a metric guide feature on-hover, filters, side navigation bar
- Is arranged in an appropriate order of importance of business acumen — KPIs at the top, related charts at the bottom, and narration notes at the bottom
- Follow the rule of Minimality — Use fewer charts or club specific chart metrics into one chart with effective designs
- Has an appealing use of visuals — A good mix of different types of charts, help texts, images help develop the aesthetic view of the dashboard
- Has consistent use of colors, symbols, and formatting — Example, monetary metrics start with ‘$,’ uniform decimal precision, predefined color palette
- Periodically validate your data sources — Remember, critical business decisions take place based on the data, so it has to be as accurate as possible!
