The analytics dashboards have their roots in the dashboard of a car. Like a car’s dashboard demands well-thought designing, so does an analytics one.
In continuation of Ana’s analysis of launching her first retail dashboard, she heads towards striking off the other dos and don’ts from the checklist of her project.
Below are the further tips to customize and launch your first analytics dashboard.
What Should be the Aesthetics?
Design, Colors, and Fonts
Just a few subtle design considerations can bring the right flavor in a dashboard instead of making it flashy.
As an alternative to represent your data in a table, making a grid layout is easy to comprehend. Whether the objects showing the numbers are arranged in a columnar structure or a row, both are suitable styles. Arrange the objects (graphs, maps, legends, et al.) in either manner, but follow the hierarchy (if any)—top to bottom or left to right—segregating them with borders and minimal background.
Avail the drill-down options in the graphs to zoom in to study in detail. The filters should also shift the focus to granular levels. These options help to bring forth the finer picture while analyzing the statistics and deriving hidden results.
Colors and fonts play a vital role in defining the looks. Do not make the visualization a palette of colors. Use colors in close proximity or from the same family. Too many contrasting colors can dramatize the report and steal the spotlight away from the important results. However, Ana highlights the KPIs with bold and prominent hues to make them stand out. Alongside colors, keep the fonts in proper size; too big fonts can consume unnecessary screen while too small ones are an eyesore.
Easy-to-Read
Apart from the design, the overall look should be comfortable on eyes; too gaudy or complicated report would immediately turn the users off.
A dashboard is destined to derive analogies from the patterns, decipher the reasons where the business is headed, and predict future possibilities. Most of the dashboards are for the C-league teams who run short of time and need quick answers; so, maintain the visualization’s focus and make sure not to hide the meat of the data under wraps. Make it easy to access and understand.
When Should the Dashboard be Refreshed to?
When we talk about Data Analytics Solutions, most analytics projects report real-time data nowadays. Present generations always look towards the future, so historical data of only 1-2 years make sense. Year-on-year reporting nowadays is reducing as users are keen to see more preemptive and predictive analysis than dwelling into the past.
But how fast should data be refreshed for the latest insights? A daily refresh is usually suitable for most of the projects, be it retail, supply chain, pharma, or any other industry. A few sectors, such as telecom, banking might need faster refresh rates. But do not try to pump in the latest data to your dashboards now and then. This affects the whole system and brings down the performance.
Similarly, the dashboard should not take ages to run. The results should come in a few blinks. If this doesn’t happen, review your technology, underlying database, and servers. Also, all the analyses should be available at one click. Users wouldn’t want to fill in long forms with multiple parameters to get to data. So, keep the dashboard fast with limited data by restricting months, regions, and other parameters.
Where Should the Dashboards be Available?
With the right design and data aspects in place, now Ana is ready with the dashboard, and she has to make it available to the consumers. Availing a dashboard in a secured yet easily accessible manner is essential for its distribution.
A dashboard can be sent out on the desired schedule via emails. This limits the dynamic functionality of the dashboard at times. So making it available in a shared place or over the cloud are good alternatives where the users with valid authorization can access and modify accordingly.
The decision to deliver daily, weekly or monthly is also crucial for the distribution.
Superficial to say, compatibility with all the possible devices should be embedded in the dashboards. However, Ana is delighted as Power BI attunes the dashboards automatically according to the device.
Auxiliary Aspects of a Dashboard
Change Management
Often, users new to BI technologies ask for canned reports to serve specific and static data. A sophisticated dashboard can fulfill such radical yet obsolete demands by flipping the filters. However, a few users—who remain attached to the legacy methods—find it difficult to accept this dynamic model.
Also, if all the user inputs are incorporated in the first version in an unstructured way, the dashboard gets cluttered with time, which ultimately brings down the performance. Such changes should be held back for the initial three months, and the consolidated changes requests can be introduced gradually. After all, no dashboard is perfect at inception.
Both the issues can be resolved with change management, which aids the users to educate themselves towards adopting new technology and enhanced systems that deliver a lot in one shot. The program seasons the novice users towards an adaptive mindset to accept the new technology faster and easier.
User Training Manual
Apart from change management, Ana makes sure to integrate a training manual to let the users learn the usage of the dashboards. DIY options in Power BI are great to explore, and user guides should facilitate such learning. More suitable would be to deliver a webinar or video tutorials to make the users comfortable with the new dashboards. This helps them understand the advanced options.
Conclusion
Ana has successfully delivered her sales dashboard to the CEO, the strategy head, and the sales head. The receivers are happy to see a one-stop-shop for all their data needs. By using the best practices for dashboard designing Ana has shared, your project can be implemented smoothly and effectively.