Essential dashboard design principles — aligned with global standards and SAP's design philosophy — for building successful SAP Analytics Cloud projects.
In the current business landscape where data-driven decision-making determines corporate competitiveness, the architecture of technology is just as critical as the capabilities it offers. Our experience at Notium in Visual Analytics projects demonstrates that success is not merely about presenting the right data; it requires visualising that data in a manner best suited to the user's cognitive processes.
Whether you are constructing a dashboard from scratch on SAP Analytics Cloud (SAC) or optimising existing reports, we have compiled the essential points to consider in light of global design standards and SAP's current design philosophy.
Design Philosophy: Listening and Iteration
A successful dashboard is the product of a listening and experimenting process rather than a purely technical production. During project phases, analyse not only which data stakeholders require but also how frequently, on which devices, and at which decision-making moments they use this data. Rather than aiming for perfection in a single attempt, adopting an agile approach to create prototypes and maturing the design through user feedback will significantly increase the adoption rate within the organisation.
Information Architecture and Focus
Users should grasp the general situation and core message within the first five seconds of viewing a dashboard. Apply the “inverted pyramid” approach: a top layer of critical KPIs and summary metrics, a middle layer of trend analyses and comparative charts, and a bottom layer of detailed tables and granular data. Instead of filling the screen with excessive data, simplifying the layout and strategically using white space reduces cognitive load and facilitates focus.
Colour Usage and Consistency
Colours are not decorative elements; they act as a semantic tool forming the language of the data. Functional colours such as red and green should be used strictly to indicate performance states like increases, decreases, or deviations from targets. Categorical consistency matters too: if a product group is represented by a specific colour on one page, it must remain consistent across all pages, increasing the speed at which users interpret the data.
Technical Nuances for SAP Analytics Cloud
Use Linked Analysis instead of static filters, so charts communicate with one another — when a user clicks on data in one chart, other components filter accordingly, helping users discover the data and reducing filter clutter. Pay attention to lazy-loading principles for performance: rather than loading all data on a single canvas, move detailed data to different pages or sub-reports accessible via page-jump links. Use SAC's Device Preview mode to test how the dashboard behaves on tablets and phones. And choose visuals correctly — line charts for time series, bar charts for categorical comparisons, and keep pie charts to a minimum given the difficulty of comparing angles.
Conclusion and Collaboration
An effective dashboard design acts as a bridge transforming raw data into strategic insight. These principles are a strong starting point for improving standard reporting processes. For complex data models, custom scripting on SAP Analytics Cloud, or advanced planning scenarios, a deeper architectural structure may be required — and Notium would be pleased to collaborate on such advanced projects.
