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 for you to consider in light of global design standards and SAP’s current design philosophy.

1. Design Philosophy: Listening and Iteration

As highlighted in SAP’s current design approach, a successful dashboard is the product of a ‘listening’ and ‘experimenting’ process rather than a purely technical production. During project phases, it is necessary to analyse not only which data stakeholders require but also how frequently, on which devices, and at which decision-making moments they utilise 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.

2. Information Architecture and Focus

It is essential that users can grasp the general situation and the core message within the first five seconds of viewing a dashboard. We recommend applying the ‘Inverted Pyramid’ approach to ensure this clarity:

• Top Layer: Critical KPIs and summary metrics.
• Middle Layer: Trend analyses and comparative charts.
• Bottom Layer: Detailed tables and granular data.

Instead of filling the screen with excessive data, simplifying the layout and strategically using white space reduces the user’s cognitive load and facilitates focus.

3. Colour Usage and Consistency

Colours are not decorative elements; they act as a semantic tool forming the language of the data.

• Functional Colours: Colours such as red and green should be used strictly to indicate performance states, such as increases, decreases, or deviations from targets.
• Categorical Consistency: If a product group is represented by a specific colour on one page, it must remain consistent throughout all pages. This consistency increases the speed at which the user interprets the data.

Technical Nuances for SAP Analytics Cloud (SAC)

When translating theoretical principles into practice on SAP Analytics Cloud, the following technical details will make a significant difference regarding performance and usability.

Utilising Linked Analysis Instead of static filters, an interactive structure where charts communicate with one another should be established. When a user clicks on data in one chart, other components should filter accordingly; this allows the user to ‘discover’ the data and reduces filter clutter on the page.

Performance Optimisation Attention must be paid to ‘Lazy Loading’ principles to enhance dashboard performance. Rather than loading all data on a single Canvas, moving detailed data to different pages or sub-reports accessible via ‘Page Jump’ links will positively impact system performance.

Mobile Responsiveness The need for executives to access reports from mobile devices is increasing. During the design phase, the ‘Device Preview’ mode in SAC should be actively utilised to test how the dashboard behaves on different screen sizes, such as tablets and mobile phones, and the layout should be optimised accordingly.

Correct Visual Selection Complex visualisations should be avoided. Line Charts are the industry standard for time series, whilst Bar Charts are ideal for categorical comparisons. We recommend keeping the use of Pie Charts to a minimum due to the difficulty the human eye has in comparing angles.

Conclusion and Collaboration

An effective dashboard design acts as a bridge transforming raw data into strategic insight. The principles outlined above serve as a strong starting point for improving standard reporting processes.

However, a deeper architectural structure may be required for complex data models unique to your organisation, developments requiring custom scripting on SAP Analytics Cloud, or advanced planning scenarios. We at Notium would be pleased to collaborate on such advanced requirements and projects.