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What is a Business Intelligence Dashboard?
A Business Intelligence (BI) dashboard is a visual representation of key information necessary for measuring, monitoring, and managing business success.
In this context, Business Intelligence (BI) refers to the systematic collection, analysis, and evaluation of company data. Key Performance Indicators (KPIs) and other relevant information are consolidated within a BI tool (e.g., SAP BW or SAP Analytics Cloud) and presented visually through graphics, charts, diagrams, and tables.
Why should you use Business Intelligence Dashboards?
There are many reasons why BI dashboards should be used in a corporate environment. Below are the key benefits:
- Essential information is presented transparently and tailored to the target audience.
- Dashboards provide management with insights into company or department performance and serve as a tool for achieving (strategic) goals.
- Weaknesses and risks can be identified more quickly.
- They facilitate dialogue between employees across different departments and hierarchical levels.
- They improve employee motivation and productivity by enabling measurable success tracking.
By focusing on the necessary KPIs and controlling indicators, dashboards highlight the company’s key information. From analyzing individual KPIs to monitoring complex processes, dashboards can be used for corporate management. The decisive factor is a user-oriented design that ensures high usability.
How do BI Dashboards differ from BI reports?
To understand the difference, it is first necessary to define what a BI report is. Reports are detailed and comprehensive representations of data. They are generated at regular intervals and provide specific information.
The key differences are outlined below:
What key features should Business Intelligence Dashboards have?
Modern BI tools, such as SAP Analytics Cloud, offer a range of essential features that a BI dashboard should include.
- Access to real-time data
- Integration of data from various sources
- Customizable interface
- Interactive data exploration
- Sharing options for other users
- Export functionality for further processing in other tools (e.g., MS Excel)
- AI support for data search and interpretation
- Mobile device compatibility
What are the benefits of Business Intelligence Dashboards?
Using a BI dashboard offers several advantages for both small and large companies, including:
- The presentation of complex data can be visualized in a simple and understandable way.
- Data can be effectively and as needed shared with various stakeholders. Through target group-oriented layouts, users receive only the information that is relevant to them.
- Data from different sources can be illustrated together.
- Time savings, as all relevant information (possibly from different sources) is immediately visible.
- Self-service tools (such as SAP Analytics Cloud) offer the possibility of easy creation and interactive use. This allows employees with little IT affinity to analyse relevant information and build their own small dashboards using standard functions.
- Trends can be specifically identified early and analysed more quickly. Users can recognise problems, determine causes, and then react accordingly.
- Through interactive approaches, further scenarios can be analyzed more closely during dashboard usage.
How should the design of Business Intelligence Dashboards be structured?
A successful dashboard is based on solid information design. It is essential to ensure a consistent color scheme (CI) and appropriate visualisation of charts and tables. Additionally, interactivity and usability play a crucial role, as they are key factors in achieving user acceptance.
The layout of a dashboard should follow a “Z-shaped” structure, allowing users to absorb the content in a natural reading flow. The key aspect here is the positioning of elements and their visual prominence.
In the reporting environment, there are many goals and guidelines to consider when creating dashboards, including the SMART guidelines and the SUCCESS rules.
SMART Guidelines
- S: Synergetic –> Ergonomic and efficient design
- M: Monitor-KPIs –> Display of decision-relevant KPIs
- A: Accurate –> Precise and correct representation of data
- R: Responsive –> Feedback on the situation through notifications and thresholds
- T: Timely –> Presentation of the latest information
SUCCES Rules according to Hichert
- S: SAY –> Express the message correctly
- U: UNIFY –> Apply notation standards
- C: CONDENSE –> Increase information density
- C: CHECK –> Ensure visual integrity
- E: EXPRESS –> Choose appropriate visualisation
- S: SIMPLIFY –> Avoid unnecessary information
- S: STRUCTURE –> Organise content effectively
Storytelling-Mantra
In the 1990s, Ben Shneiderman studied data visualisation and summarized his findings in a Visualisation Mantra (also known as the Information Seeking Mantra).
The key insight was that information derived from analyses, which often start at a highly granular level, can no longer be unequivocally placed within the overall context. As a result, strategic analyses and decisions may become distorted.
From this realisation, three levels were established to improve data representation:
How can I create a BI Dashboard in SAP Analytics Cloud?
Prior Considerations on Presentation and Design (Mock-Up)
- Before creating a SAP Business Intelligence Dashboard, it is crucial to define its purpose and objectives. Different target audiences require different visualisations—for example, a marketing dashboard serves a different goal and has a different layout than a cost center dashboard. A mock-up helps create an initial visual representation. The key figures and attributes to be used serve as a guideline, assisting users in navigating the dashboard later.
Creating the Story
- The Story is the central element of SAP Analytics Cloud (SAC). It serves as a dashboard interface that allows you to tell the story of your data.
- Since last year, it is no longer necessary to decide beforehand whether the self-service functions of the Story are sufficient or whether custom visualisations using scripting in the Analytical Application are required. This preselection has been replaced by the Unified Story, which combines the advantages of both approaches into a single interface. This allows both simple and complex dashboard implementations within one environment.
Integrating Data
- At this stage, data can be imported from various sources. To enable real-time data retrieval, a live connection to a source system (e.g., SAP S/4HANA or SAP BW) should be established. Alternatively, data can be directly imported from local files.
- Using an existing query, a CDS view, or data modeling within SAC, a data model can be created. A Story can incorporate multiple different data sources, and the widgets (such as charts and tables) can be linked together, providing users with a seamless experience.
Data visualisation
Once the data is integrated, the visual design process begins. SAC offers a wide range of widgets, including charts, tables, maps, and R-visualisations, ensuring an optimal representation of data.
Each visualisation type comes with various customisation options to meet specific business requirements. The following image illustrates the different types of charts available for use.
Adding the required filters and defining dependencies
- For better analysis, filters are available that allow the user to focus on the most relevant data. Various types of filters are available in SAC.
- Story filters, page filters, and chart filters are the most important in this category. Story filters are applied across the entire Story (e.g., a date filter that applies to all displayed data and pages). Page filters are defined specifically for the respective Story page. Additionally, a chart filter can be applied, which controls the displayed data of a particular chart.
- To ensure interactivity, charts can also be linked using “Linked Analysis.” If a filter is applied to one chart, the display of the connected widget will adjust accordingly.
- Before linked filtering:
- After linked filtering on domestic revenue:
Layout Design
- Once the visual representation through charts and filtering is complete, the layout can be finalized to align with the company’s corporate identity (CI). This includes customizing fonts, colors, scaling, hyperlinks, borders, and more to ensure a cohesive design.
Which BI Dashboards are available in SAP?
SAP Business Intelligence dashboards can be used in many different business areas. The way the gathered information is presented depends on the target audience and the intended outcomes generated from it.
BI-Dashboards for Sales
A wide range of sales-related information can be displayed in a dashboard. Key data points include existing sales activities, sales regions, lead activities, and daily sales developments, all of which need to be presented in different ways.
The following demo dashboard focuses on order backlog visualisation. Various pages within an SAP Analytics Cloud (SAC) Unified Story are used to display information.
The first page provides an overview of the current order situation, where the most important KPIs are clearly and visibly presented. The advantage of this approach is the ability to directly interpret the figures.
A timeline chart allows for a more detailed time-based analysis of order entries. The time intervals can be dynamically adjusted in multiple ways, such as using the bottom timeline, date input, or selecting a specific time range.
Additionally, bar charts function as linked filters, meaning that selecting a bar dynamically adjusts the view of other charts within the dashboard.
The third page serves as a detailed view, where all relevant information is listed in a clear and structured table. Users have the option to jump from the first page with the corresponding filter applied.
Table columns can be shown or hidden dynamically, allowing users to customize the view based on their needs. This ensures that only the most important results are displayed, which can then, for example, be exported to Excel for further processing.
BI-Dashboards for Finance
In the finance sector, a wide range of KPIs must be monitored. Typically, these are presented across different dashboards. For example, a CFO may require a comprehensive company overview, whereas a cost center manager only needs information related to specific cost centers. Additionally, financial dashboards can be categorised into different topics, such as cash flow, liquidity, and balance sheets.
The following section presents a demo financial report featuring a balance sheet and a profit and loss statement. On the first page, the most important KPIs are highlighted and graphically visualised.
However, since financial analysis often requires tracking developments over a certain period, the second page features an overview table displaying all KPIs within the company.
The next page provides balance sheet information on the opening balances, the respective changes, and the closing balances for each month up to the current month. Here, the user can conduct a detailed analysis of individual items per period and, if necessary, take further actions based on the insights gained.
Finally, the last page presents a monthly overview of the profit and loss statement. Typically, this table is displayed on a rolling basis, showing only year-to-date (YTD) values.
At this stage, it is also possible to include budget figures, prior-year values, or forecast data, providing users with all the necessary details in a single overview.
Conclusion
A BI dashboard is a crucial tool for presenting information visually and interactively to users of various skill levels, enabling them to make informed decisions. By focusing on key business areas, companies can benefit from early detection and correction of negative trends, as well as a clear and easily understandable presentation of critical business metrics, providing significant value.
With modern BI tools like SAP Analytics Cloud (SAC), dashboards contribute to more efficient workflows. SAC offers the flexibility to connect both SAP and non-SAP systems, consolidating data into a single, integrated dashboard. A well-structured visualization enhances both data clarity and flexibility, improving decision-making capabilities.
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