Planning Using SAP Analytics Cloud

With SAP Analytics Cloud, you can perform a range of planning operations such as scheduling tasks, using predictive features to kick off forecasts, carrying out data entry and version management, and writing powerful scripted calculations. You can collaborate with your team to ensure that everyone’s aligned and get more value out of your plan.

In this course, we focus on the manual planning functionality in SAP Analytics Cloud for planning.

SAP Analytics Cloud stories that are based on planning-enabled models are used to execute planning activities.

If you add a table widget in a story that will be used for planning, then extra planning tools are available for you to use.

Note

Remember, your screen resolution and zoom affects where items are located in the SAP Analytics Cloud toolbar. In the previous example, the Tools options can be seen in the toolbar, however, with a lower resolution, they can be found in the option in the toolbar.

In planning stories, you can use comments and discussions to collaborate with teammates.

There are advanced planning features such as data actions, simulation tools, and process control that are covered in the Leveraging Advanced Features in SAP Analytics Cloud for Planning course.

Tables can be used to view and analyze data and are added to either responsive or canvas pages in stories.

For tables that are based on models, the set of features and options available depends on the model type (planning, analytics, or a model based on a remote SAP HANA system). Only the features and options that are supported by the model type are visible. For example, tables based on planning models allow users to make changes to the model data using version management, data entry, and allocations; but tables based on analytic models are read-only.

When you add a table to a story, a data grid is created with the basic dimensions and categories of the model aligned along the axes of the grid. You can change this basic layout using the following designer tools:

• Use the Builder panel to select the measures and dimensions to include in the rows and columns of your table.

• Use the Styling tools to format the presentation.

• Use the Data panel to view all data sources used by your story, and all objects in each data source.

You can add multiple measures and multiple dimensions to your table. When measures or dimensions are part of a hierarchy, you can expand them and select their level. If a dimension has properties associated with it, you can display those in the table, even without the dimension being present in the table. You can also apply filters to your measures and dimensions. The table is updated as you make your choices in the builder, styling, and data panels.

The following example notes some of the options available to you when configuring the table.

In the Reporting section of the builder panel, you can see the Auto-size and Page Table Vertically setting, which can be used to scroll through the rows of a long table in View mode. The table will expand or shrink automatically. If necessary, the application will split the table over multiple pages to fit the content.

The Data panel provides you with drag and drop functionality to build your tables and charts. You can also drag and drop to the Builder panel.

You can display a bar chart in your table cells so that you have both a visual and a numeric view of your data. In the table, right-click a column or row header containing a measure or member of an account dimension, and then select In-Cell Chart.

You have been tasked with quickly understanding complex planning data in SAP Analytics Cloud and you need a way to rapidly extract meaningful insights and share them with your team without extensive manual analysis. You can use the SAP Analytics Cloud, AI-assisted prompt insights feature to accelerate your data analysis and decision-making process directly by adding the widget to your SAP Analytics Cloud planning story. This allows you to analyze your planning data in context, alongside your existing visualizations and tables.

The widget is designed to generate intelligent, data-backed business insights. It achieves this by combining your planning data analysis with real-time web search capabilities, leveraging a large language model (LLM). Essentially, it acts as a smart assistant, helping you make sense of your data faster and more efficiently.

The primary benefit of using AI-assisted prompt insights is to significantly speed up your data analysis process. Instead of manually exploring every data point, you can simply ask the system a question in natural language. The AI then processes your data and provides relevant insights, saving you valuable time. This also makes it an excellent tool for quickly sharing key insights with stakeholders directly within a story, fostering better collaboration and informed decision-making.

AI-assisted prompt insight widgets can be added to a planning story by:

1. Selecting Add in the story toolbar, as shown in the following example.
2. Dragging and dropping the widget from the Assets in the left side panel onto your story canvas.

Once it is added, you link it to a table and configure it in the Builder panel.

1. AI Prompt Insights based on: This is table to be linked to the widget.
2. Scenario Type: To help you get started quickly, there are two built-in scenarios with predefined prompts: Performance Review and Risk Analysis. However, you also have the flexibility to create your own custom scenarios to suit your analytical needs by selecting the Custom Prompt scenario type.
3. Visible Prompt: This is the user prompt and is visible to the user in the story's View mode. It's typically a concise question or instruction that guides the AI's analysis, such as "Review Q4 financial results" or "Analyze travel expenses."
4. Hidden Prompt: This is the detailed instruction sent to the large language model (LLM) behind the scenes. It is hidden in View mode and forms the foundation of the widget's analysis. As a story builder, you must ensure your system prompt is as detailed and specific as possible to elicit good, relevant insights from the AI. For example, a system prompt might define a persona for the AI (for example, "You are a risk analysis assistant") and specify the desired output format or focus.
5. Settings: You can select whether you would like the widget to retrieve content from external sources. If selected, source information is included in the insight, and if you want to find more about where the information was retrieved, select Sources to expand the footer and find links to specific articles.

If you are not satisfied with the initial results, or if you modify your prompt, you can choose Regenerate in the widget to get new insights. Similarly, if the underlying table data changes, a warning icon appears, indicating that the insights might be outdated.

When you link a table to the AI-assisted prompt insights widget, the data from that table is sent to an LLM provider for analysis. SAP Analytics Cloud automatically applies data masking to certain personal identifiers to protect sensitive information, for example, data related to profile-person, profile-credit-card-number, profile-phone, and profile-email.

However, it is critical to understand that your data might contain other sensitive or confidential information, such as gender or organization details, that is not automatically masked. As the user, you are responsible for the data sent externally. Therefore, always ensure that no sensitive or confidential data is included in the table you link to the widget before generating insights.

View Data Masking in the SAP Help Portal for more information and the full list of personal identifiers that are automatically masked.

• The SAP Analytics Cloud, AI-assisted prompt insights feature uses AI and LLMs to generate data-backed business insights from planning data, allowing you to speed up analysis and provide faster insights.
• To generate an insight, you link a table to the widget, provide a natural language prompt (both user and detailed system prompts), then start the insight generation.
• You can use built-in scenarios and custom prompts.
• You can refresh insights when data in the tables changes.
• Data masking is automatically applied to some personal identifiers, but you remain responsible for ensuring other sensitive data is not included in linked tables.

You can also use stories created for you. In the following example, you can see the Rapid Financial Planning and Analysis for SAP S/4HANA story landing page. This is an example of the prebuilt content available in the SAP Analytics Cloud Content Network that administrators can access. These stories can be customized, depending on business requirements.

This topic is covered in more details in the optional lesson Using SAP Content Network Business Packages.

Extended stories are created by story developers using advanced mode in SAP Analytics Cloud. These stories use scripting to add customized behavior to standard story widgets.

When you interact with the story widget, then the associated scripts are executed. In the following example, when you select a value in a dropdown, then a script filters the data by the value you select.

Extended planning stories can range from dashboards to highly dynamic and customized planning stories. They can be tailored for specific use cases where there are complex user interface requirements and can be useful for guided planning and approval workflows.

SAP Analytics Cloud extended planning stories are covered in more detail in the Designing Extended Planning Stories in SAP Analytics Cloud course.

With SAP Analytics Cloud, add-in for Microsoft Excel, SAP Analytics Cloud data can be imported into Microsoft Excel, where you can then continue your analysis. In this example, you can see the additional SAP Analytics Cloud tab displayed in the Microsoft Excel ribbon as well as sample formula functions available.

SAP Analytics Cloud, add-In for Microsoft Excel is covered in more detail in the Creating Workbooks Using the SAP Analytics Cloud, Add-in for Microsoft Excel course.

SAP Analysis for Microsoft Office, commonly referred to as Analysis for Office, is a Microsoft Office add-in that allows multidimensional analysis of SAP data sources, including SAP Analytics Cloud. It consists of plug-ins for Analysis and Enterprise Performance Management (EPM). These Microsoft Excel files are maintained by the business users.

The SAP Analysis for Microsoft Office add-in is covered in more detail in the Discovering SAP Analysis for Microsoft Office course.