Explaining Liquidity Planning (3L5)

To keep up with the relentless pace of change in the marketplace companies need to make use of data intelligence. It is essential for companies nowadays to connect, orchestrate, and manage large amounts of data. SAP Analytics Cloud helps to foster this change.

Data analytics supports growth. 92% of companies with well-established analytics/Business Intelligence (BI) practices have seen revenue growth of 15% or more over the last three years.

Historically decision-making was mostly linear and static in its nature. The new economy and additional market players become more dynamic with less top-down decision-making and more distributed scenarios.

Today's fast-moving world is very much continuous and augmented in its nature. Intelligent technologies help to reduce some complexity and free up valuable resources from repetitive tasks.

We are shifting from an era of digital transformation into the Intelligence Era, where we are able to accelerate growth and revenue generation by making our organizations more intelligent.

• Businesses are moving from the automation of tasks into an era where technology can be a partner.
• Technology can not only make your business more efficient, but predictive and prescriptive analytics can enable better decision making.
• SAP aims to help all customers become intelligent businesses by providing best-in-class integration across the enterprise.
• Every business customer can make their business an Intelligent Enterprise through our unique approach to bringing BI, planning and predictions into a single cloud solution.
• We have simplified processes across every aspect of business, from the manner in which users get insights to how they buy hybrid solutions.
• The possibilities for innovation are infinite with cloud solutions.
• SAP recognizes that modern analytics is about bringing context to data and automating the uncovering of hidden insights. It's about connecting to data no matter where it is, in a secure way. We are anticipating the needs of the users of tomorrow and providing innovative solutions.

How Is the Intelligent Enterprise relevant in the space of analytics?

SAP will embed intelligence into every aspect of a business's processes, from front-line applications all the way through to key information used by senior executives to make strategic business decisions. With an integrated suite of intelligent solutions, every line of business is equipped with the right platform, technologies, and applications to thrive in the Intelligence Era.

• Embedded Intelligence allows your front-line employees to make better day-to-day decisions relevant to the applications with which they interact. With an intelligent suite of applications, your organization can focus on critical days sales outstanding (DSO) items, identify at-risk opportunities, and flag employees who are at risk of leaving the business.
• Open Innovation, utilizing intelligent technologies like SAP Analytics Cloud, allows your organization to evaluate both internal and external data to predict business outcomes. Optimizing the day-to-day is important, but intelligence and new technologies can have massive impacts on influencing the unknown. Big strategic decisions on company direction, where to invest, and expanding into new markets require a different view on data. With SAP Analytics Cloud organizations are able to reduce the amount of uncertainty associated with the future and drive strategic decisions.

SAP Analytics Cloud is a completely new way to work.

• Intuitive Smart Features

  Use advanced machine learning techniques to move from business questions to insights to action in the analytics lifecycle. Optimize and achieve the best possible outcome by building recommendations for every business problem.

• Accessible to Everyone

  Regardless of their statistical knowledge, analysts of all skill levels can interact with machine learning insights and upskill to create their own predictive insights.

• One. Simple. Cloud.

  With integrated BI and planning, ensuring that insights are acted upon is simple and easy. Embed predictive insights directly into your corporate plans and monitor progress in the comprehensive command and control center: the SAP Digital Boardroom

Aside from Smart Features, the following features in SAP Analytics Cloud also support converged analytics:

• Comment across the platform to enhance cross-team workflows
• Easily share stories and curate content from SAP and non-SAP systems
• Ensure everyone is on the same page with trusted data models
• Use notifications to ensure everyone is in the loop

SAP Analytics Cloud combines Business Intelligence (BI), Predictive, Planning, and Digital Boardroom capabilities to analyze all data from your landscape, on premise or in the cloud.

SAP Analytics Cloud offers core capabilities to connect to the data and model needed. It also supports collaboration between users and offers a mobile presentation of your visualizations.

SAP rents dedicated tenants (isolated and secure) on a shared hardware-software platform based on the SAP Business Technology Platform. SAP manages the hardware and software so customers can focus on analyzing their business.

Software as a Service (SaaS) redefines the concept of a classical BI system into an intelligent enterprise system, where users can determine which information is needed, and in which form the information will be delivered.

The cloud is built natively on the SAP Business Technology Platform, allowing simplified access for customers and a trusted cloud experience.

SAP Analytics Cloud can be a public or private SaaS, which enables access to on-premise and cloud data sources. SAP Analytics Cloud provides two methods for accessing your data located anywhere in your information system landscape:

• Live connection (online)

• Data acquisition (batch) connectivity

In SAP Analytics Cloud, you can create models from data sources in on-premise or cloud systems, build stories based on those models, and perform online analysis without any data replication. This feature allows SAP Analytics Cloud to be used in scenarios where data cannot be moved into the cloud, taking into account data which cannot be moved for security or privacy reasons, or if data already exists on a different cloud system.

You can also create connections to remote systems to allow data acquisition by SAP Analytics Cloud. Data is imported (copied) to SAP Analytics Cloud HANA in-memory database, and changes made to the data in the source system do not affect the imported data.

Most customers want to get all the benefits of such hybrid architecture.

Servers responsible for your internal BI system are hosted by you or a dedicated provider. In this solution the provider is responsible for all actions and must support every function of the system, providing data, maintenance, and reporting.

Use a predefined connection to acquire data from one or more data sources. The data can then be prepared with the help of Modeler or in the report directly. Depending on how customers want to present their data, they can use different techniques to redefine data or to visualize them in the form of a story or dashboard. After sharing the result in the cloud, users can collaborate using the story or dashboard. Data can be refreshed as many times as required.

There two ways to get data to SAP Analytics Cloud:

• Replication
• Live Connection

These methods support different data sources.

Customers need to decide which connection type to set up, according to their own needs. Here are some best practices and some limitations to help you decide.

SAP Analytics Cloud as public software-as-a-service (SaaS) enables access to on-premise and cloud data sources. Furthermore, SAP Analytics Cloud provides live connection (online) and data acquisition (batch) connectivity - two ways for accessing your data located anywhere in your information-system landscape:

• You can create models from data sources in on-premise or cloud systems, build stories based on those models, and perform online analysis without any data replication. This feature allows SAP Analytics Cloud to be used in scenarios where data cannot be moved into the cloud for security or privacy reasons, or your data already exists on a different cloud system.
• You can also create connections to remote systems to allow data acquisition. Data is imported (copied) to SAP Analytics Cloud HANA in-memory Database, and changes made to the data in the source system don't affect the imported data.
• Furthermore, SAP Analytics Cloud provides SAML 2 capabilities to enable Single Sign-on, simplifying not only authentication to SAP Analytics Cloud but also to connected data sources from your landscape.

There are certainly some requirements and prerequisites in terms of system releases for the source and import volumes. For more information, see the Import Data Connection Matrix or the Live Data Connection Matrix.

Using a live connection, SAP Analytics Cloud provides the business logic and builds the queries required to see your data in your browser. Your browser in turn sends those queries, through the reverse proxy, down or through a direct live connection to the on-premise database. The results of those queries are returned to your browser, where visualizations are rendered. If your query was a list of profits per customer, for example, none of that information would actually return to or be stored in SAP Analytics Cloud.

Throughout the whole process, the browser is actually interacting with the reverse proxy or through direct live connection (CORS), which in turn sends out the requests to SAP Analytics Cloud or the remote data source, depending on the path of each request.

The short answer is: metadata and only metadata. SAP Analytics Cloud stores queries for building the stories, measure names, columns names, filter values, and so on. Basically, the metadata lets SAP Analytics Cloud rebuild the query. But none of the actual data, not even the query results or part of the results, such as totals, are saved to SAP Analytics Cloud. Metadata is transferred to your browser and encrypted in memory.

All data from your data source is uploaded (replicated) to SAP Analytics Cloud in-memory HANA database. SAP Analytics Cloud then stores the model and data. Security can be added to the model within SAP Analytics Cloud. Both Analytic and Planning models generate an account type model.

Because data is imported (copied) to SAP Analytics Cloud, any changes made to the data in the source system don't affect the imported data.

The SAP Cloud Platform Cloud Connector serves as the link between SAP Analytics Cloud and existing on-premise systems.

The Cloud Connector combines an easy setup with a clear configuration of the systems that are exposed to SAP Analytics Cloud. In addition, you can control the resources available for the cloud applications in those systems. Thus, you can benefit from your existing assets without exposing the whole internal landscape.

The Cloud Connector runs as an on-premise agent in a secured network and acts as a reverse invoke proxy between the on-premise networking customer domain and SAP Analytics Cloud. Due to its reverse invoke support, you don't need to configure the on-premise firewall to allow external access from the cloud to internal systems.

The free business content for SAP Analytics Cloud and SAP Digital Boardroom provides a quick and easy starting point for your individual analytics scenarios.

SAP Analytics Cloud business content features technology highlights such as planning, Smart Assist, value-driver trees, and mobile design.

It provides the following key assets:

• End-to-end industry dashboards
• Re-usable line of business packages
• Content is tailored to work with recommended SAP data sources
• Includes detailed documentation of KPIs, models, and data flows
• Comes ready to run with sample data or live connection

SAP Analytics Cloud provides a content library with packages of end-to-end business scenarios for specific industries and lines of business.

Each package provides an overview of which business questions are addressed. The list of technical objects is also available.

These business content packages give you pre-built stories for various industries and lines of business such as:

Industries:

• Consumer Products
• Retail
• Professional Services
• Insurance
• Engineering, Construction, and Operations
• Chemical
• Oil and Gas
• Public Sector
• Utilities

Lines of business:

• Finance
• Marketing
• Environment
• Health and Safety
• Human Resources
• Concur - Travel and Expense
• Fieldglass - Vendor Management
• Solution Manager

In the Treasury Management area there are two main business packages:

• Treasury Executive Dashboard for SAP S/4HANA Cloud
• Liquidity Planning for SAP S/4HANA Cloud

To get started, you must have a Business or Enterprise SAP Analytics Cloud license.

To open the Content Network in the SAP Analytics Cloud go to Main Menu → Browse → Content Network. Here select the Business Content tile.

In the Content Library, you see all the folders containing the different industry and line of business content packages. Each of these packages can be imported into your system.

The Overview tab gives you a description of what the package contains. The Import Options tab is where you'll find all the importing options. Finally, the Content section contains a list of the technical objects that are included in the package.

For liquidity planning on SAP Analytics Cloud there is currently only a designated business package available for SAP S/4HANA Cloud. Nevertheless we are using this as a starting base for the SAP S/4HANA Cloud liquidity planning.

Liquidity planning for SAP S/4HANA Cloud enables planners to complete a liquidity Item plan, including calculated closing balances, in SAP Analytics Cloud based on information sources from SAP S/4HANA Cloud.

Accelerators include planning input templates, planning calculations, and a planning process flow.

Liquidity planning for SAP S/4HANA Cloud enables analysts or planners to analyze trends and variances between versions such as Plan, Forecast, and Actuals in SAP Analytics Cloud.

SAP delivers Best Practices methodologies to integrate Cash and Liquidity Management from SAP S/4HANA Cloud into SAP Analytics Cloud.

Best Practices methodology establishes SAP S/4HANA Cloud as the primary source of master data and transaction data. (Best Practice Analytics scope item 3L5).

We advise you to be cautious when importing content as it will overwrite or otherwise affect any existing objects (Models, Stories, Dimensions, Dashboards, and so on) in your system that have the same name.

This is especially important for the more comprehensive industry packages because they usually re-use line-of-business content.

To import content into your system, we recommend that you first review the Import Options tab and select an option for the Overwrite Preferences.

If an object selected for import already exists in your system, the object in your system is overwritten and its data is updated. For models, however, the setting of the Privacy flag and the access permissions assigned to roles remain unchanged during the import, meaning the same users will have access to the content as before.

Be careful with deselecting content objects before the import as dependencies between dimensions, models, and stories are not taken into account. The consequence might be that a package cannot be imported successfully.

In SAP Analytics Cloud, models are the foundation for data exploration. Consisting mainly of measures and dimensions, models provide a framework for the data visualizations in your stories.

While you can create a story without a model, having an underlining model gives you more options. You can clean your data to allow for easier or more accurate data analysis; you can create hierarchies so you can drill down to different levels of granularity; you can create new measures based on formulas that can be used by multiple stories; and so much more.

Put simply, here are some of the benefits of models:

• Clean your data — separate or combine columns, fix typographical errors, ensure proper measures and dimensions are assigned, and more
• Customize your data — geo-enrich your data so that you can include maps in your stories; create multi-level hierarchies; create custom calculations; set units and currencies; add formulas; and so on
• Control your data — share your data with others and assign different permissions settings; tell multiple stories with one model

The dimensions you use in your models are saved independently of any model; when you create a new model, you can either choose an existing dimension or create a new dimension. Modeling uses several dedicated dimension types.

Apart from the built-in dimensions for Time and Category, all dimensions have three basic columns (attributes): ID, Description, and Hierarchy. These cannot be deleted, but additional columns can be added as required. The Hierarchy column is a free-format text attribute where you can enter the ID value of the parent member. By maintaining parent-child relationships in this way, you can build up a data hierarchy that is used when viewing the data to accumulate high-level values that can be analyzed at lower levels of detail.

Dimension of models are stored in their own tables. These tables can have extra fields for reporting, called a property.

For planning, the Category dimension is very important as it holds versions for planning scenarios.

The Dimension type is a generic, free-format dimension. For example, a dimension could be based on products, channels, or sales representatives. Values related to dimension members appear in different columns in the dimension grid. A model can have any number of dimensions.

Note

Note that the Description and Member ID attributes of dimensions must be of the Text data type.

The following types of dimension are available:

• Measure is a dimension that represents transactional data (note that this data is not visible in the Modeler).
• Date is a built-in dimension that defines the start and end dates of the model's timeline. The date dimension also specifies the granularity - the smallest time units that will be used in the model (years, quarters, months, or days). There is no specific setting for weekly periods, but if the lowest granularity is set to day level, then data output in stories is automatically shown grouped in calendar weeks.

  You can specify a default time hierarchy to display in stories, and optionally configure the date dimension to organize data by fiscal year instead of calendar year. You can also have more than one date dimension in a model or story.

• The Organization dimension type is optional in a model, but provides an organizational analysis of the account data. For example, an organization dimension could be based on operating units, geographic entities, or cost centers. A Region column in a dataset often maps to an organization dimension. A model can have only one organization dimension.
• A model is based on a single Account dimension (often containing multiple accounts) that may contain financial or any other business data. You can analyze the account data on the basis of the dimensions defined in the model. Example: you import some key-figure-based data into the Modeler as measures. Each column that you mapped as a measure will appear as members in the Account dimension.
• Version is a built-in dimension that defines the data versions available in stories: Actual, Budget, Planning, Forecast, and Rolling Forecast. Versioning is a financial planning concept that represents a way of providing calculations such as actual vs. budget.

  In a model that uses a currency conversion table with rate versions, you can use the Rate Version column for the Version dimension to set specific conversion rates for each version.

• The Timestamp dimension type is similar to the Date dimension type, except that it includes hours, minutes, seconds, and milliseconds, and is not hierarchical. The Timestamp dimension type is useful for data that is recorded very frequently; for example, sensor data.

Note

Models can have only one account dimension.

Note

In live data models, the Account dimension is named Measures.

Measures are numerical values that mathematical functions work on. For example, a sales revenue column is a measure because you can find out a total or average the data.

Dimensions are qualitative and do not total a sum. For example, sales region, employee, location, or date are dimensions.

When dimensions and measures work together, they help answer complex business questions.

Chart 1 visualizes a single measure, in this case, revenue. The visualization only answers one question: how much profit did we make?

Chart 2 visualizes the revenue measure in relation to the region dimension to show profits by region. Exploring profits by region will help answer questions about regional performance.

There are two types of models in SAP Analytics Cloud:

• Analytic models
• Planning models

Analytic models allow you to clean your data and prepare it for story mode. Here, you can define measures and dimensions, create calculations, set up hierarchical relationships, geo-enrich your data, and more.

Planning models allow you to do everything analytic models do, but they also give you a more control with your data such as setting up budgets and forecasts, creating your own versions of model data, copying and pasting data, and using spreading, distribution, and allocations features.

Analytic models are great for measuring success and looking for opportunities. For example, suppose you run an ice cream parlor and have the following data:

• Flavor
• Sales price
• Quantity sold
• Date

You could easily tell a story with your data showing what are the most popular flavors, what are your peak periods, and what are the long-term sales trends month over month, or year over year. From this analysis, you could make decisions about promotions, introducing new flavors, and even expansion opportunities.

Planning models can do everything analytic models can do, but they are used more by large companies looking to do sales forecasting, budget allocation, 'what-if' analysis, and so on.

Keeping with the ice cream example, imagine a large manufacturer of ice cream looking to save costs and increase profit margins.

They may use a value-driver tree to test different 'what-if' scenarios such as switching all cow milk for soy milk, increasing marketing spend in underperforming regions, or changing store hours.

Planning models allow you to do everything analytic models do, but they also give you a more control with your data such as setting up budgets and forecasts, creating your own versions of model data, copying and pasting data, and using spreading, distribution, and allocations features.

Within a planning scenario, individuals within your organization can create public, private, and shared versions of data that will not overwrite a public version until approved. These versions enable individuals to change values without compromising public data, giving planners the ability to try different what-if scenarios within their data before making final decisions.

Note

Only a planning license in SAP Analytics Cloud with allow you to access planning models.

You can also define what types of data you can manage in your model.

In planning models, there are different categories - money you actually made (Actual), money you're going to make (Forecast), and money you are going to spend (Budget). SAP Analytics Cloud allows you to choose the granularity of each of these categories.

Choosing the level of granularity determines how deep you can view into your data. For your time dimension you can choose from Year, Quarter, Month, and Day.

For example, you may have daily sales transactions, but see little value in looking at that level of granularity. You therefore may decide that Month is the lowest granularity that you require.

Or take budget as another example. You can select whether you see a daily budget or monthly, quarterly, or yearly.

The standard categories available in your planning models are:

• Actual - actual values, or money you made
• Budget - how much you are allowed to spend
• Planning - what is the goal (financial/non-financial) you are trying to achieve
• Forecast - what is your expectation of the financial data
• Rolling Forecast - the range for how far back and forward you look

You can also define your model preferences.

• Description - insert a name for your model
• Default Currency - the currency your company uses to report their results on the corporate level
• Data Audit - allows you to track when changes are made to your data
• Privacy - provides a way for user to define who can access the model data
• Currency Conversion - allows you to see the values in your model in different currencies
• Preconverted Actuals - when importing actual data from data sources into SAP Analytics Cloud, currencies will remain as is and not be converted

Whether you're planning your sales forecast, distributing funds for R&D, or reallocating your marketing spend, SAP Analytics Cloud makes spreading, distributing, and assigning budgets a straightforward task. What would be a tedious and complex formula in other accounting tools, can now be done with a click of a button.

Spreading is the process of taking funds from a higher level in a hierarchy and assigning it to lower levels. For example, resources available at the global level can be assigned to individual regions, or at the year level and spread out to individual quarters. This is a crucial function when planning budgets and sales forecasting. By looking at previous years' trends, you can estimate how much resources to devote toward a particular area of your business.

When automatic spreading is applied, the funds are split equally between the regions and the available product groups within those regions. Spreading can also be done manually so you can spread funds however you like.

Distribution enables you to move some or all the funds from one cell to other cells at the same hierarchical level, or members of the different branch of the same hierarchy.

For example, suppose you run a clothing company with different product categories such as:

• Apparel
• Active wear
• Footwear

For the upcoming summer season, you want to cut back your resource allocation from your winter line to your summer line. You could take funds from your outerwear budget and then distribute those funds to footwear, active wear, and backpacks. This is easily done with just a few clicks.

Assigning adds new values or replaces values in one or more cell. For example, suppose you want to increase your marketing spend for an upcoming campaign. Simply enter the amount you wish to assign and tell SAP Analytics Cloud where you want to assign those funds. Whatever you enter will cascade down, impacting any connected areas of your planning model.

A story is a presentation-style document that uses charts, visualizations, text, images, and pictograms to describe data. Once you create or open a story, you can add and edit pages, sections, and elements as you like. The story toolbar is divided into different categories such as File, Insert, Data, and Tools to help you find options and perform tasks more efficiently.

Models are the foundation for which stories and presentations are built. Here is where you prepare your data for analysis by wrangling, or cleaning, your dataset, defining your measures and dimensions, and enhancing your data.

To create a story, go to the main menu and choose Create → Story.

You can apply formatting to your story by using a template, which provides predefined layouts and placeholders for objects to help you build a story. It is possible to add one of the following:

• Responsive Page:

  Responsive pages allow you to create layouts that automatically resize and reflow when viewed on different screen sizes. They can be added to Digital Boardroom agendas and dashboards.

• Canvas Page:

  Lay out charts, tables, geo maps, images, and other elements on one or more canvas pages to explore and present your data. Use the Designer panel to format and manipulate the data in your canvas elements.

• Grid Page:

  Start with an empty grid, and add data; for example, by typing in numbers or pasting from another application, or by adding a table based on an existing model.

Choose how you want to start your story:

• Select a template: You can apply formatting to your story by using a template, which provides predefined layouts and placeholders for objects to help you build a story.
• Access and explore data: Import data from an Excel or CSV (comma-separated-values) file, from Google Drive, or from an existing model, an existing dataset, or a datasource.

Imported data from a file or from Google Drive opens in the Data Manipulation view, where you can prepare your data, define dimensions, and perform operations such as sorting and filtering. You can also switch to the Data Exploration view, where you can begin analyzing data and creating visualizations.

You can add multiple pages to your story to help you explore and present your data.

A story page can be a blank canvas, a responsive page, or a grid. Use a blank canvas or responsive pages to lay out tables and charts, or use a grid to work with numbers and formulas on a sheet. Responsive pages let you create lanes to section the page content into groups. Tiles within a lane stay together when the responsive page is resized.

On the page tab bar, you can select a page's drop-down menu to delete, duplicate, rename, move, hide, or add comments to that page. You can also copy and paste story pages from one story to another.

Note

When you copy or duplicate a story page, the input controls (measure, dimension, and cross-calculation) won't be copied to the new page.

As teams become more cross-functional, collaborating and sharing is essential.

SAP Analytics Cloud makes sure that this is intuitive and effective. The stories support the following functions:

• Collaborating on stories:

  Collaborating on stories is made easy with the built-in collaboration tools. You can collaborate on a story by:

  • Having a discussion
  • Posting comments
  • Assigning a task

  To create a discussion, simply select the discussion icon, choose one or more people you wish to collaborate with, and then start a conversation. You can message, add attachments, and even link to other stories.

• Commenting:

  Commenting is a great way to offer feedback on specific elements in a story. Simply select the element you wish to comment on, click the comment icon, and type in your message. Comments can be addressed to specific users by tagging them with the @ symbol if the story was shared directly with them, rather than indirectly via a 'team'.

• Input Task:

  Input tasks are used to gather feedback or additional information from colleagues. A task is created and sent to the colleague, who adds the requested information and then returns the task.

  You can assign tasks to one or more collaborator. When assigning a task to someone, you can include a final reviewer, attach related content, and even set a deadline and reminder. Your collaborators will receive an email notification with a link to your story. If you set a deadline, an event will be added to their calendar.

• Sharing stories:

  There are two ways to share your story:

  • Internally
  • Externally

  To share a story internally, simply choose the Share Story icon and choose who you wish to share your story with.

  Sharing a story with members in your organization who use SAP Analytics Cloud allows them to use the dynamic features such as hierarchical drill down, input controls, and linked dimensions.

A version is a set of data from the database, viewed in a table. To control who can access a version, you make the versions public, private, or shared.

• Public Versions:

  Public versions are stored in the raw model data in the database.

  Access to this data is controlled by data privileges. If data access control is enabled for a dimension, a user must be assigned the proper privileges in the Modeler to be able to view and edit values. In the modeler, users can also restrict view and edit permissions for public versions.

• Private Versions:

  Private versions are only visible to the creator of the version.

  Use private versions to change or simulate plan values without making the changes visible to anyone else. When you save a private version, it gets changed to a public version, and the private version is dropped.

• Shared Versions:

  Shared versions are private versions that you allow other people to see.

  You can choose to let other users read your shared data, or you can allow them to read and write the shared data. When you share a version with multiple users and want to remove one of them, you must unshare the version and then re-share it.

The Category dimension can contain multiple versions. For example, a Budget category can contain an Optimistic version, a Baseline version, and so on. Using Version Management, you can create versions within the given categories.

Note

The Actual category can contain only one public version, which is named Actuals. However, the category can have multiple private versions.

The following categories can be used in a table:

• Actual
• Budget
• Planning
• Forecast
• Rolling Forecast

In a table or a chart, the Category dimension acts as a container for the different public and private versions that are available to you. (Some data sources refer to this as a Version dimension instead of a Category dimension.)

Data is not aggregated across different versions in the Category dimension. When the Category dimension is added to an axis of a table or chart, you can display multiple versions. When the Category dimension is removed from the axis, you work with a single public or private version.

If you have defined one or more calculations that restrict the Category dimension to a single version, these restricted measures act as a filter on the Category dimension. When you remove the Category dimension from a table axis, you are not prompted to filter the table to one version. Instead, the table displays only the calculations that restrict the Category dimension, and calculations based on that dimension.

The Version Management panel shows several options for working with the versions.

From the menu you can perform the following actions:

• Share
• Undo
• Delete
• Publish your work as an update to a public version

You can save a private version to make it public, either in the same category or as a different category. You can also save edits to public versions.

Locate the version that you want to save and choose one of the following: 

• Publish:

  This publishes your work as an update to a public version. If you are saving changes to a public version, you can only choose the same version that you edited. Choose the version and then choose OK.

• Publish As:

  This creates a creates a new public version. Select a category, for example Forecast, enter a name for the new version, and then choose OK.

• Drag the private version to the Public Versions section:

  If you saved a new version, the version is now available in the Public Versions section of the Version Management panel. If you updated a version, the version is updated. If you saved or dragged a private version, the original private version is no longer available in the Version Management panel.

Note

If data access control is enabled for a dimension in the model, it restricts changes to data in public versions, but not in private versions. In a private version, you may want to simulate a scenario that involves changing dimension members for which you do not have write permissions, for example. In this case, you cannot save the changes to those members to a public version. Only members for which you have write permissions will be updated.

Using the Liquidity Planning function, cash managers are able to centrally manage the entire life cycle of rolling liquidity plans.

• The group cash managers are in charge of the entire process, starting from the planning cycle, to checking and reviewing the liquidity plans submitted by subsidiary cash managers as well as finishing the planning cycle and doing post-planning analysis.
• The subsidiary cash managers are responsible for entering the plan data for the planning units that they are responsible for.

With the SAP Analytics Cloud Liquidity Planning functionality the group cash manager can:

• Get timely, bottom-up and objective liquidity plans
• Use liquidity planning as an early warning indicator of liquidity shortages or as a steering tool for medium-and long-term investment or borrowing
• Track and trace liquidity planning cycle
• Analyze variances to improve liquidity plans

Select the play button to watch the video on the end-to-end liquidity planning cycle in the SAP S/4HANA Cloud, public edition.

Here the liquidity forecast and last year actual information is used as planning reference. You can use this reference data as a starting point for your planning. Based on liquidity items you can enter or adjust the planning data in planning currencies for the liquidity items.

The diagram details the flow of data from the SAP S/4HANA Cloud source system through to the SAP Analytics Cloud.

Starting from the SAP S/4HANA Cloud system, the reference information needed for the planning is stored in the One Exposure from Exposure. Dedicated CDS-based OData services pick up this information and provide that to the SAP Analytics Cloud as input for the models there.

These models in turn are integrated to a story where the actual planning through the planning sheets is performed.

For the liquidity planning process in the SAP Analytics Cloud there are generally three corporate roles involved.

The administrator is responsible for setting up the planning model to be used in the overall story. He provides the technical framework for the Group Cash Manager to start the planning cycle.

The group cash manager uses the pre-defined planning story to trigger the liquidity planning process. He sends out the planning sheets to the individual subsidiary managers with the request to fill these sheets.

The subsidiary cash manager(s) receives the input request. He fills the planning sheets with the required information for the upcoming period. Having done that he returns the sheet to the group cash manager.

The group cash manager in turn checks this data and can consolidate numbers across the entities if needed.

The SAP Analytics Cloud administrator is the person responsible for setting up the SAP Analytics Cloud with all the groundwork needed for upcoming planning cycles.

They need to establish a connection between the systems SAP Analytics Cloud and SAP S/4HANA On-Premise. They are responsible for building the planning model in the SAP Analytics Cloud.

Finally they create the story for planning and hand it over to the group cash manager.

The administrator establishes a connection to the SAP S/4HANA Cloud system via data acquisition on the SAP Analytics Cloud. This means that data is loaded from the SAP S/4HANA system to the SAP Analytics Cloud for further processing. For more information on how to set up such a connection, see the SAP Analytics Cloud setup section.

If the data connection is established, the liquidity planning model is created by the administrator. Therefore he defines the dimensions needed, adds a data source, and finally maps it against the SAP S/4HANA Cloud information.

For more information on dimensions, mapping, and so on, see the setup section.

The data model is used as the basis for the liquidity planning story. The administrator sets the styling of the input sheet, includes the planning model, and sets up an input task as the trigger for the planning cycle. For more information, see the setup section.

After this he hands the story over to the group cash manager who uses the story to send out the planning sheets to the individual subsidiary cash managers.

The group cash manager picks up the story from the administrator and sets a few parameters needed for the planning. These are, for example, the time period for the plan, the company assignees, or the plan versions.

Having set all of the required parameters, he sends out the planning sheets to the subsidiary cash manager with the request to fill the according data.

The group cash manager picks up the story from the administrator. If not already set by the administrator, the group cash manager can set the time filter (for the period to be shown on the sheet) and create a new private version for the period to be planned on. Both can be managed in the story designer.

Having set the filters for time and version the group cash manager can choose to create the input task from the menu.

The input task requests the subsidiary cash managers to provide additional data. A task is created and sent via mail to the subsidiary cash manager. They add the requested information and return the task to the group cash manager.

On the input task tab, the group cash manager can do several things. He can check the designated version to be planned on. He can also assign responsible persons (assignees), in this case the subsidiary cash managers. To do this, choose the drill level (company code) and choose the Select Substitute field. From here any SAP Analytics Cloud user can be assigned.

If all the assignees are set the group cash manager will send out the planning sheet to the previously maintained subsidiary cash managers.

After sending the request the summary page will change for the group cash manager. On the overview page he is informed on the overall approval status but also on the individual level per company code and assignee.

From here the group cash manager is able to track the progress and to steer the planning process.

The Summary page for a task shows the current approval status for input tasks.

•  Default view: see a high-level view of the number of assignees for each type of status (In Progress, Open, Rejected, and so on).
•  Hierarchy view: expand to see the status for each assignee.

The overall status shows Partially Accomplished if some assignees have accomplished their tasks and some have not finished or have canceled theirs.

The subsidiary cash manager(s) are in charge of entering the liquidity planning data in SAP Analytics Cloud. They have several options of using reference data to speed up the planning process. If they have updated their values in the planning sheet they submit the information back to the group cash manager. If there are questions or inconsistencies and the group cash manager rejects the submitted input sheet the subsidiary cash manager is responsible for checking and updating the information.

Once the input task is sent out from the group cash manager the subsidiary cash managers or assignees receives a mail prompting for the input. The subsidiary cash managers can use the Open Task button to be directly forwarded to SAP Analytics Cloud.

Data entry needs to be efficient and easy, whether you're a finance expert booking values to forecasts, or a line-of-business employee providing input for a bottom-up planning process. Get a familiar experience for data entry using a table that shares many functions with Excel spreadsheets.

You can enter relative or absolute values into individual cells. You can also copy cell values, along with all of the data that aggregates up to the copied value.

You can plan at any level of a hierarchy, and the data will automatically be rolled down to the lowest level. If you need to adjust proportions between members, use the Spreading, Distribute, and Assign features.

The subsidiary cash manager has the option to use social collaboration to support and optimize group decision-making processes.

All collaboration activity is grouped under discussion threads. Choose the Collaboration button from the main toolbar to see a list of discussions that you have been invited to. You can start a new discussion at any time by choosing New Discussion and inviting specific participants. Only people who have been invited can see the discussion.

This way you can ask other colleagues for help or request additional information from co-workers.

Once the subsidiary cash manager has dealt with the input of the planning data he returns to the summary page. From here he can submit the planning sheet back to the group cash manager.

The group cash manager receives a workflow message that one of the subsidiary cash managers has performed the planning task and submitted the information back.

In the SAP Analytics Cloud story the group cash manager is now able to track the approval status of each assignee.

He is also responsible for checking the feedback provided by the subsidiary cash managers and rejecting or approving the given numbers.

After this, the group cash manager is also the person who starts the next planning cycle where the involved parties are again asked to input information to the planning sheet.

The group cash manager is informed (for example, by email) that one of the assignees has submitted the input sheet of the liquidity planning.

Through the summary page of the story he can now see the status of all items on the left and can check the individual status of each subsidiary on the right.

For the submitted planning sheet a action column is provided. After checking the input the cash manager can either approve or reject the input of the single entity.

In the additional tab of the liquidity planning story the group cash manager can verify the input of the subsidiaries. This is the foundation of approving or rejecting the plan.

After the group cash manager approves the submitted numbers, the subsidiary cash manager is informed about the status update.

He is informed that the group manager has accepted his input and that the planning process is finished for this cycle.

You can use the menu path Main Menu → Browse → Dimensions to view and create public dimensions.

Public dimensions can be shared between models, while private dimensions exist only in the current model. Public dimensions are saved separately from models. They appear in the Public Dimensions list.

You can import SAP S/4HANA Cloud master data only into public dimensions, not into private dimensions. For this reason, we recommend that you use public dimensions in models that you want to connect to SAP S/4HANA Cloud.

The proposed Liquidity Planning model for SAP S/4HANA Cloud is the financial model for Liquidity Planning. The model is made up of a combination of critical dimensions sourced from SAP S/4HANA Cloud and other dimensions maintained only in SAP Analytics Cloud. 

Create a custom public dimension for the ompany Code, Liquidity Item, and Bank Accounts. The Audit Trail, Time, and Version are private or system dimensions.

When creating new custom dimensions for the liquidity item, bank account, and company code, consider the specific types of each dimension.

The Account dimension defines the set of account members and the format of the account data.

Note

The account dimension is the main dimension of the model. In the case of the SAP Liquidity Planning this main dimension is the liquidity item.

In addition to the basic columns of Member ID, Description, and Account Type, a set of technical properties is automatically created when the dimension is first set up.

• Account Type:

  The Account dimension uses an Account Type attribute to automatically handle positive and negative values. From an accounting perspective, account members belonging to the Profit and Loss statement and the Balance Sheet have to be correctly stored in the database with either a positive or negative value so that the accounts balance correctly. In SAP Analytics Cloud, you can enter all values as positive numbers, and the switching of signs from positive to negative is handled automatically on the basis of the Account Type setting.

  There are four financial account types: Income (INC) and Expense (EXP) items are included in the Profit and Loss account, and Assets (AST) and Liabilities (LEQ) are Balance sheet items. Automatic switching is applied to the account types INC and LEQ. Note that all formulas work on the displayed value, not the value saved in the database.

  When importing data from an external system, a mapping feature is available to ensure that imported data also fits into this schema. This feature is switched on using the Reverse the Sign of the Data Based on Account Type check box in the Details panel when importing data. When this check box is activated, imported data will also be identified by account type and stored and handled correctly.

• Aggregation Type:

  For account members that are parent nodes, the aggregation type determines how values are accumulated from the leaf nodes. These aggregation types don't relate to any dimension.

  • SUM: This is the default aggregation type for income and expense values; this simply adds all values together.
  • NONE: If the value types of numerical data cells are different, aggregation may not be possible; this may be the case, for example, for price information or cells containing different currencies. For these account members, set the aggregation type to NONE. In tables in stories, cells that have not been aggregated are shown with a diagonal line drawn through them. The cell will be either empty, or, if all child values for a node in the hierarchy are the same, this single value is shown at the node level.
  • LABEL: Set the aggregation type to Label for any dummy nodes on the hierarchy where you want a text label to appear in the data grid without any calculation of values. In this case, the Description Text for the member is displayed as a label, and a simple dash character is used where otherwise an aggregated value would normally be displayed. You cannot set leaf nodes to type Label - this is immediately flagged on screen as an error.
• Exception Aggregation Type:

  Set these aggregation types for summing up the values from the opening balance towards the closing balance of the liquidity items.

  • First: Shows the first (oldest) value in the selected time period; it could be used, for example, to show the number of employees on the first day of a month. Select only one exception aggregation dimension.
  • Last: Shows the last (most recent) value in the selected time period; it could be used, for example, to show the number of employees on the last day of a month. Select only one exception aggregation dimension.
  • Sum: Adds all values together.

To have the data loaded into the model make sure that the member details of each dimension in SAP Analytics Cloud fits to the information from SAP S/4HANA Cloud.

In case of the liquidity items create the members needed for your structure in order to perform the planning upon them.

Set the members of each dimension according to the needs of your organization. You can arrange for the specific account type in SAP Analytics Cloud. Incorporate hierarchies to map certain business requirements.

Nevertheless remember that the Liquidity Item, for example, is a public dimension. That means it could be leveraged also in other models. In this case make sure there are no overlaps with other projects so that information is amended for other users.

Models support several different scenarios for working with monetary data from different currencies.

• Single Currency:

  If your model only contains data in a single currency, you can specify it as the default currency in the model preferences.

• Multiple Currencies:

  When you have data from multiple currencies, you can change the currencies that are displayed by working with either the Cross Calculations dimension, or the currency dimension for the model. For multiple currencies, the following options are available:

  • Multiple currencies without conversion:

    If your model has values in different currencies but you don't need to aggregate data across the different currencies, you can specify the dimension that identifies the different source currencies.

    The currency dimension lets you view different currencies side-by-side in a table and, for a planning model, make changes within each currency.

  • Multiple currencies with conversion:

    For some models, you'll need to aggregate data across different currencies. If you have data from multiple currencies and you want to view or change values that include more than one currency, for example, overall sales for EMEA, then you can use currency conversion. Currency conversion lets you view your data in its source currency as well as converting it to one or more target currencies for aggregation. You can also simulate the effects of different exchange rate shifts. In addition to a currency dimension, models that use currency conversion also require a conversion table.

If you are using a model with a single currency, and thereby no currency conversion, you can set this as the default value in the model preferences. Go to the currency tab and choose a default currency. This is the currency for all monetary values. For example, if your model only contains monetary values in US dollars, you can set the default currency to USD.

If you are using a model without currency conversion but your model has values in different currencies and you don't need to aggregate data across the different currencies, you can specify the dimension that identifies the different source currencies.

You can set the dimension with currency property enabled again in the model preferences. Go to the currency tab and choose the option here. In this case you need to make sure that all leaf members of the currency dimension (here the SAP_ALL_COMPANY_CODE) have an entry in the currency column.

Ensure that your system contains a currency table with conversion rates for the different currencies, dates, and categories in the model. In the Modeler, enable and configure the currency column for the dimension that separates the data into different currencies. For example, this dimension could be an Organization dimension, or a generic Source Currency dimension.

In the model preferences, enable currency conversion and specify settings for the default currency, currency dimension, and currency conversion table.

In tables in stories, you can choose which currencies to display. Monetary values are then converted and displayed according to the specified rates for the currencies you selected.

Enabling currency conversion allows model data from different source currencies to be converted into a single target currency and then aggregated.

To enable currency conversion, activate the Currency Conversion  switch and specify the following settings:

• Default Currency: Enter the three-character code for the default currency. Monetary data will be converted to this currency by default.
• Currency Dimension: Select the dimension that separates model data into different currencies.
• Currency Rates Table: Select a currency conversion table. The dropdown list shows all tables that have already been created on the Currency Conversion tab of the Modeler.
• Preconverted Actuals: When this setting is on, both source currency data and preconverted currency data can be imported.
• Maximum number of Currency Conversions: This setting determines how many different currency conversions can be simultaneously displayed in a table based on this model. For example, if you want to enable users to view side-by-side figures for USD at the Budget rate, USD at the Forecast rate, and USD at rates defined for three different fixed dates, you can set the limit to five.

You can create a currency conversion table by copying and pasting data from a file, or by importing data from a data source.

To create a new currency conversion table go to Main Menu → Create → Currency. From here you can decide which method to use. For liquidity planning we choose to set up a new currency conversion table. If you also want to upload data from a file, choose New Currency Conversion Table and upload data directly here.

A currency conversion table defines exchange rates for all currencies that are in use. The currency conversion is calculated as a source currency multiplied by an exchange rate to determine the equivalent value in a target currency.

Each rate has a Valid From value, which is the start date from which the rate becomes effective, but exchange rates can also be defined for a single category (actuals, budgets, planning, and so on) and for a selected currency rate type (either Closing or Average). This makes it possible to maintain several variations of a currency exchange calculation that can be used, for example, to track differences between budgets, plans, and actuals and to compare different types of exchange rate calculations.

• Rate version:

  You can specify rates further by using the Rate Version column. Individual public versions can be assigned to a rate version, overriding the rate for the category. Users can also apply these rates when creating versions or currency conversions in a story.

• Rate type:

  The Rate Type attribute of a currency is required. Leaving it blank will result in invalid currency conversion table entries. The category and rate version are optional attributes, and are blank by default. If these attributes are not set, the exchange rate value is generic, but you can add additional lines and rates to the table with categories, versions, and rate types applied for each exchange rate you wish to use.

• Category:

  To set a category for a rate, make a selection from the list in the Category column. If you want to set a rate for individual versions instead of a category, choose Specific in the Category column and enter a name for the rate in the Rate Version column. This rate can then be assigned to public versions in the Modeler, or selected when creating a new private version or currency conversion in a story.

As planning users work with model data in stories, they may try to analyze currency data that depends on rates that do not exist in the rate table.

For example, if a user creates a Forecast version in a story that uses currency conversion, but the currency table only has rates that apply to the Actuals and Budget versions, the forecast data cannot be converted.

When working with a currency table in the Modeler, you can use the Add Missing Rates panel and the Conversion Errors list to help you fill in missing rates.

The Add Missing Rates panel allows you to search for and add conversion rates that are missing for a model. The panel only finds rates that are required for stories based on a selected model; for example, if you search for missing rates for January 1, 2020, but there is no model data or currency conversions for that date, there will be no results.

According to the missing rate information and your further needs fill the currency table accordingly.

The account dimension is the area where the additional information for the rate type is stored when activating the currency conversion.

Further you would need a dimension that has the currency attribute so that you differentiate information upon this information (in the example above that could be the Bank Account).

The Account dimension defines the set of account members and the format of the account data. Remember that the account dimension is the main dimension of the model.

If you are using currencies with this account, and you have added specific exchange rates based on rate types to the currency table, you can add the Rate Type column to the account grid by enabling currency conversion in the model preferences.

This attribute column is not visible by default, but you can add it by enabling currency conversion in the model preferences. The attribute is blank by default so that a generic exchange rate from the currency table will be applied for the account member. If you select a rate type (Average or Closing), the exchange rate in the currency table, which has also been flagged by this same type, will be used.

When you enable currency conversion, the Rate Type column is automatically added to the Account dimension as shown above. The appropriate rate type setting for each account member is determined by the Account Type setting. INC and EXP account types require the rate type to be set to Average. AST and LEQ require the rate type to be Closing.

If your model has currency conversion enabled, data from different currencies can be converted and aggregated into one or more target currencies, or it can be displayed in its source currencies.

You can use the Cross Calculations dimension to create conversions to different currencies using rates specified in the model's currency conversion table, and choose which ones to display. You can display a single member of this dimension when it's not added to the table, or add it to the table to display multiple members.

Go to your story and select a table that is based on a model with currency conversion.

In Builder, select Add Measures/Dimensions → Cross Calculations. From the Cross Calculations dimension, choose Add Calculation.

If you have selected to add a calculation the Calculation Editor appears.

Choose Currency Conversion as the type and enter a name for the currency conversion. Choose the currency that you want to convert to.

Choose a category or rate version and a date. There can be multiple conversion rates defined for each currency in the model's currency table, that apply to different dates and different categories or versions.

If the currency conversion table for your model contains different conversion rates for the target currency, you can use the date, category, and rate version settings to control which rates are used in each conversion that you apply to a table.

Set the category to Dynamic to use the conversion rate defined for the category or version that correspond to each value in the model.

If you specify a category, the conversion will apply the rates defined for that category to all values. You can also specify a conversion rate for specific versions instead, by selecting Specific as the category and then choosing a rate version.

Likewise, select the Booking Date radio button to use the conversion rate that applies to the time at which each value was booked.

You can also use the Booking Date + 1 or Booking Date - 1 radio buttons to apply a rate from a year, quarter, or month before or after the date for each value. For example, if you select Booking Date - 1 and choose Year as the interval, values for February 20, 2018 will be converted using the rate that applies to February 20, 2017. If you specify a fixed date, the conversion will apply the rates defined for that date to all values.

After setting the values a row or column is added. It shows the data values converted to the selected currency using the rates that you specified.

Note

If the maximum number of currency conversions for the table has been exceeded, the Select Conversions menu appears. You can change the currency conversions that you want to display and then choose OK.

If the currency conversion fails due to missing rates, a message is shown. Choose Show more to show the rates that are missing by currency, category, rate type, and date.

You can perform planning operations on a single target currency, such as the default currency, or on one or more source currencies. Messages will alert you when an operation affects multiple currencies, because these operations may have unexpected results.

All types of planning operations are supported on target currencies, or on data from multiple currencies:

• Data entry
• Spreading, distributing, and assigning values
• Data actions
• Structured allocation

These operations are carried out using the target cell's currency. For example, if you copy a value of 500 USD to a cell that displays a value in euros, the resulting value is 500 euros.

If you make a change to a source currency value in a public version, the other currency members in the version are immediately updated to show your changes. If you made the change to a single target currency, other currency members in the version will show diagonal lines instead of values until you publish the changes to the version, and then values for all currencies are updated to reflect your changes.

When you copy a public version while multiple currencies are displayed, you choose which currency to use for planning operations in the new private version. If you select a target currency, the private version shows values only for this currency, and values are converted to other currencies when the version is published. If you choose to plan using source currencies, converted values are shown for other target currencies as you make your changes.

When you are planning on data in multiple currencies (for example, source currency data, or data from a model that has a currency dimension but does not use currency conversion), a planning operation can change values across more than one currency.

However, the different monetary value of each currency is not considered during the operation. As a result, planning operations that affect multiple source currencies may not provide the desired values. For example, if you enter 1 million to an unbooked account for North America while planning in local currencies, it could result in values of 500,000 CAD for Canada and 500,000 USD for the United States. The numerical value is divided evenly, but not the monetary value.

When a parent member has a booked value and child members that display multiple currencies, the parent member does not support planning operations. Data cannot be disaggregated to multiple currencies with booked values.

In cases such as this one, a message appears to let you know that data has been entered in multiple different currencies. If necessary, you can undo the operation using the Version Management panel.

Messages are also displayed when you create an allocation process using the currency dimension as a target, or a data action using the currency dimension in a copy rule or as the Aggregate To dimension, and when a user executes one of these processes in a story. You can avoid this situation by planning on a target currency instead of source currencies, or by filtering the data to a single leaf member of the currency dimension.

You can enter measures that have been previously converted to a different currency, if you don't want SAP Analytics Cloud to convert these measures again.

Typically, you would use a currency conversion table when you want to analyze data from multiple regions with multiple currencies, or from multiple source currencies. But if your system has already calculated the currency conversions, and you'd like to use those conversions instead of a conversion table in SAP Analytics Cloud, you can import both the source currency data and the converted data. The source currency data and converted data appear as separate measures that you can use in stories and tables.

Note

If you select currencies in a story or table that are not the default currency, the data is converted using the selected currency conversion table.

Note

• This feature applies only to data in the Actual category, not to Budget, Planning, Forecast, or other data categories.
• Copying actuals into Budget, Planning, or Forecast allows you to lock down, or fix, the default or local currency, with the non-locked measure calculated based on currency rates.
• This feature is available with new blank models or when importing a file from your computer.
• The Preconverted Actuals switch is enabled only when currency conversion is switched on.
• Preconverted actuals cannot be edited in SAP Analytics Cloud after they have been loaded using data entry or advanced formulas.

1. To use preconverted actuals, create a new blank model. Open the model preferences, and on the Planning & Time Range tab, switch planning capabilities on if you want the option to add currency conversion later, in stories.
2. On the Currency tab, switch currency conversion on.
   Note

   You can only change this setting when no data is loaded into the model.
3. Set the model's default currency.
   Note

   Choose the currency to which your preconverted actuals have been converted.

4. Choose a currency rates table. Switch preconverted actuals on, and choose OK.
5. Because you started with a blank model, you need to enter data into the model, for example by copying and pasting from an Excel file:
   1. Create a new Account dimension.
   2. Enter account information.
   3. Add a dimension of the Organization type and enter organizational and currency information. Once currency conversion is switched on, the model needs a currency dimension, which defines the organization of the data in the model. For example, the Organization dimension might include a list of regions, each of which corresponds to a particular currency. These currencies are the local currency. 
6. Switch to the Data Management view and select Import Data. Choose the data file that contains the preconverted currency data and choose Import.
7. Select the imported data from the Draft Sources list and map the data to the model's dimensions.

   1. First, map the account dimension (must be actuals). After you've mapped the account dimension, the Measures card can be expanded to two cards: 

      • Local Currency (also known as source currency)
      • Default Currency
   2. Drag the preconverted actuals data to the Default Currency card and the standard measure data to the Local Currency card.
8. Select Finish Mapping and save your model. After creating the model, you'll typically create a story with a table to include the preconverted actuals.
9. As described above, choose Add Measures/Dimensions → Cross Calculations. Point to the calculation you just added.
10. In the Available Members list, you can select both the source currency and preconverted data members to include in your table.

To create a completely new model in the SAP Analytics Cloud for liquidity planning, several steps are necessary.

When creating a new planning model there are initially four steps we need to run through:

• Add dimensions to the model: You can either add existing dimensions or create new dimensions on your own.
• Add a data source: Choose the SAP S/4HANA Cloud system which should act as data source.
• Select and build the query: Pick the API reference which are using CDS based Odata Services to load data from the SAP S/4HANA Cloud system.
• Map dimensions: Map the dimensions from the SAP Analytics cloud to the SAP query fields provided by the SAP S/4HANA Cloud system.

In the following sections we will elaborate on each of these steps in more detail.

To create a new model for the Liquidity Planning, go to Main Menu → Create → Model.

From here you can choose which source should act as basis for your new model to start with. We use the blank model to kick-start our planning.

If you start with a blank model planning features are enabled by default.

The modeler opens, giving you an overview of the model in the first screen.

The Modeler is where you view, edit, and configure models. The modeler enables you to work on:

• Model types
• Dimensions
• Data Management
• Dimension grid view
• Further Modeler features

There are two screens in the Modeler: Model and Data Management. When you open an existing model, its contents are shown on the Model screen:

• Dimension list
• Model Details pane

The Model screen shows you the dimensions in your model, the number of members and hierarchies in each dimension, and any attributes that have been defined for the dimensions. On the right, the Model Details pane shows you the model settings, datasources, and other information about the model.

You can choose between the grouped view, where dimensions are grouped according to dimension type, and a simple list view.

Use the model details at this point to change the model name and description as needed.

Within the modeler you can set model preferences. Use the screw-wrench icon at the top of the model details to access the preferences.

General Settings

Set the model type, the model layout and a name and description for it.

Access and Privacy

Set the information such as data auditing or locking, data access control.

Planning & Time Range

Planning features are enabled by default. For a planning model, select Planning & Time Range, and then choose From and To dates to define the timeline for the data.

The proposed Liquidity Planning model for SAP S/4HANA Cloud is the financial model for Liquidity Planning. The model is made up of a combination of critical dimensions sourced from SAP S/4HANA Cloud and other dimensions maintained only in SAP Analytics Cloud. 

To add these dimensions use the modeler. Add a new dimension or an existing dimension to the model. Incorporate all the given dimensions for the liquidity planning.

You can create dimensions, and add existing dimensions to new or existing models. You can also delete dimensions.

To build your model either add existing dimensions (public) or add private dimensions as needed here. For private dimensions it is also possible to define other attributes via the dimension settings.

After laying out the dimensions there is also the possibility to add hierarchies. Hierarchies let you structure your data. When you display data in stories in a table, the nodes of the hierarchy can be expanded or collapsed.

There are two types of hierarchies that can be added and used for the liquidity planning. These are:

• Level-based hierarchies: A level-based hierarchy organizes the members of a dimension into levels, such as Country, State, and City. You can add level-based hierarchies to generic dimensions and organization dimensions by selecting a dimension, and then from the Dimension Settings panel, selecting  Create Hierarchy → Level-Based Hierarchy.

  You then define your level-based hierarchy in the Hierarchy Builder. Click  to create a new hierarchy. Name it, and then select the dimension columns to use for creating the hierarchy. Select  again to create more hierarchies. At any time, you can select the  icon beside Hierarchies in the Dimension Settings panel to create, edit, and delete level-based hierarchies.

• Parent-child hierarchies: A parent-child hierarchy organizes the members of a dimension into a set of parent-child relationships. You can add parent-child hierarchies to generic dimensions and organization dimensions by selecting a dimension, and then from the Dimension Settings panel, selecting  Create Hierarchy → Parent-Child Hierarchy.

  When you add a parent-child hierarchy, a new column is inserted into the grid. Add the parent ID values to the hierarchy column . Select () beside Hierarchies in the Dimension Settings panel to create more hierarchies.

  To see a parent-child hierarchy's structure, open the Hierarchy Maintenance view by selecting one of your parent-child hierarchies in the Dimension Settings panel. Here, you can drag members to build the parent-child relationships visually. If more than one hierarchy has been defined, you can select which one to work with from the drop-down list.

• Hierarchies in other dimension types:

  Other types of dimensions don't support custom hierarchies:

  • The Account dimension has only a single hierarchy.
  • For the Date dimension, hierarchies are predefined based on the model granularity, and on whether you've enabled fiscal time for the model. You can specify a default hierarchy in the settings for the Date dimension.
  • The Version dimension doesn't have a hierarchy, since different versions are separate and don't have parent-child relationships.

Note

A dimension can have one or more level-based hierarchies, or one or more parent-child hierarchies, but not both.

Use parent-child hierarchies to structure your data into parent-child relationships. When the data is displayed in a story, hierarchies can be expanded or collapsed. You can create a parent-child hierarchy during the data-preparation stage, or in the Modeler.

As described use the modeler, select a dimension, and open the Dimension Settings. Now choose Create Hierarchy → Parent-Child Hierarchy.

Enter a name for the parent of the hierarchy, enter a description (optional), and then choose Done. The new hierarchy is added as a new column for the dimension.

Switch to the grid view, and then type or paste data into the cells of the parent column.

Use level-based hierarchies when your data is organized into levels, such as Product Category, Product Group, and Product. When the data is displayed in a story, hierarchies can be expanded or collapsed.

Again you will be able to create a level-based hierarchy during the data-preparation stage, or in the Modeler.

In the Hierarchy Builder, enter a name for the hierarchy. Select columns to build your hierarchy.

After you have outlined all of the needed dimensions for the model it is time to add some data. In the modeler there are two tabs; Model and Data Management. In the Data Management tab you can link a data source. You can create a connection that lets you import data from SAP S/4HANA using generic OData services.

In the Import Data from SAP S/4HANA Cloud screen, either select the connection details that are already set, or create a new connection here on the screen.

After setting the connection details, you need to select the query to the SAP S/4HANA Cloud system. The C_CASHFLOWITEMBASIC query contains a certain set of available data.

You can drag and drop these elements to the selected data area. For the Liquidity Planning we are using all of the items.

When you import your new data source, SAP Analytics Cloud automatically maps it to your existing model. However, you may need to manually make some adjustments.

In the modeler, you'll see a panel on the right side. Here you can see all the mapping options as well as the import method options.

• Update: Updates the existing data and adds new entries to the target model
• Append: Keeps the existing data as is and adds new entries to the target model
• Clean and Replace: Deletes the existing data and adds new entries to the target model

When we apply any changes, the affected columns become highlighted in green.

Once all your dimensions and measures have been mapped, the proper attributes have been assigned, and there are no data quality issues, your model mapping is complete. You'll see a notification in the right-side panel.

Once you choose Finish Mapping and save your model, any stories created using this model will automatically be updated. Model mapping in SAP Analytics Cloud is a great way to save time, especially when importing data from multiple data sources.

After you have finished the mapping your query information is stored in the data management section of the model. The following options are available for the import job:

• Edit the query
• Schedule the query (update)
• Import settings
• Mapping table
• Deleting the source

From the section you also see when the last update to the query has taken place. You can also refresh the source information from here directly.

Data actions are processes that allow you to trigger sequences of copy and paste actions and scripted calculations on planning models from stories.

For Liquidity Planning there are basically three data actions you can use:

• Copy Data to Last Year Actual
• Calculate Closing and Carry Forward
• Copy Data to Version Forecast

These scripted calculations help to perform certain tasks within stories.

1. Go to the Home page and choose Main Menu → Browse → Processes → Data Actions.
2. Select SAP__FI_CLM_LIQPLN_AF_LYA from the list of data action names. Select the copy action Copy Last Year Liquidity Items.
3. In the Filters section, select the Version filter.
4. Select LY Actual to represent the last year actual cash flows mapped from actuals during data wrangling.
5. In the Copy Rules section, select Add Copy Rule.
   • Select Audit Trail dimension to add the first rule.
   • Select S4HANA Cloud as source member (From), select OK.
   • Select SAP Analytics Cloud as target member (To), select OK.
   • Select Time dimension to add the second rule.
   • Select the time period to copy from as source member (From), select OK.
   • Select the time period shifted by one year later as target member (To), select OK.

6. Select the Save Data Action icon from the menu.

For more information on how to check or create the other two data actions for Closing - Carry Forward and Copy Last Year Forecast, see the test script of the Best Practice Scope Item 3Y0 - SAP Liquidity Planning for SAP S/4HANA Cloud.

The data actions can be integrated into a story. Select the Insert button at the top and choose Data Action Trigger.

From the Builder you can now fix the name and description plus the actual data action you want to include. The data actions can also be maintained in the Admin Work Area tab.

To create a Liquidity Planning story in SAP Analytics Cloud there are several steps that need to be considered.

1. Creating a story is easiest if you use templates from the SAP Analytics Cloud. This gives you a head start over assembling all the elements individually in the story.
2. Nonetheless this does not mean you can add your company style to the planning sheet. Make use of the extensive possibilities to customize the sheet the way you and your team need it.
3. After you have done the groundwork it's time to add data. Use the model defined earlier to incorporate all the needed information.
4. To have your team working with the planning sheet it is recommended to add a private version for the specific planning cycles. This way everyone can change and update values easily.
5. Finally it is time to add a input task to the planning sheet. Here the assignees (such as subsidiary cash specialists) are matched to their respective organizations. Having done this, the planning cycle can start.

To launch a story use the menu path Main Menu → Create → Story.

There are two ways you can apply a formatted template to your story. Both ways begin with you creating a new story. When you choose Create → Story from the menu, you are presented with an option to choose a template.

These templates make it even easier for you to tell great stories that connect with audiences. Stories are meant to be shared. As such, you'll want to present the information in a way that's pleasing to the eye and conveys your message clearly.

One really useful feature in SAP Analytics Cloud is the preformatted story templates.

The preformatted story templates in SAP Analytics Cloud offer a variety of story layouts for you to choose from. These templates include placeholders that are already aligned so that you can simply choose which measures and dimensions you want to include in your story. Further formatting can be applied to your story, but it isn't necessary.

From here, you can select the template that suits you best. The new story template will open, allowing you to replace the placeholder objects with your charts, tables, and graphs. To further customize the layout of your story, you can use the various formatting tools such as adding images, shapes, and text. All elements can be repositioned, resized, or removed.

If you want to create a new story for Liquidity Planning, it's best to use a responsive page.

Once the responsive page is selected there are several ways of adding information to the empty sheet.

To start the liquidity planning, add a table to the story that contains the model information previously created. 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 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.

For the model you can select public or private models.

Note

If your story already has a model or data source on any page, that data source is used automatically for new models added to canvases or responsive pages. If there is more than one data source, the most recently used one is applied to new tables.

Depending on your needs you may change the initial layout of the inserted table. You can change the default design of a table in the Builder tab.

The builder contains the following sections:

• Data Source:

  The data source is displayed in this area.

• Table Structure:

  Choose Swap Axis to swap rows and columns.

• Rows and Columns:

  All dimensions and measures used to create the table are displayed in this area. You can add additional dimensions to rows and columns.

  When you hover over a dimension, you can choose Filter to add or modify filters.

  To make other modifications to the dimension, choose More and then choose one of the following options:

  • Hierarchy: Choose a different hierarchy to display for the dimension. For example, you can choose to display different periods for the Date dimension. You can also select Flat presentation to flatten the hierarchy of a dimension. (This option is not valid for an Account dimension.) To only show the leaf members of the hierarchy, turn on the Show only leaves in widgetswitch. For example, you can use this option while planning, if you want to enter data only at the leaf level of the dimension.
  • Display Options: Show the member description, ID, or both the ID and description.
  • Properties: Select multiple properties to display in the table, including ID and description in separate columns or rows.
  • Unbooked Data: Show or hide unbooked data. When unbooked data is hidden, only cells in the grid that contain data are visible.
  • Show Totals: Show the sum of the dimension values.
  • Rename: Provide a customized description for a dimension in your table rather than using the default value. (While you can't rename the Account dimension, you can select its members and rename them.)

Note

For hierarchical dimensions, the total is added to the top-level node only. The total does not change when you drill into the hierarchy. Create Top N does not change the total either, as it applies to all the data, not just the top values.

In order to change the table structure you can use the designer in SAP Analytics Cloud. The Designer itself consists of the Builder and the Styling panel.

The Builder lets you modify the table structure in terms of rows, columns or filter criteria to be applied in your planning model.

You can change the look of a table tile including its placement on the canvas page, border format, cell highlighting, and so on.

To add any kind of styling to the table, open the Designer panel and choose Styling.

The Styling panel displays options available for the selected tile type. Some options may not be available to all users. You see only the styling options for the specific area that you have highlighted. The heading in the Styling panel identifies the area. For example, it may show Title, Data Cell, Axis Labels, and so on. Selecting a different part of the table changes the heading and the styling options.

There are many options for styling your table. Choose from different template, colors, fonts set formatting rules, or select the number of decimals of your numbers. This will help to shape the story in exactly the way you need it.

Once you have created a table on a story page, there are several options available in table-specific action and context menus.

The table-specific menu options let you work with the data and change the appearance of the whole table, as well as letting you work with individual table cells.

Note

When your table is in edit mode, you will see all available options. When your table is in wiew mode, some options will be hidden.

In general three action menus are available:

• Table Action Menu: use to select top N items, sort, do mass data entry, and so on. Appears when the table tile is selected.
• More Table Actions: an additional set of actions that apply to the table, including freezing columns, adding dynamic text, and so on.
• Table Cell (Context) Menus: use from a table cell to add calculations directly in the chart, to create new members, set thresholds, and so on. Appears when you right-click a table cell.

Once all the styling is done it is time to create a private version for the planning. This private version is used to change or simulate plan values without making the changes visible to anyone else in first place. When you save a private version, it gets changed to a public version, and the private version is dropped.

To do this, go to the Version Management of your story. Use the More button to find this element. This opens the side panel with an overview of all available versions. Choose the More button (…) at the plan field. Create the new version with category planning and as a blank version. This immediately adds a new column to the table where users can add their data.

Through the input task you basically link a person (assignee) to a organization. This person receives a task and is thereby requested to add information and then returns the task.

To create an input task, you must have a table that has the following criteria:

• Is on a canvas or a responsive page
• Uses a Planning model
• Is based on a model that has one or more dimensions with responsible users assigned to the dimension members. For example, the model may have an Organization dimension with users responsible for different regions or departments, and a Product dimension with users responsible for different groups of products.
• Has one active private version