- SAP Managed Tags
LIVE (Seamless) planning as the backend enabler for simplifications and real-time steering
MOTIVATION
In today's fast-paced business world, the ability to effectively steer and lead an organization is fundamental for achieving strategic goals and maintaining a competitive edge. A key success criterion is the capacity to fully harness and derive value from organizational data. Many companies struggle with data problems, such as fragmented information, outdated systems, and the super important task of preparing data for emerging technologies like AI. Recognizing these challenges, we are excited to introduce a blog series dedicated to showcasing the substantial business value of SAP Business Data Cloud (BDC) in the context of planning and analytics.
The motivation behind this initiative is to provide a comprehensive exploration of how SAP BDC capabilities as essential instruments, facilitating robust strategic alignment and guiding effective decision-making processes across diverse organizational requirements. We aim to illustrate how SAP BDC, equipped with powerful data management, planning, analytics and innovative AI capabilities, empowers organizations with enhanced business steering agility by providing real-time insights, streamlined data management, and automated decision support – going from insights to action, helps mainly leaders guide their businesses with precision.
Our blog series will provide valuable insights for decision-makers seeking to harness SAP Business Data Cloud (BDC) to enhance operational efficiency, optimize resource allocation, and achieve long-term objectives. By featuring detailed planning & analytics topics, the series will illustrate the transformative impact of SAP BDC in addressing the operational complexities of today’s business environment. This first introductory blog post will spotlight the strategic advantages of SAP BDC, particularly in the context of Business Steering, setting the stage for a deeper exploration of its benefits throughout the blog series.
There are several blog posts in the series that will cover advantages of SAP BDC in the context of business steering, so please stay tuned for the upcoming blogs:
- The Value of SAP BDC in the context of business steering
- Planning & Analytics is an essential part of SAP BDC
- Key Planning & Analytics components of SAP BDC
- Is AI going to “retire” a dashboard?
- Simulations, a game changer in today’s volatile world
- Extend existing planning scenarios of SAP BPC/BW-IP in SAP BDC
- Real-time steering with LIVE planning (THIS BLOG POST)
- PaPM - The role of business calculation engine in business steering
- Self – service analytics and real-time business steering
- Business steering powered by AI agents
- Leverage data products in the context of planning & forecasting
- Introducing AI/ML capabilities by SAP Databricks
INTRODUCTION
In my previous blog post of our BDC Business Steering series, I highlighted the key Planning & Analytics components of SAP Business Data Cloud (BDC), explaining how they help organizations streamline planning and analytics processes, enhance decision-making, boost efficiency and drive business value.
SAP BDC delivers Seamless Planning, a unified enterprise planning paradigm enabled by deep integration between SAP Analytics Cloud (SAC) and SAP Datasphere (DSP). Through this integration, SAC planning model data is stored directly in SAP Datasphere, providing native connectivity to SAP and non-SAP data sources as well as to SAP BDC Data Products. This ensures organizations can operate on trusted, consistent data structures fully aligned with operational data. Seamless Planning unifies planning logic with enterprise-grade data storage and governance. SAC remains the user-friendly planning experience and calculation engine, while Datasphere serves as the authoritative, governed persistence layer for plan and master data, integrated with other data sources. This architecture provides flexibility and multiple extensibility options by leveraging DSP’s ETL capabilities or applying advanced ML/AI through SAP HANA Cloud and SAP Databricks.
The latest evolution of Seamless Planning brings the integration of external data sources directly into SAC planning models as Live Versions, as detailed by @MaxGander in an excellent recent blog post. Introduced in Q4 2025, the External Live Version Data Sources innovation significantly reduces traditional data-import workflows in SAC planning models and eliminates data movement between planning domains, enabling a fully integrated, real-time planning experience.
In this blog post, I will illustrate a practical end-to-end use case that leverages External Live Versions in SAC planning powered by SAP Datasphere. The result is a real-time, holistic view of business insights that enhances steering agility, streamlines data management, and supports automated decision-making across the entire planning and analytics workflows.
A FEW WORDS ABOUT THE USE CASE EXAMPLE
The example use case is about Brand Profitability Planning strategic process of aligning a company's branding strategies with its financial goals. The focus is on creating and maintaining a strong brand identity that not only resonates with customers but also drives long-term profitability.
With SAC and DSP Seamless Planning in SAP BDC, a Commerce Manager can quickly identify when brand commercial margin forecasts fall below budget and take proactive action by running simulations and predictive analyses using live connected reference data. They can also incorporate multiple influencers, integrated as external live data versions, to further refine projections. The CFO can then immediately assess the impact on the P&L, supported by real-time planning and analytics capabilities.
The architecture and data flow are as follows:
- Actual profitability data from the SAP ERP system is stored in SAP Datasphere (DSP).
- This actual data is exposed as an external Live Version within the SAC Planning Brand Profitability Model, which resides in SAP DSP.
- Reference data (e.g. prior forecasts) is also integrated as an external Live Version in the same planning model.
- Influencer data used for predictive scenarios is integrated as an external Live Version to enrich the planning model.
- The SAC Planning Brand Profitability experience (stories, business logic, predictions, simulations, etc.) operates directly on these live data versions, while plan data is persisted into the underlying SAP DSP exposed table of the SAC Planning Brand Profitability Model.
- Real-time reporting and variance analysis are performed in SAP Analytics Cloud using the DSP Analytic Model.
STEP-BY-STEP EXECUTION
1. Brand Profitability Analysis
The Commerce Manager conducts multiple profitability analyses to identify underperforming brands and simulates strategies to improve their profitability. Analyzing the commercial figures indicates that we are currently under budget according to the current forecast. After a detailed analysis, examining each brand individually, identifies the responsible brand that requires attention and corrective measures to ensure the accuracy of the forecast plan.
Technical setup: The above SAC visualization story is built on top of a DSP Analytic Model for real-time variance analysis, integrating actuals and plan data through a DSP view that combines ERP actuals with the plan fact data from the SAC planning model. After each new forecast update is published, the plan data becomes real-time available in the variance analysis report—with no additional data movements, replications, or delays.
2. Driver-based Simulations / Scenario Planning
The Commerce Manager initiates a new forecast by creating multiple scenarios for the key profitability drivers. Scenarios 1 and 2 are driver-based, with scenario specific inputs applied accordingly (e.g., Scenario 01: pessimistic, Scenario 02: optimistic). These scenarios leverage the reference dataset, such as the previous forecast, made available as an external Live Version. For variance analysis during the simulation process, prior year actual is also integrated in real-time through a Live Version in SAC Planning, extended also with the planning business logic on-the-fly (e.g., Gross Margin (%) and Commercial Margin (%) calculations are executed for the actual and plan versions) to provide immediate, accurate comparisons.
Technical setup: Actuals are integrated as a Live Version into the SAC Planning Brand Profitability model, enabling on-the-fly variance analysis against plan versions and supporting account and measure level calculations directly on live version data. The source for this actuals Live Version is a DSP view exposed for consumption.
Previous Forecast data is also integrated as a Live Version and serves as the baseline for driver-based scenario plan version calculations, allowing SAC data actions to perform business calculation calculations directly on top of live versions.
3. Predictive Scenario Planning
The third scenario is prediction-based, leveraging various KPI influencers alongside external data (e.g., the CPI index) sourced from the DSP Marketplace. The Commerce Manager updates the influencer values for the predictive model, and once configured, the predictive scenario can be executed. In this example, the predictive scenario for Gross Sales uses an external Live Version as the baseline, integrating actual data, CPI data, and the manager’s forecasted influencer values directly within SAP DSP.
Technical setup: The baseline version for the predictive scenario is connected as an External Live Version in the SAC Planning Brand Profitability model, integrating actual data, CPI data, and the Commerce Manager’s forecasted influencer values directly from SAP DSP plan fact table. The source for this Predictive Live Version is a DSP view activated for consumption. A multi-action then executes the predictive scenario and triggers the additional data-action calculation steps required to produce the complete commercial margin for the predictive scenario. You can find more details about Time Series Forecasting and Predictive Planning in SAC in the blog post.
4. Simulating and creating the new Brand Forecast
After identifying optimization opportunities, the Commerce Manager can simulate proposed adjustments and assess their potential impact using SAP Analytics Cloud’s out-of-the-box Value Driver capabilities. Optionally, a stochastic risk simulation (Monte Carlo Simulation) for each scenario can be performed through the embedded SAC Compass functionality. Once satisfied with the simulation results and the projected figures of the preferred scenario, the Commerce Manager proceeds to publish this scenario to the brand forecast.
Technical setup: Standard out-of-the-box simulation capabilities are configured in SAC. In the value driver tree widget, the LY Actual calculation is enabled on top of the External Live Version containing the actual data.
5. Brand Forecast Allocation
The commerce manager will execute the allocation of Brand Forecast to all product and customer combinations based on the on last year Gross Sales proportionate.
Technical setup: Standard out-of-the-box allocation and advanced formulas data action steps are configured in SAC.
6. Updated Forecast and Financial view Evaluation
Once the updated forecast allocation is executed and all unassigned data is done, the commerce manager has to publish the results. Having that done, all results are available in the Brand Profitability Analysis and the P&L in real-time!
Technical setup: As outlined in Step 1, the SAC visualizations are built on DSP Analytic Models for real-time variance analysis, integrating actuals and plan data through DSP views. Once a new forecast update is published, the plan data becomes immediately available in the brand profitability analysis reports, such as the P&L, without any additional data movements, replications, or delays. See below the DSP view used for real-time P&L reporting, which leverages the Brand Profitability view along with views from other planning domains.
SUMMARY
In this blog post, I demonstrated a practical end-to-end use case that leverages External Live Versions within the SAP BDC Seamless Planning architecture. This capability is a game changer, enabling real-time business steering by unifying actuals and plan data across planning domains to deliver a holistic, trusted view of performance.
Key takeaways from the use case:
- External Live Versions can be applied throughout the planning workflow—stories, data actions, predictions, calculations, and more.
- They enable robust variance analysis by enriching actuals with planning-model logic and calculations.
- Seamless Planning reduces data redundancy and lowers total cost of ownership.
- It provides the flexibility to decouple planning and reporting using DSP Analytic Model capabilities.
- Planning logic can be enriched through DSP’s ETL capabilities and advanced ML/AI extensions via SAP HANA Cloud and SAP Databricks within SAP Business Data Cloud.
Additionally, SAP BDC has the potential to further enhance Seamless Planning by:
- Supporting planning-enabled intelligent applications that blend analytics with actionable workflows.
- Enabling the direct consumption of BDC governed data products within planning processes.
- Extending planning architectures to include platforms such as SAP Databricks and Snowflake.
This is just the beginning—more innovations are on the way!
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