In this webinar, we cover:
- Why planning architecture matters more than adding new AI features.
- How unified data improves forecast accuracy and agility.
- What an AI-ready planning landscape looks like in practice.
- A live walkthrough of a Seamless Planning approach.
If AI is on your roadmap, your data foundation must be part of the strategy. Learn how connected enterprise data enables smarter forecasts, faster decisions, and more confident planning outcomes.
Enterprise planning is undergoing a fundamental shift. Traditional FP&A platforms were designed for structured budgeting, forecasting, and scenario planning. But today, finance teams operate in an environment defined by exploding data volumes, constant volatility, and increasing pressure to apply Artificial Intelligence directly to planning decisions.
This new reality requires more than incremental improvements to existing tools. It requires a new data foundation for planning.
This is where SAP Business Data Cloud (BDC) becomes a critical enabler for AI-driven planning.
In traditional architectures, planning data largely lived inside SAP Analytics Cloud (SAC). While SAC provides strong governance, hierarchy management, and write-back capabilities, the data was not easily reusable at enterprise scale for advanced analytics or machine learning.
BDC changes this model.
With BDC, planning data is persisted in SAP Datasphere and exposed as governed Data Products. This means planning data can be reused, enriched, and analyzed across the enterprise without losing SAP’s financial semantics or governance.
Instead of extracts, copies, and flattened datasets, organizations now have a reliable foundation where planning data remains consistent, trusted, and ready for broader analytical use.
BDC’s native integration with Databricks introduces elastic compute for advanced analytics and machine learning.
This is a significant architectural evolution.
Rather than running simulations and forecasts on exported spreadsheets or replicated data:
Finance users continue working in SAC. Data scientists and AI teams operate in Databricks. Both rely on the same governed data foundation created by BDC.
Core planning logic, hierarchies, governance, and write-back continue to reside in SAC. Finance teams retain the control and discipline they depend on.
Complex forecasting models and simulations run without affecting planning performance.
There is no hierarchy flattening and no loss of financial meaning. AI models work on semantically rich, governed data.
Planning data can now be blended with operational, market, and external datasets to create smarter forecasts and more adaptive scenarios.
The combination of BDC and AI transforms planning from a static, periodic activity into a continuously learning system.
AI is no longer an experiment outside FP&A. It becomes part of how planning works.
By combining SAP Business Data Cloud with AI and machine learning:
This is not about replacing planning.
It is about augmenting planning with intelligence.
BDC provides the architecture.
AI provides the insight.
Together, they define the next generation of enterprise data analytics and planning.