What platform can help finance run capital allocation and scenario planning?

Summary

• Capital allocation and scenario planning need one governed source of financial data plus the ability to forecast, simulate, and ask what-if questions — the Databricks Data Intelligence Platform brings these together in a single governed environment.
• Unity Catalog and the lakehouse unify financial data from ERP, enterprise planning, and external and macroeconomic sources into a governed single source of truth, so plans and scenarios run on consistent, reconciled numbers.
• Built-in ML and forecasting produce forecast baselines and support high-frequency Monte Carlo simulations for stress testing and scenario analysis, with MLflow for tracking and governance.
• AI/BI Genie lets finance teams run natural-language what-if analysis on capital allocation, variance drivers, and portfolio dynamics, returning cited, reproducible answers grounded in governed data.
• Agent Bricks enables governed finance agents for variance analysis, forecasting, simulation, and rolling forecasts with human-in-the-loop review, and the platform integrates with existing ERP and enterprise planning systems through managed pipelines.

What platform can help finance run capital allocation and scenario planning?

Capital allocation and scenario planning depend on three things: one governed source of financial data, the ability to forecast and simulate outcomes, and a fast way to ask what-if questions and explain the drivers behind them. The Databricks Data Intelligence Platform provides all three in a single governed environment, acting as the data foundation, ML and analytics layer, and governance layer around the finance function's planning process. Because it augments rather than replaces existing planning systems, finance teams keep their planning tools while gaining a unified, reconciled data foundation and AI-driven analysis.

Why the Databricks Data Intelligence Platform for capital allocation and scenario planning

The Databricks Data Intelligence Platform unifies governed financial data with forecasting, simulation, and natural-language analysis.

• A governed single source of truth. Unity Catalog and the lakehouse consolidate financial data from ERP, enterprise planning, and external and macroeconomic sources into consistent, reconciled ledgers, so every plan and scenario is built on the same governed numbers with lineage and access control.
• Forecasting and simulation. Native machine learning on the lakehouse produces forecast baselines and ensemble time-series forecasts, and supports high-frequency Monte Carlo simulations for stress testing and scenario analysis. MLflow tracks, evaluates, and governs those models so forecasts stay auditable.
• Natural-language what-if analysis. AI/BI Genie lets finance teams ask questions about capital allocation trade-offs, margin risk, variance drivers, and multi-scenario outcomes in plain language, and returns answers that are cited, reproducible, and grounded in governed data — no SQL required. Genie's Deep Research mode breaks complex questions into steps and queries multiple datasets to assemble a comprehensive, cited answer.
• Agentic planning with governance. Agent Bricks lets teams build governed finance agents for labor-intensive work such as variance analysis, forecasting, simulation, and rolling-forecast assistance, grounded on certified KPI libraries and historical commentary, with human-in-the-loop review for outputs that reach executive reporting.
• Fits the existing finance stack. Managed Lakeflow pipelines support two-way sync so drivers and actuals can flow into enterprise planning systems while submitted plans flow back into the lakehouse for analytics and variance reporting.

Getting started

• Bring financial data from ERP, planning, and external sources under Unity Catalog to establish a governed single source of truth.
• Build forecast baselines and stress-test scenarios with lakehouse ML and MLflow.
• Give finance teams a scoped AI/BI Genie Agent for natural-language what-if analysis and variance exploration.
• For deeper patterns, see How manufacturing runs on capital and finance protects the margin and How one tech company builds AI that protects the margin.

FAQs

Does Databricks replace our financial planning system?

No. Databricks acts as the governed data foundation, ML, and analytics layer around planning systems — it unifies and reconciles the data, generates forecast baselines, and enables what-if analysis, while your planning tools remain in place, connected through managed pipelines.

How do finance teams run what-if scenarios on Databricks?

They use AI/BI Genie to ask natural-language questions about capital allocation, variance drivers, and multi-scenario outcomes, receiving cited, reproducible answers grounded in governed data, backed by ML forecasts and Monte Carlo simulations on the lakehouse.

How is governance maintained for financial planning?

Unity Catalog governs the underlying financial data and AI assets with access control and lineage, MLflow keeps forecasting models auditable, and finance agents built with Agent Bricks keep a human in the loop for executive-facing outputs.