For decades, the world of Financial Planning and Analysis (FP&A) has been defined by a fundamental compromise. On one side, you have the operational reality of the business—a vast, ever-expanding universe of data generated from sales transactions, marketing campaigns, supply chain logistics, and HR systems. On the other, you have the FP&A application—a walled garden, a proprietary silo where planning, budgeting, and forecasting happen in isolation.
The bridge between these two worlds has always been a rickety, high-maintenance structure built from complex ETL scripts, manual data exports, and brittle integrations. This is the architecture of yesterday. It forces us to move and duplicate data, creating latency, version control nightmares, and a fundamental disconnect between financial plans and operational realities.
But a tectonic shift is underway, driven by the rise of the modern data stack. Today, enterprises are consolidating their data into powerful, scalable cloud data platforms like Snowflake, Databricks, and Microsoft Fabric. These data lakes and lakehouses have become the undisputed center of gravity for enterprise data, the single source of truth for analytics and business intelligence.
This raises a critical question for every CFO and finance leader: If your data has a new home, why does your planning still live somewhere else? The answer is simple: it shouldn’t. The future of FP&A is not in another silo. The future of FP&A is on the data lake.
Traditional Enterprise Performance Management (EPM) and FP&A tools were designed for a different era. They were built on the premise of their own proprietary databases, creating an island of financial data that was necessarily separate from the ocean of operational data. This architecture, while functional, comes with a heavy tax—one that modern businesses can no longer afford to pay.
The most immediate pain point is the endless cycle of data movement. To create a budget or a forecast, finance teams must first extract data from ERPs, CRMs, and HR systems, transform it, and load it into the planning application's database. This process is not just slow and resource-intensive; it's a constant source of errors and delays. By the time the data is ready for analysis, it’s already stale. This latency makes true continuous forecasting impossible and relegates FP&A to a reactive, backward-looking function.
When data is duplicated, so are the problems. Inevitably, the numbers in the planning silo diverge from the numbers in the data warehouse or the source systems. This leads to the all-too-familiar boardroom debate: "Which numbers are we looking at?" Finance and operations teams spend countless hours in reconciliation, eroding trust and wasting valuable time that could be spent on strategic analysis.
Legacy EPM databases were never designed to handle the sheer volume and variety of data available in a modern enterprise. They struggle to support the kind of granular, driver-based planning that businesses need today. Want to plan at the SKU level for a global retail operation? Or forecast based on daily transactional data? The proprietary databases of legacy systems often hit a performance wall, forcing companies to plan at an aggregated, less accurate level.
Perhaps the most significant cost in today’s environment is the AI readiness tax. Gartner’s 2024 research (The Evolution of Data Management Survey) shows that making data AI-ready is a top-five priority for 77% of organizations. However, a siloed architecture makes this goal nearly impossible to achieve.
When plan and forecast data is locked away in a separate EPM application, your enterprise AI models—which live on the data lake—are blind to it. They have the rich history of your company’s sales and operations but limited visibility into the details of your forward-looking plans and assumptions. Conversely, any "AI" features within the planning tool are starved of the rich, granular operational data that provides the context needed for accurate predictions. This forces a dilemma: which incomplete AI would you subscribe to?
The modern solution flips the old model on its head. Instead of moving mountains of data to a small, isolated planning application, you bring the planning application to the data. By running your EPM suite as an intelligent layer directly on top of your enterprise data lake or lakehouse, you eliminate the compromises of the past and build a foundation for a truly strategic FP&A function.
When your planning, analytics, reporting and other data apps all run on the same unified data platform, reconciliation becomes a thing of the past. Finance, sales, and operations are all looking at the same data, using the same definitions and business logic. This builds trust, fosters collaboration, and ensures that decisions are based on a consistent, universally understood view of the business.
The modern data platform is built for performance at scale. By leveraging its power, an Enterprise Performance Management platform running directly on your data allows you to perform planning and analysis on your most detailed, transaction-level data without performance degradation. This enables driver-based models of unprecedented accuracy and allows for real-time scenario modeling that was previously unthinkable. You can re-forecast in minutes, not weeks, giving your organization the agility to respond to market changes with confidence.
This is the game-changer. By unifying your actuals, plans, forecasts, and third-party data within a single platform, you create the rich, contextualized dataset that is the essential fuel for effective AI. There is no longer a dilemma of which AI to use. Your AI models, whether for predictive forecasting, anomaly detection, or generative insights, have access to the complete picture. This architecture doesn't just support your current AI initiatives; it future-proofs your entire EPM strategy.
This architectural shift does more than just improve efficiency; it fundamentally transforms the role of the finance organization.
The center of the enterprise data world has moved. It is no longer a collection of application-specific databases but a unified, scalable, and powerful cloud data platform. Continuing to run FP&A in a separate silo is like asking your most critical business function to work from a remote island with a dial-up internet connection.
The future of FP&A is integrated, real-time, and AI-powered. That future is not possible with the architecture of the past. It's time to stop moving your data to your plans and start bringing your planning to your data.
Lumel enables finance teams to plan directly on the data lake - no silos, no delays, just real-time, AI-ready insights. Reimagine FP&A with Lumel: unified data, faster decisions, and strategic impact at scale. The firm was recognized as the Best Overall Vendor for EPM in 2025.
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