The FP&A Stack Is Collapsing—Here’s Why That’s A Good Thing

You didn’t ask for a bloated FP&A stack. But if you’re in finance, chances are you’ve inherited one—a fragile mess of spreadsheets, BI dashboards, planning tools, and SaaS platforms duct-taped together to get the job done. My guess is, it’s slow, error-prone, and built on workflows that should’ve been retired a decade ago.

You didn’t ask for a bloated FP&A stack. But if you’re in finance, chances are you’ve inherited one.

I know this because I lived it. Before joining the team at Sigma, I spent 15 years in finance, accounting, and M&A. As a former Corporate Finance Director, I ran budgeting, forecasting, and financial reporting for a manufacturing company. We tried everything to modernize: FP&A software, BI tools, custom pipelines. But it wasn’t until we collapsed the stack into cloud data warehouse and Sigma that things actually started working.

Now I help other teams do the same. This is what it looks like to rebuild FP&A for the modern data stack, and why it’s so much better.

The legacy stack is breaking—and good riddance to it

In my last finance role, the tech stack looked modern on paper. In practice, it was anything but. We had a dedicated FP&A tool for planning and forecasting, Power BI for revenue reporting, ADP for comp planning, and NetSuite for operational data. Market benchmarks came from browser tabs. The only way to bring it all together was by exporting everything into Excel and stitching it together manually. We’d spend hours cleaning, aligning, and formatting just to build a view of the business that was already out of date by the time it was finished. 

Any time someone had a follow-up question, we’d go back to the beginning—pull new data, rebuild the logic, and hope it all tied out. It was repetitive, time-consuming work that left little room for actual analysis. And even when a report looked good, there was always that lingering doubt: did we get the full picture?

This is still the norm for a lot of finance teams. But it’s a model that’s quickly falling apart.

As soon as we moved to a CDW, the cracks in that old system became impossible to ignore. For the first time, we had governed, refreshable, real-time access to everything, all in one place. And because Sigma inherits permissions directly from the CDW, that governance was automatic, with no need to manually configure access controls in yet another system. It meant every user only saw the data they were allowed to see, and we could move quickly without sacrificing security or compliance.

The warehouse is the new core of the finance stack. The tools layered on top need to meet that moment.

But the FP&A tool we’d relied on didn’t plug into that ecosystem. We were forcing it to do a job it was never designed for. That’s when it became clear: the warehouse is the new core of the finance stack. And the tools layered on top need to meet that moment.

What the modern stack should actually look like

Once we embraced that fact, the rest of the picture came into focus. We realized that what we truly needed was a single, unified layer on top of our CDW. That’s exactly what Sigma delivered. It connects directly to our CDW and speaks spreadsheet natively—without cubes, extracts, or compromises. It looks and feels familiar to finance users, but under the hood, it’s built for scale. You can pivot on trillions of rows, filter in real time, drill into transactions, and trace numbers all the way back to the source.

Sigma is the only Analytics platform allowing teams to take action on data. You can natively write back to the CDW, allowing you to build apps for reporting, reconciliation, approval flows and forecasting. For example, we’ve used writeback to log vendor performance issues directly from a report, capture inventory risks the moment they’re spotted, and feed those updates straight into our planning models. We’ve used it to build forecasting logic, operational inputs, and AI-generated commentary into a single experience. And when we use Ask Sigma’s AI, every query runs inside the CDW environment—no data is sent to third-party models, nothing is stored outside the warehouse. That means we can safely ask for a regional sales summary, a variance explanation, or a forecast narrative without exposing sensitive financials.

Sigma is the only Analytics platform allowing teams to take action on data.

The result was astounding. Instead of chasing data across five systems, I could pull financial and operational inputs together instantly, or forecast revenue by region, and track inventory risk by vendor. I could drill into cost centers without exporting a single row, or pivot from a high-level dashboard to a transaction-level view in seconds. And when my team needed to collaborate with stakeholders, we were all looking at the same data. In short, we were making decisions faster, with more context, and less back-and-forth. 

Check out how financial reporting in Sigma works here.

How Sigma differs from traditional EPM and financial planning software

What makes Sigma stand out is that every other tool lives separately from where your data actually resides. Think about your current setup—you probably have integrations connecting your planning system to various data sources; ETL processes moving data around; and separate security models to manage. There's really no such chaos with Sigma.

Once you have permissions set up in the warehouse (which takes minutes, not weeks), you immediately have access to all the data stored there. If you already have views or tables that your team reports on, those become available instantly—no data movement, no separate integrations to maintain, no wondering if your planning tool is showing you the latest data.

With Sigma, you get to leverage all the functionality already built into your cloud data warehouse to rapidly build analytics, apps and AI.

But here's the bigger differentiator: innovation. You get to leverage all the functionality already built into your cloud data warehouse to rapidly build analytics, apps and AI. That includes your existing permissions and governance, any ML models you've developed, AI functionality you have access to. All of it becomes available on day one. Your EPM tool can't tap into the machine learning model your data science team built to predict customer churn, but Sigma can.

A smarter way forward

Most finance teams don’t need more tools. They need to support revenue generating activities for the business. When the reporting stack gets out of the way, you start operating differently. You spend less time chasing numbers and more time shaping outcomes. You stop reacting and start forecasting with intent.

It’s about clarity as well as speed, automation and alignment. When finance has the right foundation, the work stops being about reports, and starts being about impact.

It’s about clarity as well as speed, automation and alignment. When finance has the right foundation, the work stops being about reports, and starts being about impact. This is what we’ve built with Sigma and our CDW. A modern, consolidated stack that puts finance and teams across the business back in control.

Want to see it in action?

Watch the full webinar to see how we rebuilt our entire financial reporting and planning stack, and why it changed the way we work.

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