Explainable, faster forecasts for FP&A with Alteryx One
A governed way for FP&A teams to validate actuals and connect every forecast to the driver behind it
A governed way for FP&A teams to validate actuals and connect every forecast to the driver behind it
FP&A work runs across ERP actuals, planning systems, the spreadsheets that connect them when the systems don’t talk, and now an AI agent pulled in to help close the gap. Alteryx keeps the data connected through all of it, so assumptions don’t drift between model, memo, or agent.
FP&A work runs across many connected workflows, not a single model.
A forecast is only as good as its ability to survive scrutiny — and that bar doesn’t move just because an AI agent built the first draft of it.
Finance at Siemens Energy compressed scenario work from weeks to hours, helping a single site increase output 102% and cut scrap costs by $4.4 million with Alteryx.
Alteryx sits alongside the ERP and planning system your team already runs, handling the actuals validation and driver-level detail neither one covers on its own. That includes any AI agent working inside the same stack — it doesn’t get an exception to those boundaries.
With Alteryx One, FP&A teams catch variances before they become surprises, defend the numbers on the first pass, and cover new business units without adding headcount.
Forecasts refresh as new signals arrive, instead of waiting for the next scheduled cycle. A demand shift shows up in the plan before it becomes a surprise in the actuals.
SaskTel replaced a year-long inventory forecasting process with one that runs in three minutes, saving more than $250,000 with Alteryx.
A scenario one planner built to test a single assumption becomes a model the team can rerun. Nobody starts over when the question changes or the planner moves to a different role.
Every forecast draws from one governed source, so the numbers match on first review. The team spends less time defending inputs and more time on what the plan means for the business.
A finance team consolidating data across more than 100 source systems cut analysis that once took days down to seconds with Alteryx.
Finance sets the materiality thresholds, and an agent works through variances that cross them. It flags what’s affected and leaves each result traceable back to the logic that produced it.
Validated forecasts and variance analysis move straight into the plans, board packs, and dashboards that depend on them. Every downstream report draws from the same source data, every cycle, without rebuilding.
Each new business unit or planning cycle inherits the same governed structure already built. Coverage grows without a rebuild, even as the portfolio of active forecasts keeps expanding.
Built for FP&A leaders, analysts, and planners across the finance organization.
Alteryx One führt Analysen im Unternehmensmaßstab durch – mit der Compliance und den Prüfpfaden, die der Finanzbereich benötigt, sowie der Sicherheit und den Kontrollen, die die IT erfordert.
The forecast holds up under questioning before anyone has to defend it. A reviewer who didn’t build the workflow can still see which logic an AI-assisted number ran through. Every cycle produces the same answer from the same assumptions, whether the analyst has been here five years or five weeks.
Before it would have taken me a year to create this one report on 5-year forecasts and now we can run 3,300 active material numbers in less than 3 minutes.… I don't think I could even do this role without Alteryx.
The standard for trustworthy AI in finance is VURA: visible, understandable, repeatable, auditable. Each finance function meets it in its own work.
Visible means anyone can see how an output was produced. Understandable means a reviewer who did not build the logic can still follow it. Repeatable gets the same answer from the same inputs, every cycle. Auditable puts the evidence in place before anyone asks.
FP&A teams can see this pattern applied directly in these AI-Ready Starter Kits — pre-built workflows that skip the blank canvas and get a team started faster:
Because AI doesn’t know your planning rules. It can summarize a variance or draft a narrative, but it can’t tell you which driver actually caused it, what counts as material for your business, or how your team defines a completed forecast cycle. Alteryx is the business logic layer where FP&A builds and owns those rules, and it hands AI numbers that have already been validated against them, so it works from something dependable instead of guessing.
Anaplan, OneStream, and Workday Adaptive are where your plan runs, but none of them validate the actuals feeding into it or resolve a driver assumption against what a business unit reported. Alteryx handles that layer first, then feeds clean, validated figures into whichever planning system your team already uses, so the model keeps doing the modeling on inputs it can trust.
No. Workflows are built visually, and with Ask Alteryx you can describe what you want in plain language and get a starting workflow back. Either way the result is a workflow: every step is visible, reviewable, and changeable by the analyst who owns it. That matters more than how it was created, because the workflow is what a reviewer follows and what the next planner inherits when the model changes hands.
The goal is to move the logic off the spreadsheet and into something that scales, while keeping everything the spreadsheet got right. A mature forecast spreadsheet holds years of judgment about which drivers matter and how they interact. Rebuilding it as an Alteryx workflow keeps that same logic, but running on schedule, holding up when a reviewer asks how a number was reached, and independent of whoever happens to be the one analyst who built it.
Yes. With Alteryx, every number traces back to a workflow that shows which data it used, which rule it applied, and who approved it. Your team sets the driver logic, so a reviewer sees a documented assumption behind the number. The evidence exists before anyone asks, because the decision path stays visible as part of how the workflow runs.