Improve service levels and cut inventory costs with precise demand plans. Alteryx combines internal data and market signals to boost forecast accuracy, transparency, and scenario planning — helping teams align faster and adapt easily to shifting demand.
AI-driven forecasting can reduce errors by 20–50% (McKinsey, 2024). However, organizations may find themselves mired in spreadsheets or rigid demand planning software that’s difficult to configure and slow to adapt. Business users struggle to adjust assumptions without IT or data science support, leaving forecasts rigid and hard to explain. Fragmented data obscures drivers behind shifts, while limited scenario analysis slows S&OP. The result is higher inventory, missed revenue, and longer cycles reconciling numbers instead of building consensus.
Planners face fragile spreadsheets or rigid systems, forcing reliance on specialists instead of adjusting forecasts themselves.
Teams struggle to unify ERP, CRM, POS, and external inputs, reducing trust in forecast drivers.
Planners spend excessive time on repetitive data prep and reporting, delaying forecast cycles and decisions.
Without contextual, governed inputs, planners receive opaque forecasts that drift and fail to inform decisions.
Disconnected teams debate numbers instead of building consensus, delaying S&OP cycles and decisions.
Alteryx One blends ERP, CRM, POS, and external data into a unified, trusted demand view. Forecasting models can be created and compared without technical barriers, while scenario testing highlights upside and downside risks for faster conversations. Workflow automation keeps forecasts refreshed and approvals auditable. Outcomes include quicker alignment, greater transparency, and resilient plans that adapt to promotions, volatility, and market disruptions without relying on hard-to-change software.
Integrated data access
Unify ERP, CRM, POS, external drivers
Automated workflows
Refresh forecasts, retrain models, test scenarios
Advanced analytics & AI
Blend demand sensing, compare forecasts, explain drivers
Governance
Embed lineage, approvals, explainability into every forecast
Fewer stockouts and reduced excess inventory costs
Shorter planning cycles with faster consensus decisions
Lower working capital tied up in inventory buffers
Scalable forecasting process that adapts to promotions and volatility
$250K
saved by building reports in house
“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. The time savings that we’ve experienced with just this one report is astronomical.”
Byron Waugh, Demand Planning and Forecasting Manager
SaskTel
100+
workflows deployed
“Prior to Alteryx, decisions were made based on gut feeling. This way, we are able to get closer to a more scientific way to do it.”
Meghan Gohil, Automation and Data Visualization Manager
Fender
$500K
saved through inventory optimization
“Our model in Alteryx is constantly making predictions based on thousands of variables — from product data to raw material supplies. The data we get is accurate and powerful when combined with our procurement and manufacturing teams’ knowledge.”
Jeff Gordon, Director of Procurement, Warehousing, and Analytics
Armor Express
Blend historical, forward-looking, and downstream data with predictive models to generate accurate forecasts — reducing errors and improving planning confidence across products and regions.
Increase forecast frequency and compare multiple versions to reach consensus, then publish approved outputs directly into BI platforms, LLM applications, or ERP systems for execution.
Capture external signals such as customer sentiment, market data, or social activity to sense shifts early — moving beyond rule-based methods to adapt quickly in consumer markets.
Test and validate promotions, pricing, or product launches with A/B methods and sentiment analysis, shaping demand strategies that boost profitability while reducing overstock and stockouts.
Ensure forecasts are built on contextual, auditable, AI-ready data with embedded logic and lineage, reducing drift, hallucinations, and ensuring results remain explainable and trusted.
