SAS Intelligent Planning
Demand planning software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
Take the quiz to check if SAS Intelligent Planning and its alternatives fit your requirements.
Contact the product provider
Free Trial
Free version unavailable
Small
Medium
Large
- Public sector and nonprofit organizations
- Education and training
- Healthcare and life sciences
What is SAS Intelligent Planning
SAS Intelligent Planning is a demand planning application that supports forecasting and planning workflows for supply chain and commercial planning teams. It is used to generate demand forecasts, run what-if scenarios, and collaborate on plans across products, locations, and time horizons. The product emphasizes analytics-driven forecasting and integration with broader SAS data and AI capabilities for organizations that already use SAS for data management and modeling.
Advanced forecasting analytics
The product leverages SAS’s statistical and machine learning capabilities to support multiple forecasting approaches and model selection. This can be useful for organizations with complex demand patterns, large product catalogs, or frequent promotions. It also supports scenario analysis to compare forecast assumptions and outcomes. Teams that already standardize on SAS analytics can reuse skills and assets.
Enterprise data integration options
SAS products commonly integrate with enterprise data sources and data management tooling, which helps when demand planning depends on many internal and external signals. This can reduce manual data preparation and improve repeatability of forecasting runs. Integration is typically relevant for organizations with established data governance and centralized IT. It also supports embedding planning into broader analytics and reporting workflows.
Workflow and collaboration support
The application supports structured planning processes, including review cycles and exception-based work where planners focus on items that need attention. This helps operationalize forecasting beyond ad hoc spreadsheet processes. It can support cross-functional inputs (for example, sales, marketing, and supply chain) within a governed workflow. These capabilities align with enterprise planning operating models.
Implementation can be complex
Deployments often require configuration, data modeling, and integration work to align with an organization’s planning hierarchy and business rules. This can increase time-to-value compared with lighter-weight planning tools. Many customers rely on specialized SAS skills or partners for implementation and ongoing changes. Complexity tends to rise with multi-region, multi-channel planning requirements.
SAS-centric skill requirements
Organizations may need SAS platform expertise (administration, modeling, and governance) to fully utilize the analytics and integration capabilities. This can limit self-service changes by business users compared with tools designed primarily for planner-led configuration. Training and change management may be required for teams moving from spreadsheets or simpler planning systems. Licensing and environment management can also be more involved in SAS-standardized stacks.
UI and planning UX variability
User experience and configurability can depend on how the solution is deployed and customized within the SAS ecosystem. Some organizations may find planner-facing workflows less streamlined than products built with a narrower focus on retail or supply chain planning personas. Reporting and dashboards may require additional configuration to match stakeholder needs. This can increase reliance on IT or analytics teams for ongoing UX improvements.
Seller details
SAS Institute Inc.
Cary, North Carolina, USA
1976
Private
https://www.sas.com/
https://x.com/SASsoftware
https://www.linkedin.com/company/sas/
