List of SAS Forecast Server Customers
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Since 2010, our global team of researchers has been studying SAS Forecast Server customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased SAS Forecast Server for Analytics and BI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using SAS Forecast Server for Analytics and BI include: Dow, a United States based Oil, Gas and Chemicals organisation with 36000 employees and revenues of $42.96 billion, Penske Corporation, a United States based Automotive organisation with 50000 employees and revenues of $26.00 billion, Carnival, a United States based Leisure and Hospitality organisation with 40000 employees and revenues of $3.00 billion and many others.
Contact us if you need a completed and verified list of companies using SAS Forecast Server, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Carnival | Leisure and Hospitality | 40000 | $3.0B | United States | SAS Institute | SAS Forecast Server | Analytics and BI | 2021 | n/a |
In 2021, Carnival implemented SAS Forecast Server to centralize forecasting for food and beverage and other onboard consumables. The deployment is positioned within the Analytics and BI domain and shifted forecasting practice from backward looking analysis to forward looking cost forecasting for onboard consumables and provisioning.
SAS Forecast Server was configured to support automated time series modeling, automated model selection, scheduled batch forecasting, and scenario based forecast runs, leveraging the product's model management and scoring capabilities. The implementation emphasized repeatable forecasting pipelines and a unified forecasting repository, with SAS Forecast Server used as the canonical forecasting engine across use cases.
Operational intake focused on onboard consumption and cost data feeds, with forecasts consumed by food and beverage operations and finance cost planning workflows. The scope covered forecasting for provisioning and onboard consumables, and the platform ingests operational usage and cost streams to produce roll forward forecasts used in planning cycles.
Governance established centralized forecast ownership, scheduled forecast cadences, and standard model validation controls to move the organization from ad hoc historical analysis to managed forward looking cost forecasting. Carnival reported improved scalability from the unified SAS Forecast Server implementation, enabling consistent forecasting processes across onboard operations and finance.
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Dow | Oil, Gas and Chemicals | 36000 | $43.0B | United States | SAS Institute | SAS Forecast Server | Analytics and BI | 2024 | n/a |
In 2024, Dow implemented SAS Forecast Server as an Analytics and BI application to support global demand planning. The initiative targeted improved forecast accuracy and reduced manual adjustments, and the solution was reported as deployed into production in early 2025 and used to inform monthly production plans.
The deployment leveraged SAS Analytical Forecasting capabilities within SAS Forecast Server to automate time series modeling, hierarchical forecasting, and batch scoring across product and location hierarchies. Configuration emphasized model governance, automated model selection, and scheduled forecast runs to produce monthly forecast baselines for planners.
Operational coverage focused on global demand planning and monthly production planning, embedding SAS Forecast Server outputs into supply chain and operations planning workflows. The production deployment in early 2025 moved statistical forecasting into core planning processes, supporting demand planners and production schedulers across Dow's global sites.
Governance changes formalized forecast ownership and reduced manual adjustments to statistical forecasts, aligning stakeholders around SAS Forecast Server outputs. Dow uses SAS Forecast Server within its Analytics and BI stack to drive ongoing demand planning and production planning activities.
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Penske Corporation | Automotive | 50000 | $26.0B | United States | SAS Institute | SAS Forecast Server | Analytics and BI | 2022 | n/a |
In 2022, Penske Corporation deployed SAS Forecast Server to establish a centralized forecasting capability for revenue and financial planning. The implementation leveraged SAS Forecasting Studio functionality to construct hierarchical time-series models that support month-to-month business planning and multi-year forecasts, and the work is classified under the Analytics and BI category.
The implementation emphasized hierarchical time-series modeling, model selection and validation workflows, and automated model runs to generate iterative forecast scenarios, using SAS Forecast Server as the execution and orchestration layer. Configuration centered on reusable model templates and forecast hierarchies that map to Penske revenue streams and financial planning dimensions, enabling standardized forecast production across finance teams.
Rollout was executed as a multi-year program that achieved marked success after about three years, with governance focused on model governance, version control, and scheduled retraining to maintain forecast consistency across planning cycles. Penske used the SAS Forecast Server deployment to improve the rigor of revenue and financial planning processes, enabling more accurate month-to-month planning and multi-year forecasting outcomes.
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