Man unloading truck

Connect your upstream and downstream supply chain for optimal, efficient logistics

Supply Chain Analytics From SAS

Discover end-to-end supply chain scenario planning that spans organizational silos to optimize production plans, supplier collaboration and freight logistics – all based on our leading forecasting solution.

Cloud native forecasting for companies of any size

  • Automatically generate statistically driven, weighted consensus forecasts.
  • Monitor forecast performance to understand value added or lost at each step.
  • Use out-of-the-box modeling strategies with predefined models.

Balance inventory supply with demand

  • Manage production and logistics to match changing customer needs and market dynamics.
  • Enable better insights and collaboration across trading partners with our flexible open analytics.
  • Use predictive modeling and what-if analysis to simulate potential supply chain disruptions.

Integrated transportation management

  • Align transportation capacity to the specific needs of your demand plan.
  • Optimize on-time/in-full delivery performance to improve customer service and reduce penalties.
  • Gain real-time visibility to standing and in-motion inventories, reducing raw material and finished goods needs.

Get to know supply chain analytics from SAS

Discover how supply chain analytics connects your entire logistics chain to allow agile management of your critical resources.

Why choose SAS for supply chain analytics?

Sense market signals that shape – and help you predict – demand. Unify data from across your organization and beyond. Then optimize responses throughout the supply chain.

Connect customer & supply chain intelligence

Seamlessly bring together market and consumer drivers, such as syndicated scanner data and social media sentiment, with machine learning models to connect shopper engagement to product demand.

Avoid under- or over-stocking inventory

Get near-real-time insight into supply and demand dynamics. Calculate optimal inventory before the fact using what-if event simulation.

Achieve better planning outcomes

Use time-series and machine learning forecasting that considers intermittent demand, new product launches and dropped items. Let the solution choose the best algorithms or build your own with SAS or open source models.

Customer Success

Working smarter with SAS

SAS helped a multinational appliance manufacturer increase profitability and optimize its supply chain by:

  • Replacing manual spreadsheet forecasts with an automated solution that helped reduce inventory by more than 12% and boost revenue by 1%.
  • Optimizing inventory throughout its North American factories, keeping product availability above 93%, versus 63% the previous year.
  • Achieving higher service levels and lower levels of working capital.

Recommended resources for supply chain analytics


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