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

How SAS® Delivers Supply Chain Analytics

End-to-end supply chain scenario planning spans organizational silos to optimize production plans, supplier collaboration and freight logistics – all based on the world's best 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.

Multiechelon inventory optimization

  • Manage production and logistics to match fluctuating customer needs and changing marketplace dynamics.
  • Calculate optimal inventory policies using multiechelon optimization with state-of-the-art simulation.
  • Use predictive modeling and what-if analysis to determine how different variables will affect the supply/demand balance.

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 multiechelon inventory policies 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.


Working Smarter With SAS®

  • Amway China

    Improving replenishment time by 20% and achieving 97% customer satisfaction

    SAS helped the largest direct seller in China create a more effective replenishment policy for reorder, order-up-to and required quantity levels that can pinpoint each product in each warehouse and store, adjusting dynamically to market changes over time.

  • Improving forecast accuracy by 10%, resulting in less excess inventory and less inventory ending up in the wrong places, by:

    SAS helped a multinational appliance manufacturer:

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

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