How SAS® Enables Supply Chain Optimization
SAS provides precise forecasting, demand sensing and demand shaping capabilities based on up-to-date, accurate data. The result? Inventory that’s balanced with demand in near-real time and supply plans aligned with demand forecasts.
- Generate accurate forecasts at every level. Even for individual SKUs.
- Use time-series forecasting to build models that reflect your business realities, taking into account intermittent demand, new product launches, pricing, promotions – even weather.
- Use sophisticated optimization algorithms to compare and adjust forecasts so you can choose the best strategy.
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.
Demand sensing & shaping
- Sense demand signals that indicate marketplace changes faster.
- Translate demand signals – like seasonality, price, promotions, events and merchandising – into a more effective, market-driven response.
- Take a visual approach to analyzing demand data to unearth patterns and insights regarding sales, shipments, pricing, promotions and operational, category or regional performance.
Why choose SAS for supply chain optimization software?
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.
Collaborate & share customer & supply chain intelligence
- Foster collaboration among sales, marketing, finance, operations and supply teams – as well as third-party stakeholders – in support of the Integrated Business Planning (IBP) process.
- An interactive dashboard lets you monitor, track and report on forecast performance, such as forecast value-added reports.
- A forecast planning workbench generates automated, statistically driven consensus forecasts.
Avoid under- or over-stocking inventory
- Get near-real-time insight into supply and demand dynamics.
- Calculate optimal inventory policies using multiechelon optimization, or validate policies before the fact using what-if discrete event simulation.
- Predictive modeling and what-if analysis reveal how different variables will affect the supply/demand balance so you can drive product where it's needed most, meeting customer demand while managing overall inventory costs.
Improve planning outcomes
- Generate unbiased consensus forecasts that work in conjunction with IBP processes.
- Use time series and machine learning forecasting to build models that consider intermittent demand, new product launches and retired products.
- Choose the best action based on forecasted demand using sophisticated optimization algorithms.
- Reduce obsolete inventory and waste, improving sustainability performance.
Optimizing the Supply Chain With SAS
A Multinational Appliance Manufacturer
SAS helped the company:
- 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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