Supply & Demand Planning
Achieve profitability while meeting omnichannel customer demand, without over- or under-stocking.
How SAS Delivers Supply & Demand Planning
SAS provides a highly automated, fully integrated supply and demand planning solution that breaks down traditional barriers between planning steps, transforming planning into a continuous, flexible process.
Small-, medium- or large-scale forecasting
- Automatically generate statistically driven, weighted consensus forecasts.
- Monitor forecast performance to understand value added or lost at each step.
- Use time-series forecasting to build models that reflect your business realities.
Demand sensing & shaping
- Visually analyze demand data to spot patterns and insights related to sales, shipments, pricing, promotions, etc.
- Evaluate sales history and plan for future events – new products, locations, channel introduction – using what-if scenario analysis.
- Measure the effect of sales and marketing strategies on consumer demand using multitiered causal analysis.
- Gain near-real-time insight into supply and demand dynamics so you can avoid under- or over-stocking.
- Calculate optimal inventory policies using multiechelon optimization with state-of-the-art simulation.
- Use predictive modeling and what-if analysis to find out how different variables will affect the supply/demand balance.
How does a large denim wholesaler and retailer predict and plan for demand?
SAS helped the wholesaler/retailer:
- Boost sales and gross margins.
- Improve SKU mix and increase shipments to key accounts.
- Cluster trade areas based on profitable products.
- Create a better customer experience by supporting localized omnichannel demand.
- Increase revenue, boost profitability and improve the customer experience.
How does a US clothing company with the largest intimates assortment maximize inventory to meet demand, while minimizing risk?
SAS helped the clothing company:
- Generate more accurate demand forecasts.
- Shape demand to drive customer behavior.
- Automate the financial forecasting process.
- Produce accurate demand plans for new fashion items.
How does a multinational retailer that operates hypermarkets, discount department stores and grocery stores fulfill e-commerce orders to reduce shipping costs and offer in-store pickup?
SAS helped the multinational corporation:
- Establish a multichannel presence that combines online shopping ease with the advantages of a physical store presence.
- Focus on better customer service, offering a variety of pickup and delivery options.
- Use innovative machine learning, forecasting and analytics technologies to better serve customers.
- Work in an open platform while supporting scalability of the world’s largest global retail enterprise.