How SAS® Delivers 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.
How did the largest direct seller in China improve replenishment time by 20% and achieve 97% customer satisfaction?
SAS helped Amway China:
- Develop an advanced inventory optimization system that effectively estimates and models optimum inventory levels based on service levels, delivery times and costs set up by the user.
- Predict demand by automatically analyzing, modeling, executing and adjusting predictions for products and regions at different levels.
- Calculate the replenishment frequency of different regions based on predicted customer demand.
- 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.
How does the world's largest food company optimize customer service, minimize inventory overstocks and lay the groundwork for effective marketing?
SAS helped Nestlé:
- Establish reliable forecast methods that free up time to focus on demand planning for highly volatile products.
- Make more successful production decisions to ensure products are available when customers want them.
- Take proactive measures instead of simply reacting to better manage supply chain, plan operations and organize logistics on a global scale based on a variety of influences and factors.
How does a multinational appliance manufacturer improve its forecasts by 10%, resulting in less excess inventory and less inventory ending up in the wrong places?
SAS helped the multinational appliance manufacturer:
- Replace tedious, manual spreadsheet forecasts with a reliable, automated solution that helped reduce inventory by more than 12% and boost revenue by 1%.
- Optimize inventory throughout its North American factories to get the right product to the right place at the right time, keeping product availability above 93%, versus 63% the previous year.
- Achieve higher service levels and lower levels of working capital.