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Demand Planning
NEVER BE OUT OF STOCK
Empower your organization to sense, shape, and serve demand
ORS Demand Planning and Forecasting is a next-generation platform that leverages enterprise big data, AI and machine learning, and our unique Time Series Manager to help organizations sense, shape, and serve demand.
Leverage historic data and market trends to sense product/service demand
Predict where and when your product/service will be in demand
Intelligently influence your procurement and never be out of stock
ORS Demand Planning allows Demand Sensing and Demand Shaping in real time, across locations, and for multiple product categories that could be interrelated in the production supply chain. Our revolutionary Time Series Manager is critical to understanding the context of data to bring true insights into the meaning of data.
- Allow users to create new time series of data streams, as well as nodes and hierarchies in the data structures in real-time
- Perform graphical analyses of large data volumes—logarithmic and exponential scale
- Enable scenario generation and association between items and clusters, data nodes, and management features
ORS Demand Planning is a powerful analytics platform that enables data-driven decision making
Demand Sensing
Integrate historical data, time series manager, real-time market signals to improve forecast accuracy for inventory planning.
Demand Shaping
Employ price incentives, cost modifications and product push to help meet planned supply.
We cooperated with ORS in a supply chain project for a global company in the field of food and feed safety. ORS’ demand planning solution was the perfect match for the ambitious requirements of our client.
Chong-Ho Hwang, Senior Manager
Kerkhoff Consulting
Düsseldorf, Germany
ORS products fully integrate with your legacy systems while enabling you to drive impactful business transformation across your value chain.
Powering Demand Planning with Machine Learning and Artificial Intelligence
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Sense Demand. Shape Demand. Serve Demand.
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Demand Planning
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