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Webinar: Supply Planning beyond legacy tools
In this webinar, Flowlity shows Supply Chain leaders how to move Supply Planning beyond Excel and legacy ERP modules toward probabilistic, AI-driven decisions.
Legacy tools were built for stability, not volatility. This session covers how innovative Supply Planning lifts material availability while shrinking stock.
What this webinar covers
- Where Excel and legacy tools cap performance
- The principles of probabilistic, exception-based planning
- How to modernize without a heavy IT project
For the practical follow-through on stock levels, our article on predictive analytics in Supply Chain shows how to resize buffers once planning turns probabilistic.
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FAQ
Find everything you need to know right here.
What is the difference between the Flowlity approach and the DDMRP methodology?
Flowlity and DDMRP (Demand Driven MRP) share a common goal:
to better position buffer stocks to absorb uncertainties and avoid the bullwhip effect in the supply chain.
However, their methodological approaches differ significantly.
DDMRP is a methodology with prescribed components. Flowlity is an AI-native planning platform that runs probabilistic demand forecasting per SKU and sizes dynamic safety buffers from the actual distribution. The two are not mutually exclusive. Flowlity can sit on top of a DDMRP-shaped network and replace the heuristic factors with measured ones. Industrial customers like Magotteaux cut inventory by 13% by adding a probabilistic layer to their existing planning systems, without a full DDMRP transformation.
What is inventory optimization? Why is it important?
Inventory optimization consists of determining and maintaining the right stock levels to meet customer demand while minimizing tied-up working capital and storage costs. It is important because excess inventory wastes resources, while insufficient stock leads to stockouts and lost sales. Effective optimization balances service levels with cost efficiency across the entire product portfolio.
Modern inventory optimization software moves beyond static reorder points and spreadsheet rules by combining probabilistic forecasting, dynamic safety stocks, and multi-echelon logic. It continuously adapts inventory policies to real demand signals, lead-time variability, and service objectives — turning inventory management from a reactive exercise into a strategic lever for margin and cash flow.
