Sustaining target levels of inventory and service simultaneously across complex multi-echelon bills-of-materials and distribution networks is tough. That’s why Inventory Optimisation with GAINS uses sophisticated, automated, proprietary algorithms that consider a comprehensive set of cost and source variabilities, including service-level goals, demand plan error and lead-time for every SKU by location across the enterprise.
Maximising Multi-Echelon Supply Chain Performance
By managing variability and uncertain demand, our customers improve service levels and reduce expediting while reducing inventory investment, minimising operating costs and maximising profit.
The GAINS Inventory Optimisation proprietary algorithms include:
- Inventory Policy Optimisation algorithms to precisely achieve targeted service levels by comprehensively managing sources of planning error. These include: demand plan/forecast error, lead-time variation, supply yield, and optimal ordering cycles
- Service Level Optimisation algorithms that automatically determine service levels uniquely for each item to achieve an aggregate target while minimising or maximising a business objective, (e.g. minimised total cost, minimum inventory, specific inventory turns target, maximum profit, etc.)
- Sourcing Optimisation algorithms that determine the supplier(s) that provide the lowest-total-cost supply, including solving for the trade-off of unit cost, purchase minimums, and lead time
- Network Flow Optimisation algorithms that determine which supply route provides the lowest-total-cost supply, considering lead times, minimums (line-item and PO-level), handling, and transportation costs
- Multi-echelon/ Stocking Policy Inventory Optimisation algorithms that determine whether or not to stock an item and at what service level. These solve for interdependencies among locations and/or within the bill-of-materiel (BOM) to devise postponement strategies and address customer expectations to minimise cost or maximise profit