Inventory Optimisation

​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.

• Maximise Return-on-Assets (ROA)
• Cost-effectively manage and reduce risk
• Balance inventories with service levels and demand, holistically
• Find the optimal replenishment quantity and service stock parameters that minimise total annual costs
• Determine the optimal service level and stocking policy for each SKU by location
• Incorporate comprehensive error
• Provide Multi-echelon Optimisation (MEO) setting the BOM level for stocking & postponement strategy

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