Industrial manufacturers with large product mixes and many slower moving products usually face demand that is variable and hard to predict. Other challenges to providing high customer service levels include dealing with geographically distributed production facilities, complex distribution networks, and difficult allocation logic.

Our customers achieve stable and very high customer service levels, usually with about 20% less global inventory. Demand modelling incorporates internal and external elements such as market trends, returns and substitutions. These demand models have an exceptional ability to handle the intermittent demand of slow moving inventory. Machine learning reliably models even extremely seasonal demand profiles and new product forecasting.

Demand collaboration brings together demand and forecast data from multiple sources such as salespeople and distributors in a web-based consensus forecasting platform. Rough cut capacity planning covers the entire replenishment planning process, and includes fair allocation logic. S&OP bridges a critical modelling gap to reliably connect tactical planning to operational execution.

In fulfillment planning, semi-finished inventory can be optimised by propagating the service level requirements across the entire Bill-of-Material (BOM) structure. Inventory logic for customer order-driven semi-finished goods can be decoupled from production stock logic, separated by an order penetration point which balances response time and inventory costs.

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