Traditional planning methodologies like MRP and APS (Advanced Planning & Scheduling) usually don’t address the specific requirements for business where you produce a large range of finished goods from a few raw materials – typical in industries like meat, dairy, timber and steel. The reason being is that they are designed for an assembly type of production where there are raw materials which are processed and assembled into a smaller number of finished products, which is completely the reverse.
Disaggregation has unique factors which need to be considered, such as the best way to substitute raw materials with alternatives, or how to deal with push constraints (i.e. supply that has to be used up)
In contrast, optimization methods like Linear Programming (LP), Mixed Integer Programming (MIP) and Constraint Programming (CP) can handle the unique requirements of disaggregation very effectively.
To deal with decision-making for substitution, instead of using a set bill of materials, optimization assesses the pricing of all existing raw material alternatives and finds the solution that minimizes the total supply cost to meet demand.
Optimization also allows you to consider push constraints – surplus is identified and recommendations are made on the best way to translate surplus into sales opportunities.
The end result is a plan where demand and supply is balanced and profit is maximized.