What does ‘Make To Order – MTO’ mean
Make to order (MTO) is a business production strategy that typically allows consumers to purchase products that are customized to their specifications. The make to order (MTO) strategy only manufactures the end product once the customer places the order, creating additional wait time for the consumer to receive the product but allowing for more flexible customization compared to purchasing directly from retailers’ shelves.
BREAKING DOWN ‘Make To Order – MTO’
The make to order (MTO) strategy relieves the problems of excessive inventory that is common with the traditional make to stock (MTS) strategy.
Dell Computers is an example of a business that uses the MTO production strategy wherein customers can order a fully customized computer online and receive it in a couple of weeks.
Traditional production methodologies produce products and stock them as inventory until a customer buys them. This is known as make to stock or MTS. However, this system was prone to wastage and obsolescence. In order to manage inventory levels and provide an increased level of customization, some companies adopted the make to order production system.
Known as Made to Order or Build To Order
Make to order, also referred to as build to order (BTO) or made to order (MTO), is a manufacturing process in which the production of an item begins only after a confirmed customer order is received. This type of manufacturing strategy is referred to as a pull-type supply chain operation because products are only made when there is a firm customer demand. This pull-type production model is employed by the assembly industry where the quantity needed to be produced per product specification is one or only a few. This includes specialized industries such as construction, aircraft and vessel production, bridges, and so on. MTO is also appropriate for highly configured products such as computer servers, automobiles, bicycles or products that are very expensive to keep inventory.
A demand-driven method for scheduling optimal smooth production levels
This paper is concerned with demand-driven production scheduling in a commercial environment where smoothed production plans generation over a rolling horizon is desirable as new observations of demand are received through time. Demands are assumed to be normally distributed and dependent on the previous observed levels. The method of chance constraint of Charnes and Cooper is extended to multi-product production planning with variable workforce, back-ordered inventory, and nonstationary stochastic demand process. Bayesian procedures for revising the chance constraints and several variants of linear-programming-based production planning models are presented. In all cases the proposed methodology ensures that demands are satisfied, at a given level of confidence, while achieving smooth production.