JIT and Distribution Logistics

One reason for Japan’s high manufacturing productivity is the cost reductions it achieves through its just-in-time (JIT) inventory method. In this system, the supplier delivers the components and parts to the production line “just in time” to be assembled. Other names for this or very similar methods are zero inventory and stockless production.

The JIT method was successfully used after World War II by the Toyota automobile company. In the United States General Motors Ford, Chrysler, and American Motors use more advanced versions of JIT. But other companies also have used JIT with favorable results. Consider Black & Decker which produces, among other things, small appliances such as coffee makers and irons: When its plant in North Carolina switched to JIT inventory was reduced by 40% and 30% fewer forklift trucks were required. Moreover, quality losses were reduced 60% and labor productivity increased by 15%.

For the JIT method to work, a number of requirements must be fulfilled: (1) The quality of the parts must be very high; a defective part could hold up the assembly line (2) There must be dependable relationships and smooth cooperation with suppliers. (3) Ideally, the suppliers should be located near the company, with dependable transportation available.

An exciting and profit promising way of using system logistics in planning and control is the expansion of inventory control to include other factors this system is referred to here as distribution logistics. In its advanced form, it treats the entire logistics of a business from sales forecasting through purchasing and processing material and inventorying to shipping finished goods as a single system.

The goal is usually to optimize the total costs of the system in operation, while furnishing a desired level of customer service and meeting certain constraints, such as financially limited inventory levels. This gathers into one system a large mass of relationships and information in order to optimize the whole. It is entirely possible that transportation manufacturing, or any other single area of cost will not be optimized but the total cost of material management will be.

This model would be expressed mathematically as an operating system. The figure shows the relationships between the goal desired, the input variables and limits, and the expected outputs. By optimizing total costs in a broad area of operation, the system might show that it would be cheaper to use more expensive transportation on occasion rather than to carry high inventories. Or it might show that production at less-than-economic order quantities would be justified in order to get better transportation or warehousing utilization or to meet customer service standards with limited inventories.