From my observations, movement of material through a company’s supply chain is increasingly becoming a major portion of delivered costs. Depending on the industry, nearly 5% of sales dollars will be dedicated to warehousing and transportation. With margins under constant pressure, efficient logistics can be the difference between making and losing money on each sale.
Many companies outsource distribution in order to reduce these costs. The idea behind this is that a specialist that handles the distribution will achieve cost savings through economies of scale, and will pass along some of these savings. This can be true for some companies, but it may not be the best option for other companies that wish to integrate their logistics network with manufacturing and other functions to create a supply chain delivery system that is a competitive weapon.
A good example of this would be Martins, located in Brazil. Martins runs its own distribution network which serves more than 227 thousand active clients and processes more than 3 million orders per year. The total volume moved through the network is in excess of 289,000 tons. With that kind of volume, distribution costs are an issue. In general, optimization tools that address network design balance fixed costs of warehouses and distribution points against transport costs, lead times, and customer service levels.
There is one other complexity when dealing with Brazil. Each state within Brazil has its own tax system. Not only is it important to minimize direct costs, it is also crucial the tax implications of locating the warehouses and the movement of product through the warehouses be considered.
If you’re looking for an out of the box network design tool that can handle this level of complexity, you’ll have a hard time finding one. Typically, the tool is used to gain an approximation of the network (the tax implications are dialed in later). Martins felt savings could be achieved if the tax implications were considered within the optimization engine.
Arkieva has a powerful optimizer that is unique in that the model can be changed without software changes. As a result, Martins selected Arkieva to handle the network design optimization. Using Arkieva, Martins constructed a model that represented the movement of the 14,000 of its largest SKU’s.
Not only did the model show how logistics costs (transport + distribution + storage) could be reduced by 4.5%, it also showed how the imbalances between tax credits and debits could be reduced by 8.5%. These recommendations have been adopted and resulted in substantial savings.
Another example where network optimization and logistics plan can contribute to an effective supply chain can be found in agricultural products. There are often “content” requirements by country. Basically, a portion of production, or “value-add,” must be done within a country before it is allowed to be sold there. A flexible network design tool is essential in planning the movement of intermediates between production steps, and for locating the production steps in different regions.
A final example of when optimal network becomes important is in chemical re-processing. Products like sulfuric acid are shipped to customers, and then returned for reprocessing. In this case, an integrated model that considers both the distribution and the manufacturing resources becomes critical for optimizing overall costs.
While outsourcing the distribution of products is always an option, there are at least two sets of circumstances when a company ought to seriously consider using an optimization engine; one where there are unique opportunities (example tax savings in Brazil), and two where integration between distribution and manufacturing can generate savings.
This is just one perspective on this topic. For a more detailed outline of this topic, download our My Network Design Is Not Your Network Design whitepaper written by Arkieva CEO, Dr. Harpal Singh.