Reduce the warehouse operating costs by 10%

It is almost a rule that every logistics manager or warehouse manager considers his warehouse and processes to be unique. To a certain degree of detail, this is true. However, the basic storage processes and the way of storing goods or moving them are very similar in most warehouses, regardless of the industry. In this sense, certain concepts and approaches to cost optimization will have universal value.

Let's look at the typical cost structure of the warehouse: 10% of the operating costs are the costs of the systems, 40% of the costs are of renting and managing the property, and 50% of these are labor costs. Following this trail, the most of it, as many as 60% of the warehousemen's working time, is related to the cost of moving around the warehouse. The simplified counting will tell us that as much as 30% of the operating costs of a warehouse is related to the movement of people. It is also the answer to the question of where the areas for optimization should be sought first.

The total distance covered each day by warehouse employees includes both the distance between the docks and the places where goods are deposited or collected, as well as, the routes covered inside the shelving zones. Time spent by warehousemen on the route between docks and storage racks is conditioned by the size and scheme of the warehouse, the number of tasks received and also, the type of equipment for transporting goods. However, the time spent inside the shelving zones is related to the picking path, the number of SKU lines, the size of orders, the density of the picking and the equipment used.

There are at least several ways to optimize your routes through the warehouse!

One of them, more and more popular, is the use of automation: relatively simple solutions for transporting goods (e.g.  conveyors), as well as complex solutions, working according to the logic "goods to man", and therefore all types of stackers, self-propelled platforms, automatic shelves etc.

Another way to optimize routes, available for advanced WMS systems, is to model the collection process in order to maximally compact the picking sites and also maximize the number of downloaded pieces of a given SKU. These can be achieved, for example, by batch picking and sorting in the next phase. This is particularly important when handling a large number of small orders, which is a typical situation in e-commerce and when executing orders from small business partners or branches.

A third option for accomplishing the ideal warehouse’s routes is to optimize the distribution of goods through the warehouse, the so-called slotting. This involves the application of many criteria and computational algorithms that suggest the optimal distribution of goods in the warehouse. Slotting algorithms consider not only "normal" ABC goods rotation criteria, but also some key attributes of goods, such as: their weight, fragility, shape (regular or not), flammability, value of goods, quantity of "touches" of goods, way of shipping / loading, or e.g. the order in which goods are distributed in stores. Potential criteria are a huge amount, therefore, the use of additional tools outside the algorithms available from the WMS level can bring quite tangible benefits.

The Canadian company Insight (starting this year, part of the Mantis Group) states that appropriately implemented slotting saves 30% of the time related to people moving around the warehouse, effectively reducing labor costs by up to 18% and operating costs of the entire warehouse, by an extra 10%.

Another considerable benefit of slotting is a better use of the storage potential. According to WERC data (Warehouse Education and Research Council), the differences in the use of storage space between the average managed warehouses and the best managed warehouses, are as follows:

Average warehouse:

• The peak use of storage capacity: 95-98%
• Level of filling of statistical storage location: 80-88%
• Storage location occupancy rate: 85-87%

"Best practice":

• The peak use of storage capacity: 100%
• Level of filling of the statistical storage location: 93%
• Storage location occupancy rate: 95%.