Shelving/Slotting of Goods

What is slotting? Slotting is the activity of determining the most suitable storage location for each item in your stockroom.

Each item in your stockroom has its own unique combination of characteristics. One of the most important characteristics is the frequency of physical touches for each specific item. By ‘physical touches’, I’m referring to each time someone has to go to the location the item is stored to do something (pick an item for an order, put away a receipt, etc.). As physical touch activities go, the one that gets the most attention is order picking. So not surprisingly, most slotting is focused on improving the efficiency of order picking.

Plan and Implement Effective Slotting of Items

A typical slotting project will start by ranking all items in the stockroom based on the frequency that items are selected. This is easy to do and simply involves creating a report or query(s) based on either your sales order detail file, a transaction history file, or a movement history file. You will run this against a full year’s transactions, and count all sales transactions for each item, then sort the report/query by the total sales transactions, in descending order. So, the first item on the report is your fastest-moving item, the second is the second-fastest moving, and so on. Now, remember, we are talking about the total number of times an item is picked, not the total quantity. If we did the latter, then an item that was picked a thousand times last year with a pick quantity of one unit at a time would be ranked the same as an item that was picked once with a pick quantity of a thousand. Obviously, from an order-picking efficiency perspective, we want that item that was picked a thousand times in a more accessible slot than the one that was picked once, even if both represent the same unit sales.

Now that we have our times-picked ranking that shows what our fast movers are, we need to determine where we want our fast movers to go. So now we need to look at the characteristics of our locations. Primarily, we want to look at the distance an order-picker would need to travel to get to the location, and how accessible the location will be once the picker gets there. A location that needs a ladder or lifts truck for access is not as easily accessible as one that is directly accessed from floor level. And, even within those locations that can be accessed from floor level, those that do not require a worker to bend over or reach up are more easily accessible than those that do. As to the distance, an order-picker would need to travel, things get a little more complicated. That’s because we need to consider exactly how orders are picked in your operation. If a picker has a fixed starting point and moves to a location for a single pick, and then returns to that fixed location, we can simply rank the locations by the distance from the fixed starting point. This would often be the case in a full-pallet picking operation where a lift truck operator can only pick one pallet at a time before returning to the starting point (probably the shipping dock). But what if a picker follows a fixed picking path through several aisles before returning to the starting point? In this case, each location along that fixed picking path will be ranked the same as far as distance goes, because the picker is going to go past each location anyway. In many stockrooms, you have a combination of the previous examples, so you need to take all this into consideration when ranking your locations.

Now that we have our locations ranked and our items ranked, we can take our fastest-moving item and slot it in our best location, then take our second fastest moving item and put it in our second-best location, and so on.

In some operations, the above example is about all you really need to do. Well, that is, assuming that your items are all similar in size, your locations are all similar, and your quantity per pick is all similar, and there are no relationships between products, and… As you can see, there are a few more things that need to be considered.

First, when you have items with varying sizes, you will also likely have locations (slots) of varying sizes. Therefore, you obviously need to make sure the items are going into slots that are appropriately sized. But, an item’s size, combined with the quantity picked, also needs to consider. In both these cases, the size of the slot is determined by the size of the item and how many items need storage. Slot size is important when looking at order-picking efficiency because larger slots need your order-pickers to travel further when moving past these slots to get to other slots. Therefore, what we really need to look at here is how many picks we can get out of a specific size pick face. For example, if I have a somewhat-bulky item that gets 500 picks per year, and requires a pick face of 1,2m2, but also have five smaller items that each get only 200 picks per year, all five items together will fit in the same pick face size as the bulky item, you are better off giving the five slower-moving items a better slot than the bulky faster-moving item. That is because the objective with slotting is to get the most picks with the least amount of travelling.

Another consideration is how many (quantity) should you expect a slot to hold? Larger slots will stretch out your pick paths and therefore result in less-efficient order picking. But, smaller slots need more-frequent replenishment. You can apply costs to these activities and calculate the point that financially makes the most sense, but this can get complicated. Typically, you will calculate by product group and then put together some guidelines to apply to each product group.

Other slotting considerations would include, the weight of the items being stored, or other characteristics that may make some slots more appropriate. You want to keep your heaviest items lower, but this does not necessarily require going to floor locations. You really need to consider how you pick and stock these items. If, for example, you are picking and stocking these heavy items from a raised picking cart, the best slots for these items would be levelled close to the level of the cart. And then there are more obvious characteristics, such as hazardous items stored in areas specifically designed for hazardous items, or cold storage items slotted in cold storage.

We may also want to consider related items that are picked together in the same order. This needs some analysis but can be very beneficial in some operations. Obviously, you need to consider this within the context of how you pick orders (your pick paths) because the benefits of slotting these items together will vary, based on your pick paths.

By understanding the variables in your specific environment, you can use your knowledge of these variables to help you approximate their effect on groups of products and locations. If a variable does not make a significant difference in your specific operation, do not waste your time trying to incorporate it. If a variable is important but is way too complicated to calculate on an item-by-item basis, try to put together some guidelines that help to consider this variable. In addition, try not to get too overwhelmed by the complexity of all these calculations. While many of them have interdependencies that need to be considered, it is often easier to build up from a series of variable-specific calculations than to try to make one master-slotting calculation.

You do not have to have the perfect slotting plan. In fact, you do not even have to have to be close to perfection to achieve many of the benefits of slotting. Even a simple ranking of items, purely by times-picked and then slotting them without considering any other variables, will prove to be a significant improvement over no slotting logic. Anything you can do over and above this is a bonus.