It’s no news that inventory in wholesale distribution is a daily roller coaster. Sometimes you’re up and doing great, other times you’re down and your inventory is completely chaotic. There are several inventory management tools out there created solely to help with such struggles but there are also small steps that can be taken by distributors in order to reduce and better understand their inventory.
Recently, I came across a blog entitled, “Three Simple Analyses to Identify Risky Inventory in your Supply Chain.” (the article can be found here). The blog, written by Arkieva, highlights three different analyses you can use when trying to identify inventory. Each section discusses a different aspect and a different way of looking at your inventory. The three analyses are: Match ABC classification on your demand items to your inventory positions, do an analysis of order count and do an analysis of customer count.
Match ABC classification on your demand items to your inventory positions:
In this first analysis the blog suggests a wholesaler do a traditional “Pareto or ABC analysis on your item demand over the last 12 months.” This analysis will help you see how your demand stacks up against your inventory. Like most other companies an odd pattern will reveal itself. Usually, the demand and inventory will not match-up, in fact, the highest demand usually has the lowest inventory and the lowest demand will take up the most inventory. This is something useful to know so that the problem can be adjusted. Below is a table courtesy of the blog to help make this point more clear.
Do an analysis of order count:
There are two likely scenarios when dealing with inventory. There are items that get sold every single day, or at least at a very high frequency. Because of this, a wholesaler might be able to keep a mental note of this item. The risk comes into play when a professional sees the trend of this item being sold every day, which they then begin to overstock simply so they never run out, this can cause a problem if one day that item becomes obsolete, now there’s all this excess or even dead inventory sitting on the shelf. It’s better to keep a running analysis so this does not become a problem.
What about those items that while equal in volume, have a lower order count because they are sold less frequently, perhaps once or twice a month or once every other month. If you do not run this analysis there will be a lot of excess inventory if for some reason that order discontinues. Maintain a strong analysis of order count and this problem can be avoided as well.
Do an analysis of customer count:
I think the blog explains this analysis very well.
“This one is similar to the one above and yet it is different in that it does not need to be looked on a per period basis. If many customers buy an item, then I suppose you will see lots of orders and the law of averages will take over. So the risk involved with the inventory is low and similar to the risk involved with the case above with a lot of orders.
However, if only one or two customers are buying a product, then you run a bigger risk. What if those customers start buying from another seller? What if they want to cut a hard bargain for themselves and negotiate a very low price? What if they simply go out of business? In all these cases, you might be stuck with the inventory for a long time.”
These are just 3 important analyses when maintaining a successful inventory. Do you have your own favorite analysis for risky inventory? I would enjoy your feedback and your views on keeping a more efficient inventory. Please, leave your comments below.