Inventory Control
There has been a lot of information going back and forth about item management, category management and inventory control. Actually, considering this is the biggest line on a retail financial statement, the amount of discussion is sadly lacking. What is the actual cost of inventory? What is your true cost of a promotion, write off of inventory? There are many questions but retailers sadly keep to the old metrics of inventory turns and margin. Unfortunately, these numbers are mostly after the fact. We are building bigger and bigger stores, yet most of the SKU we carry do not carry their weight of cost of capital. How do we justify the use of all this square footage? There are retailers that do an excellent job of maximizing sales per square. But how do you truly arrive at a top quartile, best practices assortment. Not through dealing with vendors. No matter what, their goal is opposed to yours. We talk about partnerships but if you realistically look at the business, they are making money off of you. So how do we tighten our supply chain and assortment?
There are new metrics being introduced to retail. After a long, long time, quantitative analysis and analytics are being used in retail. Wall Street has been using them for years but retail management has for the most part been relying on outdated analysis. Will your customer substitute? What is the cost of out of stocks? What is the cost of carrying additional inventory to make sure you are not out of stock?
As more retailers switch to enterprise based software and have access to OLAP item level transaction data, the choice is not having data to look at but how to look at such a multitude of data. The modern C store management team is increasingly heavy on analysts or quants that provide filters for management and marketing to allow them to make sense of the reams of data. All one has to do is look at one daily transaction file and your head begins to hurt. Even now as we attempt to distill this new data into KPI that make sense, we have to start lumping data together to try and make sense. Most of the material I deal with now is item level logarithms but rely on assumptions that lump items together based on some quality so we can make some type of relationship appear and make sense in execution. There is no doubt the average store carries way too much inventory. How do we justify carrying three cans of something that we may only sell once every several months but need to have some presentation or we will not sell any at all? What is the best use of cash? I struggle with stores that are getting larger and larger but yet really have no unique offering. Perhaps services are the new key to utilizing all this space. They have a low carrying cost, usually have some barrier to entry and do provide value added to the customer. And maybe most importantly, they provide the human factor to the shopping experience. Our next blog post will examine this in more detail. Future shock as the term was first coined years ago. Take care….