[3537]

Slow-moving inventory. How to control, prevent and push sales automatically

Date:
October, 2011
Prototype:
proto$ gen VI mod 3FFECA (Londinium)
Customer:
Just.ru
An unpleasant discovery each CEO or owner will inevitably face when analyzing the stock is that some goods have become a tough sell. Wasted money: how dia$par helps to keep losses within boundaries.

In most cases, the biggest (if not the only) asset of a trading company is its stock.
It’s characteristic that the biggest problems in bookkeeping are associated with the same thing.
We are not talking about trivial theft or usual warehouse troubles like shortage of or mixed up goods. Teething problems are treated with a system of regular physical stocktaking, which is rather labor-intensive in reality, but very straightforward in essence.
Anyway, fundamentally, there are no problems with quantitative stock recording.
The same cannot be said about cost accounting, especially if we are dealing with merchandise with relatively quickly changing prices or demand.

Indeed, if the current market price of an item is, say 1 dollar, then how up-to-date is the price of 2 dollars at which it was bought and capitalized? Or, the market conditions have changed (e.g. the season for Christmas trees is over) and this product is no longer in demand even for free?
It’s clear that the balance-sheet value of such item has very little to do with the price, which can be theoretically paid for it. As a result, we have a situation, which is twice unfortunate:
a) the company’s balance sheet statement contains corrupt data (assets that actually don’t exist), while the profit and loss statement is more optimistic than the reality is (the expenses not showing losses from market depreciation);
b) the warehouse is being stocked with new slow sellers — goods that have no chance of being sold due to unrealistic and nonmarketable prices (the selling price was set on the basis of the purchasing price of 2$). A proportionate part of the expensive working capital is being blocked, as well as warehouse space.

Now, let’s presume that the range of products consists of thousands of completely different goods, which is a real-life situation, indeed. Then without a proper control the problem gets really big.

In fact, from our experience with various retail trading companies, the average value of "slow sellers in stock is about 20-30%, and it’s not the worst case scenario. The numbers for trading formats that are now extinct, such as hordes of "kiosks", are usually a lot higher.

Proper control. In simplified form it looks quite straightforward: the assortment is divided in lines, relevant subdivisions are run by managers. Their incentive scheme is based on the line KPI, e.g. gross profit and turnover rate. In case the company’s structure is distributed geographically, the responsibility hierarchy is replicated down to local levels.
The turnover component (or the like) in the incentive scheme of the people in charge encourages them to keep the warehouse contents and their prices updated and not allow any slow sellers, etc.

Life is usually more complicated than schemes. The responsible product managers, even highly qualified and motivated, are still people, and the human element here is also a major unconstructive factor.
One thing is buying, selling, and dealing in big money to the persisting ringing of phones, and another is spending long hours sorting out what’s left of it, cutting prices, coming up with special offers for "unmarketables", and doing other uninspiring and unambitious things.
Which, by the way, neither yield direct profits nor increase their salary. Actually, the other way around.

Fortunately, dia$par easily copes with these uninspiring and unambitious things that are however vital for business.

Regional Auto-Markdown Setup

First, we define the slow sellers: e.g. the number of days that the product has spent in the warehouse without a single sale. AND/OR life expectancy of current stock is over X days. AND/OR the number of views of the product’s webpage is less than Y per week. The set of criteria can be however complicated, and it has to be adopted each time for a particular business (and a particular product category all the way down to a single product, if  required).

Next, the anti-slowselling robot may work in both prevention mode (generating reports on slow sellers dynamics, escalating the problem when predetermined safety goals are met, prioritizing slow sellers when generating sales catalogs, additional bonuses in loyalty programs?) and active mode.
In active mode, using predetermined business rules, it routinely performs markdowns on the slow sellers. Until they start selling at a reduced price, which allows eliminating one product after another (on formal grounds) from this hardly reputable category.

This is how the dia$par won’t allow growing an initially small problem into a major one, one that may in some cases be a serious threat to profitability of the business as a whole.

A sophisticated reader might ask, whether it’s worthwhile describing what in fact is a fairly simple functionality?
Our answer is "Yes".
From the program point of view, the functionality is indeed, the simplest. But we believe that one of our key differences from the host of ERP creators and implementators is the fact that we look at life and customers" needs from the business point of view, and not from the program writing one.

Mature and highly competitive markets are characteristic of low margins and high turnover of its players. With this background, optimization of merchandise that leads to a substantial decrease of "unmarketables’slow sellers lead to a multiple increase in profits.

Even if such a result is achieved with a relatively little effort, its absolute value does not become any lower.

Being inside dia$par. Some stories
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