Developing an Approved Stock List

Last month's article discussed developing an approved-stock list to determine what products should be inventoried at each of an electrical distributor's branches. The next stage in the process to develop inventory-related policies and procedures is to determine how much of a product should be stocked in each location, when to replenish stock and what replenishment source is appropriate for each item (buy from a vendor, transfer from another branch, etc.).

When developing replenishment ground rules, the first step is to separate items sold on a regular basis from products you sell sporadically — when an item is not purchased for several months, but a great quantity of the item is sold in a few months each year. In other words, one specific month's quantity is greater than the average quantity sold or used per month.

To do this, return to the hits analysis developed in last month's article. A hit represents a customer order for a product regardless of the actual quantity ordered. Let's look at a summary of the 16,348 items stocked in a hypothetical warehouse.

Number of Items Months Sold
2,076 or 12.7 percent All 12
2,501 or 15.3 percent Six to 11
4,120 of 25.2 percent Two to five
7,651 or 46.8 percent Less than two

Notice only 2,076 or 12.7 percent of the items were sold every month. The replenishment of these popular products should be micromanaged to maximize inventory turnover (i.e., the number of opportunities to earn a profit) while retaining a high level of customer service. Most books and articles on inventory management focus on maximizing the profitability of items customers request most often. Most, if not all, of the methods involve predicting future demand are based, at least in part, on a calculated average of past usage.

But can these same methods be applied for predicting replenishment of items sold less than six months out? In such a case, that's 11,771 products or 72 percent of the stocked products in the warehouse. Let's look at an example. Consider an item with the following usage history:

Mar Feb Jan Dec Nov Oct
Usage 10 0 0 10 0 0

Ten pieces of the item sold in December, and another 10 pieces sold in March. The history displayed suggests when customers order the product, they order 10 pieces. But any forecast-demand formula based on an average (or weighted average) of past usage will calculate a forecast of future usage of less than 10 pieces. To illustrate, let's apply two common demand-forecast formulas to the usage history: the six-month-rolling-average method and the weighted-average method.

The six-month-rolling-average method averages the usage recorded over the past six months:

(10 + 0 + 0 + 10 + 0 + 0) ÷ 6 = forecast of 3.3 units per month.

This is well below the normal sales quantity of 10 pieces.

The weighted-average method decreases the weight or emphasis of each month's usage history over the previous five months in the average usage calculation:

Month Usage Weight (Emphasis) Extension
March 10 3.0 30
February 0 2.5 0
January 0 2.0 0
December 10 1.5 15
November 0 1.0 0
Total 10 45

The total extension of 45 pieces is divided by the total weight of 10 pieces, resulting in a forecast for April's demand of 4.5 units. Again, this is well below the normal sales quantity of the product.

We could apply other forecast-demand formulas, but the results will probably be the same. The demand forecast will be less than the normal sales quantity of 10 pieces. As a result, there will not be enough inventory to meet a customer's needs.

If an item with sporadic sales remains a stocked product, its replenishment parameters cannot normally be determined using a forecast based on the average of past usage if you want to have enough on hand to fulfill a typical customer order. These items should be maintained based on a multiple of the normal sales quantity — in other words, a specific number of typical customer requests you would like to maintain in your inventory.

Normal sales (usage) quantity

The easiest way to determine the normal sales quantity is to divide the total number of pieces sold or used over the past 12 months by the number of orders the product received over the same time period. For example:

Total pieces sold or used over the past 12 months = 40 pieces

Number of sales and requisitions = four hits

Average sale quantity = 10 pieces

If your computer system does not accurately record hits, use the greater of an adjusted-mean average or mode average (i.e., the most common quantity of monthly usage).

Adjusted-mean average:

Total pieces sold or used over the past 12 months =40 pieces

Number of months with usage activity = four months

Adjusted mean average = 10 pieces

Mode Average

Consider an item with the following usage history. The mode average or most common quantity is 1,000 pieces. This is far higher than the adjusted mean average of 670 pieces (2,010 pieces ÷ 3 months with usage = 670 pieces).

Mar Feb Jan Dec Nov Oct
Usage 1,000 0 1,000 0 0 10

The number of normal sales quantities to maintain in stock

After determining the normal sales or usage quantity, determine the multiple of this quantity to maintain in inventory. Do you want to be able to fill one, two or three sales from stock? The multiple of the normal sales quantity usually depends on the number of times the product sells during the year and the lead time of the product.

For example, if you normally sell an item once a year, you might want to keep only one normal sales quantity in stock. When sold, you could order another from the vendor, but you would run the risk of being out of stock during the lead time.

Here is how the minimum and maximum parameters for this item would be set up if the normal sales quantity for it is five pieces:

Maximum = 5 pieces

Minimum = 0 pieces

When you reach the minimum of zero, you will order enough of the product to bring the stock level back up to five pieces. But if you sold the item six times a year, you might decide to keep two normal sales quantities in stock. When you sold one normal sales quantity, you would issue a replenishment order for another normal order quantity. Here is how the minimum and maximum parameters for this item would now be set:

Maximum = 10 pieces

Minimum = 5 pieces

By issuing a replenishment order when there is still one normal sales quantity on the shelf, you reduce the chance of being out of stock of this more popular product. You also might want to keep an additional normal sale quantity if the item has a lengthy lead time. Why? Because if you sell the one normal sales quantity on the shelf, you will be out of stock for a longer period of time.

It's a good idea to develop a matrix to determine the number of normal-order quantities that will be stocked for a typical sporadic-usage item:

The values in this table can be modified to meet a distributor's investment and desired customer-service goals. The maximum quantity is always set to the number of normal sales quantities you want to maintain in stock. The minimum quantity is set to the maximum less one normal sale quantity (if your computer system orders products when the stock level equals the minimum quantity) or the maximum less one normal sales quantity plus one piece (if your computer system suggests you order products when the stock level drops below the minimum quantity).

Lead Time ≤14 Days ≤30 Days ≤60 Days >60 Days
1-2 Hits/Year 1 1 1 2
3-4 Hits/Year 1 2 2-3 3
>4 Hits/Year 1 2 3 3

Although items with sporadic sales or usage usually do not (or should not) represent a large portion of total inventory investment, they can comprise more than 50 percent of the items on your approved-stock list. Maintaining these items correctly is crucial to providing a high level of customer service. Distributors should follow a simple system to maintain inventory, so a majority of a buyer's time can be spent on those items with recurring usage — the products representing the best opportunity to maximize inventory turnover, customer service and corporate profitability.

With more than 36 year of experience, Jon Schreibfeder is president of Effective Inventory Management Inc., Coppell, Texas, a consulting firm dedicated to helping distributors maximize the productivity and profitability of their investment in stock inventory. Schreibfeder is author of the recently published “Achieving Effective Inventory Management — 3rd Edition.” Contact Schreibfeder at (972) 304-3325 or [email protected].

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