8. Inventory Control

Inventory management is the process of controlling inventory with the fewest people and the least amount of inventory. Maintaining an optimum inventory is the most important aspect of inventory management. Implementing the techniques necessary to maintain an optimum inventory can equal massive company-wide savings.

ABC analysis is a technique used to prioritize inventory by its relative importance. The priority can be a number of factors. The following are generally the most commonly used priorities. The issue with these is that they are usually conflicting goals. For example, the highest selling strategy may sacrifice profit, and the maximum-revenue strategy makes it impossible to maintain a minimum inventory. The goals outlined are as follows:

• Maximize the revenue

• Maximize the profit

• Maximize the units sold

• Minimize inventory

• Maximize turns

These priorities cannot be collectively attained as one goal. Companies can choose to prioritize inventory on dollar sales, profit of the item, or number of items sold to maintain a minimum inventory and maximize turns. Each one of these has a definite impact on internal and customer goals.

Companies must maximize sales of the highest revenue items because sales fulfill the revenue goals set by upper management. In this case, the highest revenue and profit items should be coded as A items. This would tell the computer to stock more of the A item and so lessen the chance of out-of-stocks. The items that sell the highest quantity should also be categorized as A items because they will be the first to be noticed by the customer as the fill rate falls.

Fill rate is calculated as:

A good example of fast-moving items is batteries. If a customer orders batteries and they are out of stock, the customer is dissatisfied with his shopping experience. Customers believe that commodity items should always be available. To avoid this problem, prioritize the inventory into five categories focusing on high revenue, high profit, and high quantity:

• Class A is the top 20% with 5% of the inventory.

• Class B is the next 20%, which generally is 10% of inventory.

• Class C is the next 20%, which is generally 18% of inventory.

• Class D items represent the next 20%, which accounts for 27% of the inventory.

• Class E items represent the next 20%, which accounts for the remaining 40% of the inventory.

At this point, it becomes necessary to run the distribution by line value (DBLV) report for the revenue items, the profit items, and the high line or quantity items in each department. The DBLV for profits will list the items in each department for each warehouse in sequence from high to low for the most profitable items. The DBLV report for fast-moving items will list the items in sequence from high to low for the fastest moving items inventory by department and by warehouse. Now combine the first percentages for all three, add them together, and divide by 3 to get a global categorization. This allows for a blended approach of taking the best out of all three goals.

For example, item AA sorted by revenue may have a 3%, which means it is the top 3% of revenue growth in the department. Items sorted by profit may have a 12% figure, meaning they are ranked in the top 12% of profit for the department. The sort by SKU may rank

item AA at the 30% rank. Now add all ranks together and divide by 3 to get the total global ranking by department for item rank. This is still high enough to categorize item AA because it’s the top 20%. This will be conducted for each item in the inventory by department and by warehouse.

Each category can be weighed differently. Weighted averages can be used to measure the priority within the company. Let’s say the quantity ordered is the highest priority in the company because this is what the customer actually measures the company by. The customer in this case measures by line fill rate. So the quantity ordered has a weight of 45%. The next is the profitability, which receives a weight of 35%, followed by the revenue or highest price times demand, which is weighted at 20%. The new consolidated ranking by department for item AA is:

which is still in the A category of top 20%. The operational savings is as shown next.

• Sales before the ABC Classification program = $931,000,000.

• Turns before the ABC Classification program = $931,000,000 / $191,905,560 = 4.85 turns.

• Inventory reduction from the ABC Classification program is 1.2%.

• The Inventory Reduction results in a 1.2% × $191,905,560 = $2,299,306 reduction in inventory.

• The new inventory is $189,602,693.28.

• Carrying cost reduction = .266 × $2,299,306 = $611,615.

• Freed-up cost of capital = .02 × $2,299,306 = $45,986.

• There’s a service-level improvement of 2%. This will increase sales. If there is 1% out of stock, three-fourths of the customers will wait until it is in stock. One-fourth will buy it direct from the manufacturer or buy it from a competing distributor. If the retailer is out of stock, only one-third of the customers come back to buy the product. This is a 66.67% reduction in sales because of out-of-stock. A 2% service-level increase represents a 2% × 25% = .5% increase in sales.

• The new increase in revenue is .5% × $931,000,000 = $4,655,000.

• The additional profit generated from the increase in sales is 18% × $4,655,000 = $837,900.

• This represents a new sales figure of 1.005 × $931,000,000 = $935,655,000.

• The new turns are $935,655,000 / $189,602,693 = 4.94 turns.

Total Lean Savings is $2,956,907.

Total Lean and Green Savings is $1,719,683.

• It must be within 7% of the original price. There may be other price rules that apply, depending on the unique nature of the product.

• It must have the same or better functionality.

• It must look the same as far as retail appeal.

• The item must be readily available.

• The item must have the same consumer acceptance as the primary item.

• The item must be shippable by UPS or small parcel shipping.

The substitute program allows for a decrease in the out-of-stocks by .50%, with a small inventory decline of .25%, which amounts to a $473,273.88 reduction on an $189,309,553 inventory.

• The Sales = $935,655,000.

• Turns before the substitution program = 4.94 turns.

• Sales before the substitution program = $935,655,000.

• Reduced out-of-stocks by .50%. This would increase sales as mentioned in the ABC classification section by (1 + .5% × .25) = .125%. The sales increase is $1,169,568.

• Added profit from the sales increase = 18% × $1,169,568 = $210,522.

• Sales after the substitution program = 1.00125 × $935,655,000 = $936,824,568.

• Inventory reduction from the substitution program is .25%.

• The actual amount of Inventory Reduction is .25% × $189,602,693 = $474,007.

• The new inventory is $189,602,693 − $474,007 = $189,128,687.

• Carrying cost reduction = .266 × − $474,007 = $126,086.

• Freed-up cost of capital = .02 × $474,007 = $9,480.

• Old turns = 4.95.

• The new turns are $936,824,568 / $188,836,279 = 4.95.

Total Lean Savings is $346,088.

Total Lean and Green Savings is $392,304.

It is a statistical fact that the more demand there is in a period, the less volatility is experienced on the item. This leads to a lower safety stock level and fewer out-of-stocks with a lower overall inventory. The question posed is why all the items in every warehouse are necessary when some of the items barely sell in other distribution centers. One reason for this is the lucrative client who demands to have a product to stock in a specific warehouse.

The item is stocked in the specified warehouse as well as the other seven warehouses, which barely have any movement. This low movement translates into a phenomenon known as lump demand. This pattern of demand is almost impossible to forecast. There may be months of very low demand or zero demand and then, unexpectedly, large demand patterns begin and are interspersed through the year. An example of this is SKU item BB’s monthly demand from January to December:

January = 500, February = 0, March = 20, April = 0, May = 0, June = 300, July = 40, August = 500, September = 0, October = 0, November = 0, December = 500

If there is no clear pattern or seasonal explanation, it is considered lumpy demand. In some cases, the safety stock could be equal to three times the average usage. This is a waste of merchant and cash flow tied up in inventory.

The algorithm used in central stock items is to test the VI, or Volatility Index, of the item. If the Volatility Index is defined as:

and if the VI is < .20, then the item is not considered a central stock candidate. In forecasting terminally, MAD stands for Mean Absolute Deviation. The formula for MAD is:

where F is the forecast for the items throughout the year for each period. The xi is the monthly value of demand for the current year. Performance won’t be improved much by central stocking the items if the VI is less than or equal to .20. The following represents the algorithm used for central stocking an item.

• If the VI is greater than .20 but less than .50, use Pareto analysis to central stock the items. The Pareto analysis is based on total dollar revenue per item. The top 20% of this value will be considered central stock only if

• The inventory can be shipped by FedEx or UPS.

• The percent cost for freight does not exceed 20% of the gross margin dollar.

• If the VI is greater than .50 and less than 1, try to central stock the next highest 10% of the stock from the Pareto analysis, which is the top 30%. The next set of inventory will be considered central stock only if

• The inventory can be shipped by FedEx or UPS.

• The percent cost for freight does not exceed 20% of the gross margin dollar.

• When the VI gets larger than 1, try to central stock all the items without using Pareto analysis. The key factor is that

• The inventory must be shipped by FedEx or UPS.

• The percent cost for freight does not exceed 20% of the gross margin dollar.

One last operation will be performed by the software:

• The central warehouse will be the warehouse with the largest outbound volume no matter what the VI value is.

• The item will be assigned to the warehouse that has the lowest UPS cost. This will override an earlier judgment if the software chose another warehouse. This costing function is performed by comparing the ZIP Code of the shipping warehouse to the ZIP Code of the customer. This is performed by the software that is provided by UPS and that is integrated into the shipping program.

The warehouse that has a VI less than or equal to .20 will not be central stocked. The warehouse with the same SKU with a VI greater than .20 will be up for consideration to move its stock to another warehouse using the preceding rules. The following rules apply to the dissemination of the warehouse inventory. Table 8-1 shows an example of an item in each warehouse by month. Notice that if the same item is stocked in one central warehouse, the demand volatility will be much less. This is represented in the last column.

Table 8-1. Demand for Eight Warehouses

The SKU is a class B item, so it will have a 94% service level assigned to it. This gives a k value of 1.94. The k is defined in the forecast section but it is similar to the Z factor in statistics. The k values are found in Table 21-1 in Chapter 21, “The New Sustainable EOQ Formula.” It gives the relationship of k to the Z transform. For instance, a Z of 1 represents one standard deviation, which represents 69.27% of the sample. In this case, the k value of 1.94 states a desire for a level of safety stock that gives the customer a 94% service level or 6% out-of-stocks. The Order Quantity if the item minimum is 1 is equal to Q = (Avg. Demand/Month) * (LT + RT) + k * MAD * (LT + RT)^.7. This is also further explained in Chapter 19, “Forecasting Methodology and Gamma Smoothing: A Solution to Better Accuracy to Maintain Lean and Green.” The lead time is 1.5 months and the review time is half a month = .5.

The lower the coefvficient of variation (CV), the less safety stock is in the system and the lower the volatility is in the demand pattern. The formula for the CV is:

The following example shows the calculation of the OQ (Order Quantity) for each of the nine distribution centers:

DC1 OQ = (250) * (2) + k * 333 * (2)^.7 = 1,038 and CV = 1.333333333

DC2 OQ = (91) * (2) + k * 106 * (2)^.7 = 353 and CV = 1.168195719

DC3 OQ = (217) * (2) + k * 183 * (2)^.7 = 729 and CV = 0.846153846

DC4 OQ = (121) * (2) + k * 116 * (2)^.7 = 429 and CV = 0.959770115

DC5 OQ = (10) * (2) + k * 15 * (2)^.7 = 44 and CV = 1.5

DC6 OQ = (44) * (2) + k * 31 * (2)^.7 = 138 and CV = 0.698113208

DC7 OQ = (8) * (2) + k * 13 * (2)^.7 = 37 and CV = 1.5

DC8 OQ = (83) * (2) + k * 83 * (2)^.7 = 279 and CV = 0.833333333

CON OQ = (824) * (2) + k * 352 * (2)^.7 = 2,218 and CV = 0.428210313

Total Order Quantity for all warehouses (OQ) = 3,047, which stands for the total of all the order quantities for all the warehouses. The CON stands for the consolidated warehouse. For the central stocked warehouses the average demand per month is 824. This represents the average of the demand for all nine warehouses combined. There is less variation in the demand from month to month, so the MAD is lower as a percentage to the overall average. This is proven because the coefficient of variation is .428210314. This figure is lower than any one of the individual distribution center’s CVs. This is the biggest reason that the overall inventory of the central warehouse is less than that of the individual warehouses combined. Note that Central Stock OQ = (824) * (2) + k * 352 * (2)^.7 = 2,218.

By definition, average inventory = 1/2 OQ. The analysis shows that for the warehouse that does not centrally stock its products, the average inventory would be 1/2 × 3,047 = 1,523. The warehouse that uses the central stock process has an average inventory of 1/2 × 2,218 = 1,109. This results in a 27.2% reduction in inventory with a higher service level because the product is being ordered more often. Interestingly, the central stock items are class C, D, and E items, which are not the fastest moving items. This is actually the area of inventory that needs minimized because it represents 60% of sales with 85% of inventory. The A and B items represent 40% of sales with 15% of inventory. If the inventory was $189,309,553 and the company central stocks 15% of this inventory, then the new inventory is 15% × 27.2% = 4.1%.

• The Sales = $936,824,568.

• Turns before the Central Stock program = 4.96 turns.

• Inventory reduction from the Central Stock program is 4.1%.

• The actual Inventory Reduction is 4.1% × $188,836,279 = $7,742,287.

• The new inventory is $188,836,279 − $7,742,287 = $181,093,991.

• Carrying cost reduction is .266 × $7,742,287 = $2,059,448.

• Freed-up cost of capital is .02 × $7,742,287 = $154,845.75.

• The new turns are $936,824,568 / $181,093,991 = 5.17 turns.

Total Lean Savings is $2,214,293.

Total Lean and Green Savings is $2,970,335.