by Robert S. MacDonald Appraisers, lenders and financial analysts have been calculating inventory-turnover ratios for the last 100 years. The ratio is calculated by dividing Cost of Goods Sold by the ending inventory then dividing the quotient into the number of days in the period, e.g. 365 days. Today, lenders can use digitally-reported data and calculate inventory turns by categories, classes or even standard stock keeping units. This provides the lender much more detailed and useful analysis of inventory. Base case: Nonseasonal inventory The reader s attention is directed to Exhibits 1, 2 and 3 beginning on page 59. Most inventory appraisers and lenders value more highly inventory that turns rapidly than inventory that turns slowly. The logic behind their thinking is that the market favors inventory with a high turnover and criticizes slow-turning inventory. In Exhibit 1 the appraiser has valued fast-turning inventory at 70 percent and slowmoving inventory at 30 percent. Contrasted against seasonal inventory Exhibit 2 shows the inventory at the start of the new season with new model inventory that shows little or no turnover because there are little or no sales for the new model items. The appraiser, knowing that this slow-turning inventory is brand new, has valued it at 70 percent. Conversely, in Exhibit 3, carry-over inventory from last year s seasonal inventory shows high turnover relative to last year s sales, but in that case the appraiser valued that inventory at a low 10 percent because she knew that this was carry-over inventory. Seasonal carry-over apparel inventory has much risk because of associated style and fashion factors such as color, pattern, texture and tailoring. By comparison, the (Continued on page 58) 56 THE SECURED LENDER MARCH/APRIL 2003 VOLUME 59 NUMBER 2
Lenders cannot track seasonal carry-over inventory in a truly effective manner without using digital inventory-reporting. appliance inventory shown in Exhibit 1 has very low seasonal, style and fashion risks. Preseason inventory versus postseason carry-over inventory At first glance, Exhibits 2 and 3 appear to be identical and they are except for the Values. The Item Numbers, Descriptions, Unit Amounts and Costs are, in fact, identical, but Exhibit 2 shows a preseason inventory while Exhibit 3 shows a postseason carry-over inventory. Observe how the point in time affects the value of the same inventory. Exhibit 2 shows many items with no historical sales units and high values while Exhibit 3 shows many items with high-inventory turns, but low values. Lenders need to guard against inventory over-advances by demanding loan paydowns on carry-over inventory. Exhibits 1, 2 and 3 are fictional examples of the principles described here. However, a real-life case study is summarized below and it demonstrates in detail why lenders need to monitor seasonal inventory collateral in a more sophisticated and relevant manner. Robert S. MacDonald is a graduate of Alfred University. He is a marketing representative for Plant & Machinery, Inc. and the owner operator of AVS, Corp., Stamford, Connecticut. A case study of an actual orderly liquidation of seasonal carry-over inventory Recently, a company was requested by a secured lender to foreclose on an inventory of casual men s clothing imported from India and Sri Lanka. It took possession of the goods in a Stamford, CT warehouse from the lender s borrower. After several months of litigation, the lender gave the company the green light to sell this carry-over inventory of men s casual clothing which was labeled, plastic-bagged and out of season. The goods were marketed to all the major discount retailers. None had any interest in purchasing this inventory. These major discount retailers were interested in only purchasing recognizable brand names. Some sales interest was found at a different level of trade. The goods were sold to a company operating a chain of salvage stores in Mississippi for $1.00 per item. The sales prices printed on the plastic-packaged garments ranged from $8.00 to $20.00 each. That means about ten cents on the cost dollar. This is why lenders need to guard against loan advances on carryover seasonal inventory through digital inventory-reporting and line-item turnover analysis. This number-crunching, however, has to be combined with a thorough understanding and/or diligent study of the borrower s industry and the borrower s business strategy in that industry. The need for digital inventory-reporting Lenders cannot track seasonal carry-over inventory in a truly effective manner without using digital inventory reporting. There are several additional advantages of digital reporting over paper inventory reporting but the most significant reason is the increased level of confidence that the lender can gain from the reliability of the digital data. With paper reporting, the lender does not even know if the totals Foot correctly. The lender should request the borrower provide reports with item labels that communicate the month and year purchased and/or manufactured so that report readers can better track and understand the inventory items. The lender should also instruct its field examiners to test check these dates by a random sampling of purchase invoices. In addition, the field examiners should test check historical unit sales for accuracy and reliability. A more subtle, but highly significant advantage, of digital reporting over paper reporting is the ability of the lender s account executives and field examiners to carry this digital data home in their lap-top computers from their offices. By so doing, these lending professionals are able to achieve much higher levels of understanding of their borrowers businesses and collateral. 58 THE SECURED LENDER
EXHIBIT 1 NONSEASONAL INVENTORY Item No. Item Units on Hand Cost Extended Unit Sales # Days OLV % OLV $ Description Cost Sales YTD 101 APPLIANCE 1 1000 10 10,000 100000 4 0.7 7,000 102 APPLIANCE 2 2000 20 40,000 2000 365 0.3 12,000 103 APPLIANCE 3 3000 30 90,000 3000 365 0.3 27,000 104 APPLIANCE 4 1500 50 75,000 100000 5 0.7 52,500 105 APPLIANCE 5 2000 100 200,000 2000 365 0.3 60,000 106 APPLIANCE 6 2500 150 375,000 3000 304 0.3 112,500 107 APPLIANCE 7 3000 10 30,000 100000 11 0.7 21,000 108 APPLIANCE 8 4000 20 80,000 2000 730 0.3 24,000 109 APPLIANCE 9 5000 30 150,000 3000 608 0.3 45,000 110 APPLIANCE 10 1000 10 10,000 100000 4 0.7 7,000 111 APPLIANCE 11 2000 20 40,000 2000 365 0.3 12,000 112 APPLIANCE 12 3000 30 90,000 3000 365 0.3 27,000 113 APPLIANCE 13 1500 50 75,000 100000 5 0.7 52,500 114 APPLIANCE 14 2000 100 200,000 2000 365 0.3 60,000 115 APPLIANCE 15 2500 150 375,000 3000 304 0.3 112,500 116 APPLIANCE 16 3000 10 30,000 100000 11 0.7 21,000 117 APPLIANCE 17 4000 20 80,000 2000 730 0.3 24,000 118 APPLIANCE 18 5000 30 150,000 3000 608 0.3 45,000 119 APPLIANCE 19 1000 10 10,000 100000 4 0.7 7,000 120 APPLIANCE 20 2000 20 40,000 2000 365 0.3 12,000 121 APPLIANCE 21 3000 30 90,000 3000 365 0.3 27,000 122 APPLIANCE 22 1500 50 75,000 100000 5 0.7 52,500 123 APPLIANCE 23 2000 100 200,000 2000 365 0.3 60,000 124 APPLIANCE 24 2500 150 375,000 3000 304 0.3 112,500 125 APPLIANCE 25 3000 10 30,000 100000 11 0.7 21,000 126 APPLIANCE 26 4000 20 80,000 2000 730 0.3 24,000 127 APPLIANCE 27 5000 30 150,000 3000 608 0.3 45,000 128 APPLIANCE 28 1000 10 10,000 100000 4 0.7 7,000 129 APPLIANCE 29 2000 20 40,000 2000 365 0.3 12,000 130 APPLIANCE 30 3000 30 90,000 3000 365 0.3 27,000 131 APPLIANCE 31 1500 50 75,000 100000 5 0.7 52,500 132 APPLIANCE 32 2000 100 200,000 2000 365 0.3 60,000 133 APPLIANCE 33 2500 150 375,000 3000 304 0.3 112,500 134 APPLIANCE 34 3000 10 30,000 100000 11 0.7 21,000 135 APPLIANCE 35 4000 20 80,000 2000 730 0.3 24,000 136 APPLIANCE 36 5000 30 150,000 3000 608 0.3 45,000 4,200,000 34% 1,444,000 (Continued on page 60) MARCH/APRIL, 2003 59
EXHIBIT 2 SEASONAL INVENTORY START OF SEASON Item No. Item Units on Hand Cost Extended Cost Unit Sales # Days OLV % OLV $ Description Sales YTD 101 SHIRT A 1000 10 10,000 100000 4 0.1 1,000 102 SHIRT B 2000 20 40,000 2000 365 0.7 28,000 103 SHIRT C 3000 30 90,000 3000 365 0.7 63,000 104 PANTS A 1500 50 75,000 100000 5 0.1 7,500 105 PANTS B 2000 100 200,000 2000 365 0.7 140,000 106 PANTS C 2500 150 375,000 3000 304 0.7 262,500 107 SHORTS AA 3000 10 30,000 100000 11 0.1 3,000 108 SHORTS BA 4000 20 80,000 2000 730 0.7 56,000 109 SHORTS CA 5000 30 150,000 3000 608 0.7 105,000 110 SHIRT AA 1000 10 10,000 100000 4 0.1 1,000 111 SHIRT BA 2000 20 40,000 2000 365 0.7 28,000 112 SHIRT CA 3000 30 90,000 3000 365 0.7 63,000 113 PANTS AA 1500 50 75,000 100000 5 0.1 7,500 114 PANTS BA 2000 100 200,000 2000 365 0.7 140,000 115 PANTS CA 2500 150 375,000 3000 304 0.7 262,500 116 SHORTS AA 3000 10 30,000 100000 11 0.1 3,000 117 SHORTS BA 4000 20 80,000 2000 730 0.7 56,000 118 SHORTS CA 5000 30 150,000 3000 608 0.7 105,000 119 SHIRT AB 1000 10 10,000 100000 4 0.1 1,000 120 SHIRT BB 2000 20 40,000 2000 365 0.7 28,000 121 SHIRT CB 3000 30 90,000 3000 365 0.7 63,000 122 PANTS AB 1500 50 75,000 100000 5 0.1 7,500 123 PANTS BB 2000 100 200,000 2000 365 0.7 140,000 124 PANTS CB 2500 150 375,000 3000 304 0.7 262,500 125 SHORTS AB 3000 10 30,000 100000 11 0.1 3,000 126 SHORTS BB 4000 20 80,000 2000 730 0.7 56,000 127 SHORTS CB 5000 30 150,000 3000 608 0.7 105,000 128 SHIRT AC 1000 10 10,000 100000 4 0.1 1,000 129 SHIRT BC 2000 20 40,000 2000 365 0.7 28,000 130 SHIRT CC 3000 30 90,000 3000 365 0.7 63,000 131 PANTS AC 1500 50 75,000 100000 5 0.1 7,500 132 PANTS BB 2000 100 200,000 2000 365 0.7 140,000 133 PANTS CC 2500 150 375,000 3000 304 0.7 262,500 134 SHORTS AC 3000 10 30,000 100000 11 0.1 3,000 135 SHORTS BC 4000 20 80,000 2000 730 0.7 56,000 136 SHORTS CC 5000 30 150,000 3000 608 0.7 105,000 4,200,000 63% 2,664,000 60 THE SECURED LENDER
EXHIBIT 3 SEASONAL CARRY-OVER INVENTORY END OF SEASON Item No. Item Units on Hand Cost Extended Unit Sales # Days OLV % OLV $ Description Cost Sales YTD 101 SHIRT A 1000 10 10,000 100000 4 0.7 7,000 102 SHIRT B 2000 20 40,000 2000 365 0.1 4,000 103 SHIRT C 3000 30 90,000 3000 365 0.1 9,000 104 PANTS A 1500 50 75,000 100000 5 0.7 52,500 105 PANTS B 2000 100 200,000 2000 365 0.1 20,000 106 PANTS C 2500 150 375,000 3000 304 0.1 37,500 107 SHORTS AA 3000 10 30,000 100000 11 0.7 21,000 108 SHORTS BA 4000 20 80,000 2000 730 0.1 8,000 109 SHORTS CA 5000 30 150,000 3000 608 0.1 15,000 110 SHIRT AA 1000 10 10,000 100000 4 0.7 7,000 111 SHIRT BA 2000 20 40,000 2000 365 0.1 4,000 112 SHIRT C A 3000 30 90,000 3000 365 0.1 9,000 113 PANTS AA 1500 50 75,000 100000 5 0.7 52,500 114 PANTS BA 2000 100 200,000 2000 365 0.1 20,000 115 PANTS CA 2500 150 375,000 3000 304 0.1 37,500 116 SHORTS AA 3000 10 30,000 100000 11 0.7 21,000 117 SHORTS BA 4000 20 80,000 2000 730 0.1 8,000 118 SHORTS CA 5000 30 150,000 3000 608 0.1 15,000 119 SHIRT AB 1000 10 10,000 100000 4 0.7 7,000 120 SHIRT BB 2000 20 40,000 2000 365 0.1 4,000 121 SHIRT CB 3000 30 90,000 3000 365 0.1 9,000 122 PANTS AB 1500 50 75,000 100000 5 0.7 52,500 123 PANTS BB 2000 100 200,000 2000 365 0.1 20,000 124 PANTS CB 2500 150 375,000 3000 304 0.1 37,500 125 SHORTS AB 3000 10 30,000 100000 11 0.7 21,000 126 SHORTS BB 4000 20 80,000 2000 730 0.1 8,000 127 SHORTS CB 5000 30 150,000 3000 608 0.1 15,000 128 SHIRT AC 1000 10 10,000 100000 4 0.7 7,000 129 SHIRT BC 2000 20 40,000 2000 365 0.1 4,000 130 SHIRT CC 3000 30 90,000 3000 365 0.1 9,000 131 PANTS AC 1500 50 75,000 100000 5 0.7 52,500 132 PANTS BB 2000 100 200,000 2000 365 0.1 20,000 133 PANTS CC 2500 150 375,000 3000 304 0.1 37,500 134 SHORTS AC 3000 10 30,000 100000 11 0.7 21,000 135 SHORTS BC 4000 20 80,000 2000 730 0.1 8,000 136 SHORTS CC 5000 30 150,000 3000 608 0.1 15,000 4,200,000 17% 696,000 MARCH/APRIL, 2003 61