McFadden’s department store ha
McFadden’s department store has been a profitable family-ownedretail business (consisting of several stores in the Pacific Coastregion) since its beginning in 1910. The last five years have beenrough due to the economy, and McFadden’s has been losing ground tonational department and discount stores moving into the area.
The executive team is hopeful that a turnaround is finallyoccurring. Last year’s sales volume for the entire retail storechain was $50 million. The National Retail Federation (NRF)predicts an increase in retail sales due to positive economicprojections being felt throughout the country (e.g., unemploymenthas been dropping, the stock market is up, so investors have moremoney in their pockets, working hours have been steadilyincreasing, and there is an expectation of pent-up consumer demandafter a number of years of lower sales and belt-tightening inhouseholds). Overall, retailers are expecting one of the bestholiday seasons in a long time!
The NRF estimates a 5.5% increase in sales during the July toDecember 2019 season for the Pacific Coast, where McFadden’soperates. Upper management believes that this increase in saleswill be felt throughout all of its departments.
You are the buyer for Department 121, which sells youngmen’s clothing. This department has been one of the moreprofitable departments for the company. Last year (2018), salesfrom Department 121 for the July-December season reached $750,000.Your sales forecast for this year (2019) must take intoconsideration the NRF’s prediction for an increase in sales thisperiod, and be based on an initial markup percentage of 52%.
Reductions for this period in 2018 totaled $105,000. Managementexpects the dollar amount of reductions to increase this season by2% in an attempt to spur additional sales. The following reductionpercentages are planned for November and December:
November: 21%
December: 35%
Relying on information from the last three years, you forecastthat 28% of seasonal sales will occur in November and 38% inDecember:
November:28%
December: 38%
You have the following additional information on the historicalstock-to-sales ratio for this type of department:
July: 3.0
August: 1.9
September: 2.1
October: 2.2
November: 3.0
December: 3.2
Today is November 11, 2019. Your inventory database has recordof an additional merchandise order valued at $300,000 that has yetto be delivered. It’s on a container ship arriving at one of thePacific ports in five days. Also, the distribution center justnotified you via the in-house inventory alert system that anotherlarge shipment has just arrived on the loading docks for Department121. This shipment contains merchandise valued at $190,000 and hasyet to be scanned into the computer system.
Finally, your reports show that your desiredbeginning-of-the-month stock (BOM) for December is $962,160.
- Given the NRF’s retail trend forecast for 2019, you need toproject planned seasonal sales (July-December) for Department 121for 2019.
- Calculate Department 121’s projected monthly sales forNovember.
- Calculate Department 121’s existing inventory or BOM inventoryfor November.
- Calculate Department 121’s desired ending inventory or EOMinventory for November.
Answer:
Answer:
1. CALCULATIONOF DEPARTMENT 121’S DESIRED EOM INVENTORY FORNOVEMBER
Given:Department 121 Desired BOM Inventory for Dec.month is = $ 962160.
Hence, Department 121 Desired EOM Inventory for Nov month is= $ 962 160 (Next month’s Opening balance isCurrent month’s Closing balance).
2. CALCULATIONOF DEPARTMENT 121’S PROJECTED MONTHLY SALES FORNOVEMBER
GIVEN:Historical stock-to-sales ratio for Nov. = 3
Stock to Sales Ratio = Monthly Stock / Monthly Sales = 962160/Monthly Sales = 3.
Therefore, Projected Monthly Sales forNovember = 962160/3 =$ 320720.
3. CALCULATIONOF DEPARTMENT 121’S EXISTING INVENTORY OR BOM INVENTORY FORNOV.
BOM Inventoryfor Nov. = EOM Inventory + Sales – Purchases
= $ 962 160 + $ 320 720 – ($ 300 000 + $ 190 000)
= $ 1 282 880 – $ 490 000
= $ 1 772880
4.CALCULATIONOF DEPARTMENT 121’S PLANNED SEASONAL SALES (JULY -DEC.2019)
= 750 000 X 5% OF 750 000 = $ 791 250