Sport Obermeyer
...edge) and probability of accuracy: 0.3 Vice President 0.2 Marketing director 0.2 Customer Service Manager 0.15 Sales Representative 0.1 Production Manager 0.05 Production Coordinator 4. Using the data provided about the profitability of the skiwear when sold in season (24%) of wholesale and the loss level in late season (8% wholesale) we have run an iteration of each of the forecasted sales predictions to determine the Q for One-Time Inventory commitment based on the following formula (see pg 715 Krajewski): Payoff = pQ = pD – l(Q-D) where the tabled results represent the quantity-demand combinations where some units must be disposed of after the season (Q>D). Using OM explorer we have calculated the resulting Max Payoff Q (See Attach 1-A for an example, Attach 1-B for the Payoff Values plugged into the One-Time Contribution margin table.) 5. The style forecasts are re-organized in priority of highest correlation accuracy (ie lowest 2X Standard Deviation is least risky forecast) We have expressed this as a function of the Coefficient of Variation of the forecasts predicted by the buying committee: Vc = StDev/Mean (See Attach 1-C for results). 6. We have expressed the variation and expanded upon the coefficient correlation by running an ABC analysis wherein A styles are closely correlated with the market (low Vc) allowing for an initial order quantity at the high end, B styles ordered at the mid level and C styles (with lowest correlation) ordered at the minimum variation calculated. (See attach 1-D) 7. Finally, based on the constraint that the total production quantity must equal 10,000 units the distribution is normalized, resulting in the following initial order quantities: 794 Gail 998 Entice 845 Isis 1400 Assault 925 Teri 1250 Electra 539 Stephanie 1593 Seduced 603 Daphne 1053 Anita 10000 Total 8. Key operational changes are recommended to improve performance. In Exhibit 4 the Planning and Production Cycle is described, however it is certainly a place to start by looking at the imbalance between the maximum production capacity per month of 30,000 units and the 7 months of full scale production that seem to require an additional year to prepare for. In fact the best indicator of design starts with the European shows in Feb. and ends with the Las Vegas show in Mar every year, however the current process sees these two events over a year apart. • Bringing the two events into the same year, taking advantage of the productive capacity, placing prototype orders immediately upon exiting the European show and beginning the first order quantities would enable Sport Obermeyer to fully utilize the capacity of the facilities available with more accurate and current information. • Sport Obermeyer should also consider how the consolidated cycle would enable a better response for replenishment orders as well. The lead time of materials is up to 90 days, thus requiring the Graige fabric t be ordered for the first production quantities in the preceding November to enable production in Mar. • Rather than ordering all material at the same time the material should be periodically ordered to ensure adequate supply stock and the system fill. • A detail Value Stream analysis of the actual production activities rendered in HK, for the purpose of defining standardized work, people qualifications and support systems that can be transplanted to the Chinese facilities is one possible solution to eliminating a significant variation in the production process. • Lead times for the various materials are from 45-90 days, these need to be explored for reduction of variation as well. By setting a goal of 30 day lead times for al materials (in particular the zippers are extremely long) the production cycle would be more flexible and the order to delivery lead time shortened, perhaps reducing the quantities required to fill the demand. Attach 1-A Example Calculation of Q – One Time Order Quantity Profit $35.52 (if sold during preferred period) Loss $11.84 (if sold after preferred period) Demand Probabilit...