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Sport Obermeyer

Sport Obermeyer. What to order? What are the issues?. A Sample Problem. Commit 10,000 units before show Commit 10,000 units after show Minimum of 600 units. A First Approach. Ignore differences in Profit margins Salvage values Ignore minimum lot sizes Consider only first order cycle.

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Sport Obermeyer

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  1. Sport Obermeyer • What to order? • What are the issues?

  2. A Sample Problem • Commit 10,000 units before show • Commit 10,000 units after show • Minimum of 600 units

  3. A First Approach • Ignore differences in • Profit margins • Salvage values • Ignore minimum lot sizes • Consider only first order cycle

  4. Sample Problem

  5. Normal Distribution Std Dev.s

  6. Idea 1 • Make all products equally likely to sell out • Choose a single std dev. To set production quotas for all products

  7. What should the Std. Dev. Be?

  8. Normal Distribution Set order Qty to this many std. devs Probability we stock out = Probability demand exceeds over qty = 0.86 Probability we discount last item = Probability demand is smaller than order quantity = 0.14 Std Dev.s

  9. What’s Wrong with This? • What else should we be looking at? • Still just worried about • Order up to 10,000 • One order cycle • No minimum order qty.

  10. A Second Idea • Look at 1 Product • How to trade off risks of overstock (discounting) vs risks of understock (lost sales)? • If we order Q • The last item faces what risk of being discounted? • Probability Demand < Q = F(Q) • The last item faces what risk of selling out • Probability Demand > Q = 1 - F(Q)

  11. We want to be indifferent • We want two to be equal • Expected loss from Overstock = CO*F(Q) • Expected loss from Lost Sale = CL*(1-F(Q)) • A little Algebra: • F(Q) = CL/(CO+CL)

  12. Example • Oversimplification • Lost Sale: CL = Selling Price - Cost • Discount: CO = Cost - Salvage Value • Electra: • Selling Price $173 • Cost $ 50 • Salvage $ 0 • Lost Sale: CL = $123 • Discount: CO = 50 • Want Probability of Discount = F(Q) = 123/173 = 0.71 • Find Q with this cumulative probability: ~2,599

  13. Balancing Risks

  14. Additional Thoughts • What’s the derivative of the cost as a function of order quantity? • Expected Cost of Discounting Last Item (increases with order size) - Expected Cost of Stocking Out (decreases with order size) • Decrease Order with largest estimated derivative

  15. Estimated Derivative

  16. 2-Rounds • What additional Issues? • What rules of thumb? • Only order late • Surely order early

  17. Differences in Suppliers • Hong Kong • Higher Cost • Smaller Minimums • Faster • What rules of Thumb?

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