Presentation is loading. Please wait.

Presentation is loading. Please wait.

1 Sport Obermeyer Case Prof Mellie Pullman. 2 Objectives Supply Chain Choices & Operations Strategy Product Category challenges Operational changes that.

Similar presentations


Presentation on theme: "1 Sport Obermeyer Case Prof Mellie Pullman. 2 Objectives Supply Chain Choices & Operations Strategy Product Category challenges Operational changes that."— Presentation transcript:

1 1 Sport Obermeyer Case Prof Mellie Pullman

2 2 Objectives Supply Chain Choices & Operations Strategy Product Category challenges Operational changes that reduce costs of mismatched supply and demand Coordination Issues in a global supply chain

3 3 Type of Product Typical Operational & Supply Chain Strategies Cost Quality Time (delivery, lead time, etc) Flexibility (multiple choices, customization) Sustainability Sport Obermeyer ?

4 Challenge of delivering on the strategy?

5 5 Challenges of matching supply to demand Supply Side Demand Side

6 6 Costs & Risks of Over-stock versus Under-stock Over-stock Under-stock

7 7 November Pre year February September August March November China ColoradoUS Retailer Design clothes Order textiles & styles Las Vegas show Warehouse Distribute to retailers Make orders to Sport O. Make Fabric Assemble Clothes Deliver to Colorado Take Orders Make forecasts Retail Season

8 8 Two Order Periods How are they different?

9 9 Speculative Production Capacity Reactive Production Capacity New Info. Material Lead time Lead Time to Store Risk-Based Production Sequencing Strategy

10 10 Planning Approach How many of each style to product? When to produce each style?

11 11 Buying Committee Forecasts Ave Forecast Stan d Dev 2 x Stand Dev StylePriceLauraCaroly n GregWendyTomWally JobMarket Director CS Mgr Product -ion mgr Product -ion coord Sales Rep VP Gail $ Isis $ Entice $ Assault $ Teri $ Electra $ Stephani $ Seduced $ Anita $ Daphne $ Totals Standard Deviation of demand= 2x Standard Deviation Forecast

12 12 Team Break out 1 Using the available data, assess the risk of each suit and come up with a system to determine: How many of each to style to produce When to produce each style Where to make it

13 13 Low Risk Styles We under-produce during initial production so we want: Least expensive products Low demand uncertainty Highest expected demand

14 14 Standard Normal Distribution - produce z

15 15 Production Strategy A Account for production minimum If we assume same wholesale price, we want to produce the mean of a styles forecast minus the same number of standard deviations of that forecast i.e., i -k i (k is same for all). Approach: produce up to the same demand percentile (k) for all suits. Sum ( -k ) each style = 10,000 (meet production minimum) Determine k for all styles

16 16 Solve for k with total close to (k=1.06)

17 17 But what about the batch size minimums? Large production minimums force us to make either many parkas of a given style or none. How do we consider the batch size minimums for the second order cycle?

18 18 Strategy B: Categories for Risk Assessment m= minimum order quantity (600 here) SAFE: Styles where demand is more than 2X the minimum order quantity (well have a second order commitment) SOS: Sort of Safe=expected demand is less than minimum order quantity. If we make em at all, make em first (have to make minimum) RISKY: demand is between C1 & C2.

19 19 Approach Compute risk for each style Rank styles by risk Figure out the amount of non-risk suits to produce in the first run

20 20 Assign Risk

21 21 Modified Approach Determine how many styles to make to give total first period production quantity. Assess each case by determining the optimal quantities for non-risk suits using Production Quantity = Max(600, i -600-k* i ) Same approach as before (determine the appropriate k so that lot size <10,000)

22 22 Example: Production Quantity = Max(600, i -600-k* i ) ; k =.33

23 23 Should we make more suits? Production minimum order is 10,000? Pros? Cons?

24 24 Sport Obermeyer Savings from using this risk adjustment Models DecisionsSport O Decisions Total Production (units)124,805121,432 Over-production (units)22,03625,094 Under-production (units) Over-production (% of sales) 1.3%1.73% Under-production (% of sales).18%1.56% Total Cost (% of sales)1.48%3.30%

25 25 Team Breakout 2 What supply chain & operations changes can be implemented to reduce stock-outs and mark-downs? Design, production, forecasting, etc.? Specific: How are you going to do it, Actions?

26 26 Operational Changes to Reduce Markdown and Stock-out Costs Reducing minimum production lot-size constraints How ?

27 27 Effect of Minimum Order Quantity on Cost

28 28 Capacity Changes Increase reactive production capacity How? Pros and cons? Increase total capacity How? Pros and Cons?

29 29 Stock-out & Mark-down Costs as a Function of Reactive Capacity

30 30 Lead Times Decrease raw material and/or manufacturing lead times Which ones? How?

31 31 Lead Times Reduce findings leads times (labels, button, zippers) inventory more findings standardize findings between product groups more commonality reduced zipper variety 5 fold.

32 32 Where does it make sense to inventory product? Griege Fabric Dye Solid Colors Size 8 Black Electra SKU Printed SKU

33 33 Obtain market information earlier

34 34 Accurate Response Program Using buying committee to develop probabilistic forecast of demand and variance (fashion risk) Assess overage and underage costs to develop relative costs of stocking too little or too much Use Model to determine appropriate initial production quantities (low risk first) Read early demand indicators Update demand forecast Determine final production quantities


Download ppt "1 Sport Obermeyer Case Prof Mellie Pullman. 2 Objectives Supply Chain Choices & Operations Strategy Product Category challenges Operational changes that."

Similar presentations


Ads by Google