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Objectives

2. Objectives. Supply Chain Choices

albert
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Objectives

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    1. 1

    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

    8. 8 Two Order Periods How are they different?

    9. 9 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

    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 m-zs

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

    16. 16 Solve for k with total close to 10000 (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 (we’ll 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, mi-600-k*si) Same approach as before (determine the appropriate k so that lot size <10,000)

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

    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?

    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

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