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Coordinating Capacity and Inventory in Supply Chains with High-Value Products Murat Erkoc Associate Professor and Director UM Center for Advanced Supply.

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Presentation on theme: "Coordinating Capacity and Inventory in Supply Chains with High-Value Products Murat Erkoc Associate Professor and Director UM Center for Advanced Supply."— Presentation transcript:

1 Coordinating Capacity and Inventory in Supply Chains with High-Value Products Murat Erkoc Associate Professor and Director UM Center for Advanced Supply Chain Management Department of Industrial Engineering University of Miami Coral Gables, Florida.

2 Matching Demand and Supply Two types of costs occur if supply and demand do not match Supply opportunity cost Supply opportunity cost Supply > Demand => Inventory cost Supply > Demand => Inventory cost To match the two Manage Supply Manage Supply Capacity management Inventory management Manage Demand Manage Demand Marketing/pricing

3 High-Tech Manufacturing Supply Chain Rapid innovation & volatile demand High obsolescence rate on technology Short product life-cycle Capital intensive facilities ($2 Billion +) High capacity costs Manufacturers are conservative in capacity expansion of any form Capacity reservation contracts

4 CM 1 Buyer 1 Buyer M Buyer 2 Spot Market CM 2 CM n Supplier K Supplier 2 Contract Manufacturers High-Tech Supply Chain Building Blocks Capacity Reservation Contract Supplier 1

5 Product Life-Cycle

6 Integrated Channel Supplier w p c V(k) Buyer Market F(x) expected sales given capacity k

7 Delegation of Control in the Supply Chain Systems Profit (concave) Let k o be the system optimal solution Suppliers newsvendor profit function Let k * be the newsvendor solution

8 Double Marginalization - suboptimal Supplier w p c V(k) Buyer Market F(x) Due to double marginalization the system optimal capacity is always greater than the suppliers newsvendor capacity Optimal Competitive Outcome

9 Reservation Contract with Deductible Fee For each unit of capacity reserved, the buyer is charged a fee The fee is later deducted from the purchasing price if the reserved capacity is used by the intended customer If the buyers demand exceeds the reservation amount, the orders are satisfied based on the availability of extra capacity Customer reservations are locked in and some extra capacity may be built during expansion The wholesale price w and product cost c are set at the design- win phase, which are not negotiable

10 The Sequence of Events Supplier announces reservation fee (r) Buyer announces how much to reserve (q) Supplier decides how much capacity to build (k) Demand is realized (x) Buyer is penalized for unused reserved capacity

11 Suppliers Capacity Decision If, then the constraint must be binding If, then the constraint must be binding

12 Buyers Incentive to Reserve Buyer never reserves less than k*. In fact, she reserves only if the reservation fee is below a certain threshold, r t. The reservation quantity will be at least q t, where q t is a function of w and does not depend on p The buyer reserves iff r r t Threshold fee Threshold Reservation Qty.

13 The Suppliers Faces Three Profit Scenarios in sequence as the Buyers Margin Decreases r min r* Reservation Fee Expected Profit Reservation Fee Expected Profit Reservation Fee Expected Profit r min r Scenario 1: High Scenario 2: Medium Scenario 3: Low The buyers margin must be sufficiently high to justify capacity reservation Theorem: It is individually rational for the supplier and the buyer to enter the reservation contract if the buyer revenue margin p is no less than the threshold p t as follows:

14 Capacity reservation may create surplus for the channel However, except for a few special cases the surplus is sub-optimal We design two additional coordination mechanisms to achieve optimality Partial-deduction (PD) contract Partial-deduction (PD) contract Cost-sharing (Options) contract Cost-sharing (Options) contract System Optimality and Reservations

15 Inventory Management with Horizontal Model Subcon SupplierCustomer SupplyDemandBuffer

16 Horizontal Challenges Conflict w/in the Supply Chain No Motivation for Holistic SCM for Subcons, Drives Suboptimal Behavior Balance Harder to Maintain as More Trading Partners are Introduced Decreased Deliver Performance, Slower Inventory Velocity and Less Flexibility Information Intermediation Information Intermediation Distributed Inventory Distributed Inventory

17 Information Intermediation Demand Information Received is Brokered by Subcons Introduces Latency – Existence of Customer Demand Changes Not Immediately Apparent to the Supplier Slows Responsiveness Slows Responsiveness Amplifies Bull Whip Effect Amplifies Bull Whip Effect Inflates Full Stream Inventory Inflates Full Stream Inventory Overforecasting Effect – Sum of Individual Subcontractor Demand is Greater than End Customer Demand Redundant Upside Planning Redundant Upside Planning Subcontractor Share Uncertainty Subcontractor Share Uncertainty

18 Optimization Model Distribution Method Demand Mgmt CentralRegional Installation Echelon Vis. To CM WIP & Dmd Identify best method of distribution and demand management for outsource models.

19 Scenarios Distribution Method Demand Mgmt CentralRegional Installation Echelon Vis. To CM WIP & Dmd ICIR EREC Central: inventory is staged at central supplier location. Regional: inventory is staged at customer regional locations Installation: legacy information policy – only CM forecast and orders shared with supplier. Echelon: collaborative information policy – CM WIP, inventory and end customer demand on CM shared with supplier.

20 Installation Policies (No visibility)

21 Echelon Policies Visibility on Sub-Con WIP and FGI

22 Objectives Identify the business model that leads to Higher profits Higher profits Higher service levels for the end customer Higher service levels for the end customer Lower inventory costs Lower inventory costs Higher inventory turnover/velocity Higher inventory turnover/velocity Find scenarios that lead to desirable performance combinations Investigate the advantages and drawbacks of each model under different parameter settings and demand structures Performance Measures

23 Approach Create an Excel Spreadsheet model to simulate the supply chain for the 4 scenarios Part 1: Decision Making IC IR EC ER Part 2: Performance Evaluation (Test Bed) IC IR EC ER Input Parameters Scenarios

24 Scenario Parameters Demand forecast refreshed weekly or daily Sub-con shares Demand volatility (% of forecasted demand) Manufacturing lead times for all facilities Assumed 1-2 weeks at subcontractors Assumed 1-2 weeks at subcontractors Delivery Performance Transportation lead times Cost Parameters Manufacturing cost Manufacturing cost Inventory cost Inventory cost Transportation cost Transportation cost Selling price Selling price

25 Input Screen

26 Input Screen (Simulation Parameters)

27 Results Screen Red row: highest profit Blue row: lowest inventory cost

28 Examples Demand forecast across two quarters from end customer 1(Example 1) and end customer 2 (Example 2) Example 1 (Device Code) 10 weeks of manufacturing lead time 10 weeks of manufacturing lead time Weekly review Weekly review Two volatility scenarios (30% & 80%) Two volatility scenarios (30% & 80%) Two CMs with split Two CMs with split No transportation delay No transportation delay Example 2 (Device Code) 41 days of manufacturing lead time 41 days of manufacturing lead time Daily review Daily review 65% volatility 65% volatility Two CMs with no obvious pattern in split Two CMs with no obvious pattern in split 3 days of transportation lead time to the CM location 3 days of transportation lead time to the CM location

29 Higher profits with echelon and central warehousing policies More than 35% improvement in inventory cost under echelon policy No significant advantage of central warehousing in inventory cost Policy Comparisons Higher profits with echelon and central warehousing policies Around 50% improvement in inventory cost under echelon policy 10% to 20% improvement in inventory cost under central warehousing

30 Inventory Velocity (annual sales/average inventory) 30-50% improvement in overall inventory velocity with echelon policy FG inventory velocity increases more than 3 fold with echelon policy 15-20% improvement in overall inventory velocity with echelon policy FG inventory velocity increases around 5 fold with central warehousing

31 Inventory Velocity More sensitive to distribution method More sensitive to demand management

32 Test Bed & Sensitivity to Subcon Split Changes Optimal policies from each model are plugged in the Test Bed Test bed is used to analyze the sensitivity of the business strategies to subcon split changes The model investigates different scenarios by fluctuating subcon shares in demand

33 Impact of Split Changes on Inventory Cost EC policy is less sensitive to split changes (< 3%) Increase can be as high as 11% in IC policy

34 Conclusions Modeling allows for rapid identification and subsequent optimization of the dominant drivers for device-specific and customer-specific supply chains Both demand management and distribution policy have significant impact on the supply chain performance Demand and manufacturing profiles have dramatic effect on how models perform With high subcontractor share volatility, highest advantage is gained by moving to central warehousing With greater demand stability and subcontractor share certainty, highest advantage is gained from moving to echelon policy

35 Murat Erkoc, Ph.D., Director of CASCM Tel: Fax: ABOUT UM CASCM Focus on analytical and computational research, education and training Membership based Housed in the College of Engineering with contributions from other Colleges University of Miami IBMRyder Industrial Engineering School of Business School of Law Inter-American Sponsor Program

36 CASCM Sample Projects Joint optimization of inventory and scheduling for exchange programs in MRO operations Optimal network flow design for a 3PL Efficient contract/bid design for a logistics company Optimal replenishment policies for food and beverage items in cruse lines


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