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The Role of Governance in Supply Chains Paulo Gonçalves MIT System Dynamics Group 30 Wadsworth St., E53-358A Cambridge, MA 02142 Phone 617-258-5585 [email protected] Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 1 Motivation • Intel faces enormous challenges in managing its supply chain – Must produce the right products at the right time in the right amount – In environment of rapid growth, increasingly complex technology, short product life-cycles, long manufacturing cycle times and high demand variability • At the same time, Dell the supply chain leader can require – Just-in-time delivery, short windows for order changes or cancellations (and no penalties) – High supplier flexibility in product customization Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 2 The problem • Traditionally strong supply chain players have used their leadership position to own advantage • Self-interested actions can increase own benefits at the expense of other players – Manufacturers would like to ensure a steady flow of orders and maximize volume purchases – Retailers would like to minimize inventory holding and obsolescence costs, maintaining quality level • Locally rational behavior can lead to inefficiencies Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 3 Research Questions • Does it always make sense to act in a narrowly conceived self-interested way to try to maximize profits in a supply chain? • Under what conditions does cooperation and risk sharing among supply chain players make sense? • What cooperative policies in a supply chain are most appropriate to improve firms’ performance? Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 4 Purpose and Goals • To develop a system dynamics model addressing the issue of governance in a real supply chain that incorporates several features of real supply chains often not considered in models in other literatures, including: – Explicit behavior rules, instead of myopic and intertemporal optimization – Inventory shortages and capacity constraints – Double ordering dynamics and lost sales dynamics – Locally available and distorted information • To develop a set of policies to improve system performance Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 5 Relevant Literature • System dynamics – Beer game dynamics (Forrester) – Experimental research (Sterman, Diehl & Sterman, Croson) • Microeconomics – Industrial Organization (Spencer, Williamson, Hart) – Game theory, incentives and contracts (Tirole) • Operations management – Multi-echelon inventory management (Clark &Scarf, – Supply chain management (Lee at al.,Cachon & Lariviere) Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 6 Dynamic Hypothesis • Narrowly conceived decisions, which are locally beneficial and boundedly rational, aimed at maximizing firm performance may, in a highly complex system, generate unanticipated side effects that are not in the best interest of the firm. Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 7 The Approach • Develop small concept models for comparative purposes providing – Deep understanding of limitations and assumptions of exiting models in other literatures – Basis for integrated model and realistic conditions • Test integrated model in one or two case studies – PC Industry: Intel - Dell – Consumer goods industry: P&G - Walmart Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 8 A microeconomics perspective Double Marginalization Total Profits Manufacturer Profits Manufacturer Costs + + + + Retailer Profits + - + Switch Centralized Chain Manufacturer Revenues + Retailer Costs Retailer Revenues + + + Production Wholesale Cost + Price Wholesale Payment + <Reference Price> Production + Manufacturer + Shipments to Retailer + Retail Price Retailer Sales+ Reference Price Market + Demand + + Retailer Orders • • • <Wholesale Price> Total Demand Focus on the financials, complete neglecting the physics Feedback poor, no dynamics, stationary demand Unlimited capacity, no delays, perfect information (price and demand), fully rational behavior, single period maximization Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 9 An Operations Management Perspective • Relaxing old assumptions makes models more realistic, still very complicated. Approach allows: – Decentralized control – Multiple decision makers – Locally rational behavior • Leading to inefficiencies dealt with contractual arrangements to improve system performance – – – – – Specifying decision rights: RPM, Quantity fixing Pricing schemes, minimum purchase Quantity flexibility, buy-backs Allocation policies, lead times Quality Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 10 Market Share + Firm's Share Total Demand Desired Backlog Total Attractiveness + + Expected Delivery Delay + Backlog Adjustment + Time to Adjust Backlog + - + Competitors Attractiveness Table Eff DD Table for Attractiveness Attractiveness + - Delivery Delay + - Reference Fraction of Orders Filled + Backlog Target Delivery Delay Firm Demand - Desired Shipment Rate + Work In Process Production + Start Rate Available Capacity B2 + Completion Rate Inventory Table for Capacity Utilization Inventory Control + <Desired Shipment Rate> + Maximum Shipment Rate Manufacturing Time Desired Production + Start Rate Inventory Adjustment Time + Shipments + B1 Capacity Utilization + Time to Perceive Fraction Order Fulfillment + - Perceived Fraction of Orders Filled Order Fulfillment Rate Minimum Order Processing Time Desired Inventory Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 11