1. 1 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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 paulog@mit.edu

2. 2 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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

3. 3 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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

4. 4 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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?

5. 5 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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

6. 6 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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)

7. 7 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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.

8. 8 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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

9. 9 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. A microeconomics perspective Double Marginalization 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

10. 10 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001. 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

11. 11 Albany-MIT Ph.D. Colloquium, MIT System Dynamics Group, April 20 2001.