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Baris Ata
Baris Ata

MANAGERIAL ECONOMICS & DECISION SCIENCES; OPERATIONS
Associate Professor of Managerial Economics & Decision Sciences

Print Overview
Baris Ata is an Associate Professor of Managerial Economics and Decision Sciences and coordinator of the school’s doctoral program in operations. He serves as Associate Editor of Manufacturing & Service Operations Management.

Ata’s research is on stochastic models of operations management, specifically the design and control of manufacturing service and telecommunications systems, and revenue management.

Ata received his PhD in Operations, Information and Technology from Stanford University. Prior to his appointment at Kellogg in 2003, he worked as an associate for McKinsey & Company in Istanbul.

Areas of Expertise
Pricing Strategies
Queuing Systems
Revenue Management
Print Vita
Education
PhD, 2003, Operations, Information, and Techonology, Stanford University, California
MS, 2002, Statistics, Stanford University, California
MS, 2001, Mathematics, Stanford University, California
MS, 2000, Business Research, Stanford University, California
MS, 1999, Engineering Economic Systems & Operations Research, Stanford University, California
BS, 1997, Industrial Engineering, Bilkent University, Ankara,Turkey

Academic Positions
Associate Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 2007-present
Program Coordinator, Kellogg School of Management, Northwestern University, 2007-present
Assistant Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 2003-2007
Associate, McKinsey&Co., 2001-2001

 
Print Research
Research Interests
Dynamic control of manufacturing systems and communication networks: heavy traffic approximations, Brownian and fluid network models, discrete-review policies, and analysis of asymptotic performance; pricing congestible resources; revenue management

Articles
Ata, Baris and Jan A. Van Mieghem. 2009. The Value of Dynamic Resource Pooling: Should a service network be integrated or Product-focused?. Management Science. 55(1): 115-131.
Ata, Baris and Wuqin Lin. 2008. Heavy Traffic Analysis of Maximum Pressure Policies for Stochastic Processing Networks with Multiple Bottlenecks. Queueing Systems: Theory and Applications. 59: 191-235.
Ata, Baris and Konstantinos E. Zachariadis. 2007. Dynamic power control in a fading downlink channel subject to an energy constraint. Queuing Systems. 55(1): 41-69.
Ata, Baris. 2006. Dynamic Control of a Multiclass Queue with Thin Arrival Streams. Operations Research. 54(5): 876-892.
Ata, Baris and Shiri Shnerson. 2006. Dynamic Control of an M/M/1 Service System with Adjustable Arrival and Service Rates. Management Science. 52(11): 1778-1791.
Ata, Baris, J. Michael Harrison and Larry A. Shepp. 2005. Drift Rate Control of a Brownian Processing System. Annals of Applied Probability. 15(2): 1145-1160.
Ata, Baris. 2005. Dynamic Power Control in a Wireless Static Channel Subject to a Quality of Service Constraint. Operations Research. 53(5): 842-851.
Ata, Baris and Sunil Kumar. 2005. Heavy Traffic Analysis of Open Processing Networks with Complete Resource Pooling: Asymptotic Optimality of Discrete Review Policies. Annals of Applied Probability. 15(1A): 331-391.
Working Papers
Rubino, Melanie and Baris Ata. Forthcoming. Dynamic Control of a Make-to-Order Parallel-Server System with Cancellations. Operations Research. Forthcoming
Akan, Mustafa, Baris Ata and Martin Lariviere. 2009. Asymmetric Information and Economies-of-Scale in Service Contracting.
Agarwal, Manish, Michael Honig and Baris Ata. 2006. Adaptive Training and Data Power Allocation for Fading Downlink Channels with Feedback.
Afeche, Philipp and Baris Ata. 2005. Revenue Management in Queueing Systems with Unknown Demand Characteristics -- working paper?.
Ata, BarisR. Canan Savaskan-Ebert and Mustafa Akan. A Pricing Model for Hybrid Manufacturing Systems with Remanufacturing.

 
Print Teaching
Teaching Interests
Operations
Full-Time / Part-Time MBA
Operations Management (OPNS-430-0)

This course counts toward the following majors:Operations.

Operations management is the management of business processes--that is, the management of the recurring activities of a firm. This course aims to familiarize students with the problems and issues confronting operations managers, and to provide the language, concepts, insights and tools to deal with these issues to gain competitive advantage through operations. We examine how different business strategies require different business processes and how different operational capabilities allow and support different strategies to gain competitive advantage. A process view of operations is used to analyze different key operational dimensions such as capacity management, cycle time management, supply chain and logistics management, and quality management. Finally, we connect to recent developments such as lean or world-class manufacturing, just-in-time operations, time-based competition and business re-engineering. Prerequisite: DECS-433 or DECS-436.

Spreadsheet Modeling for Managerial Decisions (OPNS-450-0)

This course counts toward the following majors: Analytical Consulting, Decision Sciences, Operations.

This course focuses on structuring, analyzing and solving managerial decision problems on Excel spreadsheets. We address problems of resource allocation (how to use available resources optimally), risk analysis (how to simulate the effects of uncertainty in problem parameters), decision analysis (how to analyze sequential decisions involving uncertainty), data analysis (how to synthesize the available data into useful information) and forecasting (how to extrapolate past observations into the future). In each area, we pose specific problems from operations, finance and marketing, structure them on Excel spreadsheets, and analyze and solve them using the available Excel commands, tools and add-ins. The course involves a hands-on, in-class learning experience in modeling and analyzing a variety of business decision problems on a common spreadsheet platform. It should, therefore, enhance one's problem-solving capabilities as well as spreadsheet skills. A good working knowledge of Microsoft Excel is required.

Operations Strategy (OPNS-454-0)

This course counts toward the following majors: Analytical Consulting, Operations.

In this course, students learn how operations strategy can add value by tailoring a set of core principles to a specific business setting. The course provides a framework to formulate an operations strategy and analyze, value, and optimize the key decisions involved in operations strategy. The key evaluation metric is how operations strategy impacts the net present value of the firm. The key decisions studied are choosing competitive operational competencies and benchmarking; capacity expansion, timing, flexibility and location; sourcing and contracting; risk management and operational hedging; revenue management; improvement and learning. This course builds on the core operations class. Students should also be familiar with the basics of finance, economics and strategy, as the strategic decisions studied in this course require a detailed analysis and understanding of the underlying operations. Thus this course has a greater amount of concreteness and detail than a competitive strategy class, and uses a combination of in-depth case analysis, mini-lectures, presentations and qualitative discussions of other examples. The course is intended for students interested in operations and supply chain management, general management, or management consulting.

Doctoral
Contemporary Topics in Operations Management (OPNS-520-6)
This course is designed to introduce students to contemporary research topics in the field of Operations Management. Some familiarity with statistical/empirical methods, dynamic programming, mathematical programming, stochastic processes is required.