Supply Chain Management; Capacity and Inventory Planning; Electricity Markets; Healthcare Analytics.
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1 ALEX ANGELUS Mays Business School Wehner Building Texas A&M University 4113 TAMU 210 Olsen Blvd College Station, Texas RESEARCH INTERESTS Supply Chain Management; Capacity and Inventory Planning; Electricity Markets; Healthcare Analytics. EDUCATION 1997 Ph.D. in Operations, Information and Technology, Graduate School of Business, Stanford University, California B.Sc. in Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts PROFESSIONAL EXPERIENCE 2017 present Assistant Professor of Operations Management, The Mays Business School, Texas A&M University Visiting Assistant Professor of Operations Management, Jindal School of Management, University of Texas at Dallas Associate Professor of Operations Management, Lee Kong Chian School of Business, Singapore Management University Lecturer, Operations Management Department, Haas School of Business, University of California at Berkeley Adjunct Professor, Graduate Business School, St. Mary s University Consultant, Senior Consultant, Engagement Manager; Strategic Decisions Group, Palo Alto, California REFEREED ARTICLES PUBLISHED J7. Looking Upstream: Optimal Policies for a Class of Capacitated Multi-Stage Inventory Systems, (with W. Zhu), Production and Operations Management, Vol. 26, pp , J6. Knowledge You Can Act On: Optimal Policies for Assembly Systems with Expediting and Advance Demand Information, (with Ö. Özer), Operations Research, Vol. 64, pp ,
2 J5. On the Structure of Capacitated Assembly Systems, (with W. Zhu), Operations Research Letters, Vol. 41, pp , J4. A Multiechelon Inventory Problem with Secondary Market Sales, Management Science, Vol. 57, pp , J3. An Asset Assembly Problem, (with E. Porteus), Operations Research, Vol. 56, pp , J2. Simultaneous Capacity and Production Management of Short-Life-Cycle, Produceto-Stock Goods under Stochastic Demand, (with E. Porteus), Management Science, Vol. 48, pp , J1. Opportunities for Improved Statistical Process Control, (with E. Porteus) Management Science, Vol. 43, pp ARTICLES A2. Electricity Price Forecasting in Deregulated Markets, The Electricity Journal, April A1. On the Valuation of Electricity Generation Assets with Spark Spread Options. White Paper, Strategic Decision Group, March HONORS AND RECOGNITIONS 2012 Best Professor in Operations Management 3rd Asia s Best B-School Awards 2012 Dean s Teaching Honor List, Lee Kong Chian School of Business 2011 Dean s Teaching Honor List, Lee Kong Chian School of Business 2009 Dean s Teaching Honor List, Lee Kong Chian School of Business 2009 Operations Research, Meritorious Service Award FUNDED RESEARCH National Science Foundation, EAGER Grant. Title: An Exploratory Approach for Managing Multiple Flows in Serial Supply Systems August 1, 2016 ($200,503) (Co-PI: Ö. Özer, Co-PI: Alex Angelus), Awd # INVITED TALKS AT SEMINAR Mays Business School, Texas A&M University, College Station, TX (December 2017) Chinese University of Hong Kong, Hong Kong (February 2014) University of Minnesota, Minneapolis, MN (October 2010) Eindhoven Technological University, Eindhoven, Netherlands, (September 2010) City University, Hong Kong (February 2010) Fuqua School of Business, Duke University, Durham, NC (November 2009) University of Texas at Dallas Business School, Dallas, TX (November 2009) 2
3 Haas School of Business, University of California, Berkeley, CA (October 2009) Universidad Pompeu Fabra, Barcelona, Spain (May 2009) Hong Kong University of Science and Technology, Hong Kong (April 2008) Chinese University of Hong Kong, Hong Kong (April 2008) Hong Kong Polytechnic University (April 2008) INVITED CONFERENCE TALKS Looking Upstream: Optimal Policies for a Class of Capacitated Multi-stage Inventory Systems, INFORMS Conference, Houston, TX. (November 2017) Optimal Control and Value of Reverse Logistics in Supply Chains with Multiple Flows of Product, INFORMS Conference, Houston, TX. (November 2017) Distributed Renewable-energy Generation and Implications for Strategic Consumer Behavior, Electricity Pricing and Installed Capacity, INFORMS Conference, Nashville, TN. (November 2016) Uncovering the Hidden Value of Reverse Logistics with Complementary Product Flows in a Supply Chain, International INFORMS, Hawaii, (June, 2016) On Managing the Supply-Demand Mismatch with Complementary Product Flow Options, INFORMS Conference, Philadelphia, PA. (November 2015) On Managing the Supply-Demand Mismatch with Complementary Product Flow Options, MSOM Conference, Toronto, Canada. (June 2015) Knowledge You Can Act On: Optimal Policies for Assembly Systems with Expediting and Advance Demand Information, POMS Conference, Washington, D.C. (May 2015) Knowledge You Can Act On: Optimal Policies for Assembly Systems with Expediting and Advance Demand Information, MSOM Conference, Seattle, WA (June 2014) Optimal and Heuristic Policies for an Assembly System with Secondary Market Sales, INFORMS Conference, Charlotte, NC (October 2011) Optimal and Heuristic Policies for an Assembly System with Secondary Market Sales, MSOM Conference, Ann Arbor, MI (June 2011) A Capacitated Assembly Problem, INFORMS Conference, Austin, TX (Nov. 2010) A Multiechelon Inventory Problem with Secondary Market Sales, MSOM Conference, Haifa, Israel (June 2010) Managing Capacitated Multiechelon systems with Domain-Optimal Policies, INFORMS Conference, San Diego, CA (October 2009) Managing Capacitated Multiechelon systems with Domain-Optimal Policies, EURO Conference, Bonn, Germany (July 2009) Managing Capacitated Multiechelon systems with Domain-Optimal Policies, MSOM Conference, Cambridge, MA (June 2009) To Assemble or Not to Assemble, INFORMS, Seattle, WA (Nov. 2007) 3
4 PROFESSIONAL ACTIVITIES Referee for Journals: Management Science, Operations Research, Manufacturing & Service Operations Management, Production and Operations Management. University Service and Activities: MBA Admissions Committee, Singapore Management University Faculty Hiring Committee, Singapore Management University Course Coordinator for the undergraduate Management Science course, Singapore Management University. Professional Memberships: INFORMS, MSOM TEACHING EXPERIENCE The University of Texas at Dallas (semester, course title, overall rating, 5 high - 1 low scale): Fall 2016 OPRE 6398 Prescriptive Analytics 4.50 Summer 2016 OPRE 6398 Prescriptive Analytics 5.00 Spring 2016 OPRE 6398 Prescriptive Analytics 4.38 Fall 2015 OPRE 6398 Prescriptive Analytics 4.25 Spring 2015 OPRE 6398 Prescriptive Analytics 4.36 Fall 2014 OPRE 6301 Quant. Intro. to Risk and Uncertainty in Business 4.05 Singapore Management University (semester, course title, course type): Spring 2013 Operations Management MBA Core Course Fall 2012 Business Analytics MBA Elective Spring 2012 Operations Management MBA Core Course Fall 2011 Supply Chain Management MBA Elective Spring 2011 Operations Management MBA Core Course Fall 2010 Supply Chain Management MBA Elective Spring 2010 Management Science Undergraduate Fall 2009 Supply Chain Management Undergraduate Spring 2009 Management Science Undergraduate Fall 2008 Supply Chain Management Undergraduate Haas School of Business, UC Berkeley (semester, course title, course type): Spring 2007 Supply Chain Management MBA Elective Spring 2007 Operations Management MBA Core Course Fall 2006 Supply Chain Management MBA Elective 4
5 Fall 2006 Operations Management MBA Core Course Spring 2006 Supply Chain Management MBA Elective Spring 2006 Operations Management MBA Core Course Fall 2005 Supply Chain Management MBA Elective Fall 2005 Operations Management MBA Core Course SELECTED INDUSTRY EXPERIENCE Supply Chain Optimization S5. For a large soft goods distributor, used Big Data analytics to evaluate long term profitability of each product carried, as well as excess inventories in the supply chain. Replaced traditional product replenishment policies with new ones, analytically deduced from demand variability, inventory holding costs, and unit margins. The new inventory policies increased inventory turns by 76%. S4. For a large Japanese retailer, assessed the value of a middle-man company in its apparel supply chain. Conducted a quantitative analysis that established that, contrary to the prevailing wisdom, the middle-man company was creating value in the supply chain due to its taking on inventory risk in the form of buying back excess inventory. S3. For an apparel company, redesigned their complex and overly costly supply chain strategy, which had historically involved both in-house manufacturing and traditional arms-length sourcing arrangements. Used a variety of analytical models to evaluate a hybrid manufacturing approach based on sourcing relationship that combined some of the virtues of vertical integration with the flexibility of sourcing. S2. For an Asian electronics component manufacturer, formulated a novel analytical approach to assess the value of developing a secondary market for selling off excess stock in the supply chain. Based on the approach, the secondary market for this supply chain was estimated to reduce total supply chain costs by as much as 5%. S1. For a Japanese apparel company, used business analytics and data-based models to quantify advantages of a quick response approach to market. Helped implement the quick response approach redesigned business processes to achieve better product planning and development, and more efficient production and marketing. Number of inventory turns increased by 45%, while the gross margins improved by 12%. Inventory Management I3. For a large consumer goods manufacturer, implemented the lowest-cost-provider strategy by initiating SKU rationalization, improving inventory management, and creating more efficient production schedules. Introduced the notion of a moving bottleneck to the client, and redesigned policies to insure adequate WIP supply to the bottleneck. 5
6 I2. For a US-based electronic components company, helped introduce buffers for storing work-in-process inventory along the conveyor belt. Optimized buffer size at key locations along the conveyor in order to mitigate the impact of machine breakdown, without creating excess inventory. I1. For an Asian wholesaler of pharmaceutical products, strategically reduced the number of products carried, and redesigned the inventory replenishment policies to take advantage of risk-pooling inherent in supplying identical products to multiple pharmacies. As a result, total inventory of products carried was reduced by an average of 20%. Capacity Planning and Investment C3. For a major US railroad, helped create a company-wide capacity investment strategy. We developed a methodology for assessing rail traffic flows over congested nodes that allowed the company for the first time to plan long-term capacity investments into trains and rail lines on the business-unit level. C2. For a California-based power-generation company, developed quantitative methods and supporting software tools to manage pipeline of orders for gas turbines. We formulated an innovative approach to valuing deferrals and cancellations of initiated orders for the turbines. Savings thus created for the company estimated at $40M. C1. For a Fortune 100 chemical company, designed and executed a system to determine the optimal size and timing of capacity expansion. This method used financial data, historical price and volume data, as well as future price and demand forecasts to fundamentally alter capacity investment strategy for the company. Price and Demand Forecasting P3. For a major US chemical company, developed time-series statistical models to construct short-term and long-term price and volatility forecasts for input chemicals traded through bilateral contracts. The forecasts were used to rebalance forward contracts position, and develop new hedging strategies for the company. P2. For a Middle East agricultural company, developed short-term price and volatility contracts for the basic food commodities bought and sold by the company. These forecasts were used to set up a trading desk for the first time in the company s history. Profits from the first year of trading were in excess of US$5M. P1. For a US-based power-generation company, developed a fundamental model to forecast future long-term prices of electricity, based on the balance of supply and demand in the region. The model was based on the representation of the regional electricity market as a network of demand and supply nodes, with incorporate planned capacity additions and stochastically growing demand for electricity. 6
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