2010 Edelman Award Presentations
INDEVAL Develops a New Operating and Settlement System Using Operations Research
Presented by: Hector Anaya, INDEVAL, Jaime Villaseñor, INDEVAL, Francisco Solis, Banco de Mexico, Miguel de Lascurain, ITAM, and Arturo Palacios, INDEVAL.
Authors: Arturo A. Palacios-Brun, Indeval, Paseo de la Reforma # 255, Col. Cuauhtémoc C.P. 06500, Mexico City, Mexico, apalaciosb@indeval.com.mx; Luis de los Santos Cayetano, Banxico, Avenida 5 de Mayo #6, Col. Centro, 06059, Mexico City, Mexico, lsantos@banxico.org.mx; Omar Romero-Hernández, ITAM, Rio Hondo # 1, Colonia Progreso Tizapán 01080 Mexico City, Mexico, oromero@itam.mx; Miguel de Lascurain, ITAM, Rio Hondo # 1, Colonia Progreso Tizapán 01080 Mexico City, Mexico, mdelasc@itam.mx; David Fernando Muñoz, ITAM, Rio Hondo # 1, Colonia Progreso Tizapán 01080 Mexico City, Mexico, davidm@itam.mx; Francisco Solís, Banxico, Avenida 5 de Mayo #6, Col. Centro, 06059, Mexico City, Mexico, fsolis@banxico.org.mx; Francisco J. Herrería, Indeval, Paseo de la Reforma # 255, Col. Cuauhtémoc C.P. 06500, Mexico City, Mexico, fherre@indeval.com.mx
Abstract: The S.D. INDEVAL Institución para el Depósito de Valores, S.A. de C.V (INDEVAL), Mexico's Central Securities Depository and Securities Settlement System, implemented a new operating system to achieve best international practices, using operations research techniques. Best practices include: high capacity and reliability, real-time settlement, Delivery versus Payment (DvP), secure data storage and communications (based on the ISO15022), and operational transparency. This paper presents the problem definition, a linear programming model and a system simulation, along with a major business process modeling devised for the new system. The novel application of operations research techniques has produced several benefits including: (i) analysis and testing of the DvP settlement mechanism that processes transactions quickly and efficiently, with optimal use of available cash and securities balances, (ii) a secure, reliable and automatic clearing and settlement engine that operates continuously and efficiently handles all transactions that INDEVAL receives from its participants, (iii) an intelligent and customized pre-settlement function that controls the execution of the clearing and settlement process using business rules and parameters. The new system settles securities operations that average over U.S. $250 billion daily, and its successful implementation is a major improvement in Mexico's financial system.
Chapter Guide:
Organization and problem: Slide #01
Approach and methodology: Slide #37
Results, impact, and conclusion: Slide #61
Delaware River Basin Commission - Breaking the Deadlock: Improving Water Release Policies on the Delaware River Through Operations Research
Presented by: Robert Tudor, Delaware River Basin Commission, James Serio, The Delaware River Foundation, and Peter Kolesar, Columbia University.
Authors: Nathaniel Gillespie, Trout Unlimited, 1300 N. 17th Street, Suite 500, Arlington, VA 22209-3801, United States of America, ngillespie@tu.org; Peter Kolesar, Columbia University, 314 Uris Hall, Columbia University, 3022 Broadway, New York, NY 10027, United States of America, pjk4@columbia.edu; James Serio, Delaware River Foundation, 538 West Main Street, Hancock, NY 13783, United States of America, jimserio@hancock.net
Abstract: The Delaware River provides half of New York City's drinking water, is a habitat for wild trout and American shad, and has suffered three 100-year floods in the last five years. The water releases from three New York City dams on the Delaware's headwaters impact the reliability of the city's water supply, the potential for floods and the quality of the aquatic habitat. This successful project aimed to revise the water release policies to benefit the fishery habitat without increasing the City's drought risk. We describe the O.R. analyses and the politics that led to the October 2007 implementation by the Delaware River Basin Commission of our optimization-based "Adaptive Release" framework. In addition to meeting the stated habitat improvement goals, our algorithm conservatively decreases reservoir levels less in dry years than in wet years, thereby offering modest increases in flood protection during the hurricane season, and is simpler to administer.
Chapter Guide:
Organization and problem: Slide #03
Approach and methodology: Slide #26
Results, impact, and conclusion: Slide #54
Deutsche Post DHL - Managing Global Brand Investments at DHL
Presented by: Lori Folts, Deutsche Post DHL, Marc Fischer, University of Passau, and Tjark Freundt, McKinsey & Company
Authors: Marc Fischer, University of Passau, Innstrasse 27, 94032 Passau, Germany, marc.fischer@uni-passau.de; Tjark Freundt, McKinsey & Company, Inc., Am Sandtorkai 77, 20457 Hamburg, Germany, tjark_freundt@mckinsey.com; Wolfgang Giehl, Deutsche Post DHL, Charles-de-Gaulle-Str. 20, 53113 Bonn, Germany, w.giehl@deutschepost.de
Abstract: In this proposal, we introduce the customer-insight-based approach that has been adopted by Deutsche Post DHL (more than 500,000 employees) to improve its global express delivery business. The O.R.-based brand assessment tool has been used in more than 20 of the largest countries in four continents since 2004. It supports local brand managers in allocating marketing resources to activities that grow the global brand in the right direction in their country market. Its application led to an estimated increase in brand value of U.S. $1.32 billion over 5 years. This corresponds to an ROI of 38% and an internal rate of return of 24%. The implementation of the tool also had major impact on DHL's strategy and organization, beyond financial success.
New Brunswick Dept. of Transportation - Taking the Politics Out of Paving: Achieving Transportation Asset Management Through O.R.
Presented by: Dale Wilson, New Brunswick DoT, Kim Mathison, New Brunswick DoT, Ugo Feunekes, Remsoft, and John MacNaughton, New Brunswick DoT.
Authors: Jay Cunningham, New Brunswick Canada Department of Transportation, PO Box 6000, Fredericton, New Brunswick, Canada, E3B5H1, jay.cunningham@gnb.ca; Andrea Feunekes, Remsoft Inc., 160-77 Westmorland Street, Fredericton, New Brunswick Canada, E3B 6Z3, andrea@remsoft.com; Ugo Feunekes, Remsoft Inc., 160-77 Westmorland Street, Fredericton, New Brunswick Canada, E3B 6Z3, ugo@remsoft.com; John MacNaughton, New Brunswick Canada Department of Transportation, PO Box 6000, Fredericton, New Brunswick, Canada, E3B5H1, john.macnaughton@gnb.ca; Kim Mathison, New Brunswick Canada Department of Transportation, PO Box 6000, Fredericton, New Brunswick, Canada, E3B5H1, kim.mathison@gnb.ca; Steve Palmer, Remsoft Inc.,160-77 Westmorland Street, Fredericton, New Brunswick Canada, E3B 6Z3, steve@remsoft.com
Abstract: The New Brunswick Department of Transportation (NBDoT) maintains over 18,000 kilometers of roads, 2,900 bridges and various ferry crossings and other assets. The organization faced significant challenges in rehabilitating its billions of dollars in infrastructure assets and maintaining a safe and effective transportation system with a very limited budget. Their goal was to develop long-term plans for managing New Brunswick's highway infrastructure that were transparent and defensible, enabling buy-in from decision makers and support from the public. The O.R. component of the framework uses a unique combination of linear programming and heuristic techniques for a goals-based approach. The model incorporates long-term objectives and constraints from an operations-wide view that weighs all options, costs, timings and asset life-cycles to produce optimal treatments plans. Results of the initial analysis offered the substantiation required to secure increased funding that helped address the growing infrastructure deficit, allowed NBDoT to maintain levels of service, and assisted the local road-building industry by stabilizing funding. NBDoT anticipates $72 million (discounted) in annual savings, amounting to $1.4 billion (discounted) over the next 20 years. The solution provides the capability to commit to long-term decisions, and has removed politics from the decision-making process because the consequences of deviating from the optimized plan can be easily quantified and communicated. Future program development capital budgets will see highway fixtures and ferries added to the model. The Department of Transportation has become a global leader in the field of asset management, and the success has attracted the attention of transportation officials around the world.
Chapter Guide:
Organization and problem: Slide #03
Approach and methodology: Slide #14
Inventory Optimization at Procter & Gamble: Achieving Real Benefits Through User Adoption of Inventory Tools
Presented by: Daniel Myers, Procter & Gamble, Glenn Wegryn, Procter & Gamble, William Tarlton, Procter & Gamble, and Sean Willems, Boston University.
Authors: Ingrid Farasyn, Procter & Gamble, Global Business Services, Product Supply Analytics, Temselaan 100, 1853 Strombeek-Bever, Belgium, farasyn.i@pg.com; Salal Humair, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02215, United States of America, shumair@hsph.harvard.edu; Joel I. Kahn, Procter & Gamble, Global Business Services, Product Supply Analytics, One Procter & Gamble Plaza, Cincinnati, Ohio 45202, United States of America, kahn.ji@pg.com; John J. Neale, Boston University, 595 Commonwealth Avenue, Boston, MA 02215, United States of America, jneale@bu.edu; Oscar Rosen, Procter & Gamble, Global Business Services, Product Supply Analytics, One Procter & Gamble Plaza, Cincinnati, Ohio 45202, United States of America, rosen.o@pg.com; John Ruark, Optiant, Inc., 7 New England Executive Park, Burlington, MA 01803, United States of America, john.ruark@optiant.com; William Tarlton, Procter & Gamble, Beauty & Grooming, Supply Chain R&D, 11050 York Road, Hunt Valley, MD 21030, United States of America, tarlton.wm@pg.com; Wim Van de Velde, Procter & Gamble, Global Business Services, Product Supply Analytics, Temselaan 100, 1853 Strombeek-Bever, Belgium, vandevelde.wm@pg.com; Glenn Wegryn, Procter & Gamble, Global Business Services, Product Supply Analytics, One Procter & Gamble Plaza, Cincinnati, Ohio 45202, United States of America, wegryn.gw@pg.com; Sean Willems, Boston University, 595 Commonwealth Avenue, Boston, MA 02215, United States of America, willems@bu.edu
Abstract: Over the past ten years, Procter & Gamble has leveraged its cross-functional organization structure with operations research to reduce inventory investment significantly. Savings were achieved in a two-step process. First, spreadsheet-based inventory models locally optimized each stage in the supply chain. Since these were the first inventory tools installed, they achieved significant savings and established P&G's scientific inventory practices. Second, P&G's more-complex supply chains implemented multi-echelon inventory optimization software to minimize inventory cost across the end-to-end supply chain. In 2009, a tightly coordinated planner-led effort, supported by these tools, drove $1.5 billion in cash savings. While case studies reveal the mathematics employed, of equal importance is the presentation of the planning process that facilitates inventory management and the decision tree that matches a business to the optimal inventory tool depending on the business' requirements. Today, more than 90% of P&G's business units (about $70 billion in revenues) utilize either single-stage (70%) or multi-echelon (30%) inventory management tools. Plans are underway to grow the use of multi-echelon tools to 65% in the next three years.
Chapter Guide:
Organization and problem: Slide #03
Approach and methodology: Slide #23
Results, impact, and conclusion: Slide #61
Sasol - Innovative Decision Support in a Petrochemical Production Environment
Presented by: Hylton Robinson, Sasol Technology, Marlize Meyer, Sasol Technology, Michele Fisher, Sasol Technology, and Willem Louw, Sasol Technology.
Authors: Gerkotze Bonthuys, Sasol Technology, Operations Profitability Improvement, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, gert.bonthuys@sasol.com; Ebert Cawood, Synfuels Secunda, Operations Profitability Improvement, North Park offices, Synfuels Road, Secunda, 2302, Mpumalanga, South Africa, ebert.cawood@sasol.com; Esmi Dreyer, Sasol Technology, Value Chain Optimisation, North Park Offices, Synfuels Road, Secunda, 2302, Mpumalanga, South Africa, esmi.dreyer@sasol.com; Michele Fisher, Sasol Technology, Value Chain Optimisation, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, michele.fisher@sasol.com; Jaco Joubert, Sasol Technology, Value Chain Optimisation, Baker Square West, 33 Baker Street, Rosebank, 2196, Gauteng, South Africa, jaco.joubert@sasol.com; Marlize Meyer, Sasol Technology, Value Chain Optimisation, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, marlize.meyer@sasol.com; Hylton Robinson, Sasol Technology, Value Chain Optimisation, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, hylton.robinson@sasol.com; Ruan Rossouw, Sasol Technology, Research and Development, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, ruan.rossouw@sasol.com; Gerrit Streicher, Sasol Technology, Value Chain Optimisation, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, gerrit.streicher@sasol.com; Hentie van den Berg, Sasol Technology, Value Chain Optimisation, North Park Offices, Synfuels Road, Secunda, 2302, Mpumalanga, South Africa, hentie.vdberg@sasol.com; Anette van der Merwe, Sasol Technology, Value Chain Optimisation, North Park Offices, Synfuels Road, Secunda, 2302, Mpumalanga, South Africa, anette.vandermerwe@sasol.com; Lorraine van Deventer, Previously employed by Sasol Technology, 63 Gaudi Way, Clarkson, WA, 6030, Australia, lorraine42226@hotmail.com; Johan Janse van Rensburg, Sasol Technology, Value Chain Optimisation, 1 Klasie Havenga str, Sasolburg, Freestate, South Africa, 1947, js.jansevanrensburg@sasol.com; Cecile Wykes, Sasol Technology, Process Design, Growth Building, Synfuels Road, Secunda, 2302, Mpumalanga, South Africa, cecile.wykes@sasol.com
Abstract: Declining fossil fuel reserves, stricter clean fuel specifications, fluctuating oil and gas prices, a recessionary world economy and unique developing world issues are some of the challenges facing Sasol, an integrated energy and chemical company based in South Africa. A passion for innovation has made the company a world leader in unique technologies including the application of operations research. A perfect example is Sasol's modeling operations using stochastic simulation (MOSS) methodology. Historically, the petrochemical industry based business decisions on average production limits. This approach ignored any time-based variability, hence requiring the addition of a design margin and more expensive production facilities. Sasol Technology's operations research team developed MOSS to address the critical need to include this key factor in decision making. The team uses MOSS models to develop business cases for gas and liquid production facility modifications, to highlight risks and to assist strategic decision making. They also analyze the impact of changing market conditions, product composition, operations efficiency, operating philosophies and schedules. These models have provided an estimated value addition for Sasol of over $230 million since 2000. Although not audited, this is considered a conservative estimate since it does not account for the improvements in energy efficiency, greenhouse gas emissions, general risk reduction and the overall understanding of Sasol's complex and integrated systems. Sasol believes that this work has applications in the wider chemical and fuels industries and represents a major innovative step forward for operations research in the chemical engineering discipline.
Chapter Guide:
Organization and problem: Slide #03
Approach and methodology: Slide #21
Results, impact, and conclusion: Slide #41
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