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Short Programs

Analytics for S&OP and Network Design [PI.195s]

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Overview  |  Learning Objectives  |  Who Should Attend  |  Program Materials  |  Topics Covered  |  Course Schedule  |  Participants' Comments  |  Instructors  |  Location  |  Updates

Overview

Analytics for Sales & Operations Planning and Supply Chain Network Design have emerged as important tools for achieving better decision making. They help managers extract intelligence from the large and growing databases created by Enterprise Resource Planning and other transactional software systems. Timely and penetrating intelligence is especially needed in today’s volatile business environment.

In this course, a wide range of predictive and optimization models for supply chain planning will be examined in the context of successful cases where they have been applied. Predictive models to be discussed include those for demand forecasting, market segmentation, managerial accounting, production transformations, transportation costing, and inventory management. Optimization models to be discussed include those for integrating purchasing, production, distribution, and inventory decisions so as to minimize the total cost of meeting demand over the coming months. These models can be extended to maximize profits by coordinating marketing and sales decisions with supply chain decisions. Network design models to be presented determine the strategic location, timing, and phasing of facility opening, closing, and other re-design decisions. Such decisions must be made, for example, when the firm seeks to enter new global markets, to adjust to changing economic conditions, or to consolidate following a merger or an acquisition.

Change management leading to new processes for exploiting analytics is essential for their successful application. A critical requirement is the creation of new business entities comprised of knowledge professionals who assist managers with overlapping responsibilities in making intelligent, integrated decisions. Business process changes that exploit analytics will be examined at several junctures during the course.

Content

Fundamentals  Fundamentals: Core concepts, understandings and tools (30%)

Latest Developments  Latest Developments: Recent advances and future trends (30%)

Industry Applications  Industry Applications: Linking theory and real-world (40%)

Delivery Methods

Fundamentals  Lecture: Delivery of material in a lecture format (50%)

Latest Developments  Discussion: Participatory learning (20%)

Industry Applications  Computer Exercises : Hands-on, data-driven modeling exercises (30%)

Level

Fundamentals  Introductory: Appropriate for a general audience (35%)

Latest Developments  Specialized: Assumes experience in practice area or field (65%)

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Learning Objectives

  • Understand how predictive and optimization models can be used to support S&OP and network design decision making.
  • Appreciate the overlap between S&OP and network design planning problems and models for analyzing them.
  • Comprehend the complementary roles of supply chain, marketing science, and corporate financial models in analyzing decisions that maximize a firm’s net profit.
  • Examine guidelines for creating and using models including: model selection; data collection, preparation, and validation; scenario planning; and organizational process change.
  • Acquire insights from case studies where supply chain models were successfully applied to S&OP and network design problems.
  • Learn how to create and apply data-driven models for analyzing S&OP and network design problems.
  • Gain knowledge of off-the-shelf software systems for demand forecasting, inventory management, S&OP, and supply chain network design.
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Who Should Attend

This program is intended for:

  • Managers and analysts responsible for S&OP and/or network design decision-making
  • Managers and analysts responsible for acquiring or developing and applying data-driven modeling systems to support S&OP and/or network design decision-making
  • Consultants who direct or participate in S&OP and/or network design studies
  • Academics who teach supply chain subjects to students in management and engineering

Participants will not need advanced analytical skills to fully absorb material presented in the program.

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Program Materials

At the start of the program, participants will receive a CD containing a wide range of recently published and unpublished papers as well as copies of the lecture session slides.

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Topics Covered

  • Demand forecasting and optimization models to support S&OP and network design
  • Overview of supply chain network optimization models
  • Using analytics to extract intelligence from large transactional databases
  • Business process changes for exploiting analytics
  • Optimal positioning of the inventory push-pull boundary
  • Net profit maximization using revenue models that are price and location sensitive
  • Flowcasting the retail supply chain
  • Integration of supply chain and marketing plans in consumer products companies
  • Incorporation of global supply chain issues in network design models
  • Network design for new products
  • Analytics for evaluating postponement strategies
  • Analysis of supply chain risks
  • Integration of inventory deployment with facility location decisions
  • Analytics for multi-echelon inventory optimization
  • Network design for green supply chains
  • Extension of supply chain optimization to enterprise optimization
  • Explanation of the synergy between business intelligence systems and modeling systems
  • Using spreadsheet models for demand forecasting and optimization
  • Case study: Applying an S&OP modeling system in a manufacturing and distribution company
  • Case study: Improving inventory metrics and expanding the supply chain network in a retailing company
  • Case study: Locating DC’s in an electronics distribution company
  • Case study: Consolidating the supply chain network in a food products company following a merger
  • Case study: Worldwide sourcing in an industrial chemicals company
  • Case study: S&OP for products with short life cycles
  • Case study: Postponement planning in a computer manufacturer
  • Case study: Implementing an inventory optimization system in a consumer products manufacturing company
  • Case study: Optimizing physical and financial supply chains in a multinational pharmaceutical company
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Course schedule and registration times

View 2012 Course Schedule

Class runs 9:00 am - 5:00 pm on Monday, 8:30 am - 5:00 pm Tuesday - Thursday, and
8:30 am - 4:30 pm on Friday.

Registration is on Monday morning from 8:00 - 8:30 am.

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Participants' Comments

Steven Frumkin, Professor, Philadelphia University
"Each [lecturer] has expertise in the specific area of the lecture. Each reinforced the previous lecturer's topics yet delved into other areas of importance."

Emanuele Luison, Supply Chain and Production Planning Manager, Safilo Eyewear Industries
"I understood that there are a lot of scientific approach in progress for the operation issues and the course stimulated me to resume this kind of approach in my daily activities."

Silvia Virviescas, Master Planner SCM, Industria de alimentos Zenu
"It was a good academic and personal experience."

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Instructors

The five-day course will be presented by Jeremy F. Shapiro, Professor of Operations Research and Management, Emeritus, at the Sloan School, MIT. He will be joined by: Rodrigo Cambiaghi, CEO of Axia Value Chain, North America; Matt Davis, Supply Chain Research Director at Gartner; Larry Lapide, Research Affiliate, MIT Center for Transportation and Logistics; Andre Martin, CEO of Factory2Shelf; and Sean Williams, Associate Professor in the Graduate School of Business, Boston University.

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Location

This course takes place on the MIT campus in Cambridge, Massachusetts. We can also offer this course for groups of employees at your location. Please contact the Short Programs office for further details.

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Updates

There are no updates at this time.

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