ENGINEERING SYSTEMS ANALYSIS FOR DESIGN
(Previous title: Dynamic Strategic Planning)
ESD.71, 1.146, 2.192, 3.56, 13.62, 16.861, 22.821, MIT School-Wide Elective

Professor Richard de Neufville and Dr. Frank R. Field

Web site: http://msl1.mit.edu/mib/dsp/curricula.mit.edu/~dsplan

Revision: September 2001 This subject is substantially different from previous offerings with the same numbers It builds upon previous versions; namely those called "Engineering Systems Analysis" and, more recently, "Dynamic Strategic Planning." Much of the basic material is similar. However, the focus is now squarely on the systems analysis tools useful for designing and managing important technical projects operating in the inevitably risky environment. Specifically, it culminates in the presentation of the several methods of analyzing "real options." Many researchers and practitioners believe that these techniques will revolutionize the way we will develop and manage complex projects. Indeed, a number of implementations have already demonstrated gains in overall performance of 10 to 30 percent. These are significant opportunities. Organization of Syllabus The syllabus consists of 2 major blocks covering 5 interlocking topics. Part 1 covers the elements of engineering systems analysis in the context of certainty: Evaluation techniques for projects that exist more than 3 to 5 years. These feature the discounted cash flow analyses essential for any realistic assessment of significant systems. They are sophisticated versions of traditional "engineering economy." Concepts for correctly modeling technically and economically efficient performance of systems. These derive from the economic notions of production and cost functions. These theoretical functions lose important technical realities, however, and need to be replaced by technical cost models derived from a deep understanding of the engineering details of the system. Optimization over a system model anchored in a context of certainty, specifically linear and dynamic programming. Linear programming, in addition to being a powerful means to optimize systems for fixed conditions, illustrates the important concepts of sensitivity analysis, shadow prices and opportunity costs. Dynamic programming is an essential means to calculate the value of real options. Part 2 presents the techniques for analyzing systems in the context of uncertainty. These are: Decision and utility analysis. These two methods provide a coherent basis for determining the optimal value of possible choices in the design and management of a system and, thus, for determining an optimal choice. However, they do deal effectively with evaluation over time, because they do not support a way to do a discounted cash flow that properly accounts for changing patterns of risk. Real Options analysis, a integrated approach that not only properly deals appropriately with evaluation over time in risky situations but also pinpoints the value of specific design elements. It thus gives designers and managers the means to decide what kinds of flexibility to build into a system, and when to exercise these options. With sufficient data, real options analysis directly calculates the value of flexible choices. More generally, as demonstrated theoretically and by example applications, real options analysis of engineering systems requires approximate methods. Prerequisites The full course builds upon a basic knowledge of calculus and of probability. Recognizing the variety of backgrounds among the students, it presents all the more advanced material required. However, it expects that students are mathematically agile and that many students will have seen several of the methods in some context or another. The course therefore presents the more advanced mathematical treatments rapidly, focussing on the essential elements. Students should either already be familiar with spreadsheet programs, or spend extra time at the beginning of the course to become familiar with Excel©. In the short version of the course given at Cambridge University, the instructors expect the participants to be familiar with the material in Part 1. Course Materials The text for the course is Applied Systems Analysis (R. de Neufville, McGraw-Hill, 1990). Participants can get photocopied versions from the Teaching Assistant for the subject for $20. Book versions are unavailable except in the library. Prof. de Neufville is preparing a completely revised version of the text. Software for course is Treeage© (student edition) also available from the Teaching Assistant for $ 20. Students will find it convenient to have their own copy of both the software and the text, but may share with colleagues if they want. The assignments assume that each student has these materials readily available, including in the final exam. Additionally, participants can view and download copies of the pdf versions of the PowerPoint slides on the web site for the course. As the instructors will routinely improve their presentations as the course proceeds, the web versions of the slides may differ from those actually shown in class. Every effort will be made to keep the web site current up-to-date, even after the presentations. Computer Environment The course web site (at top of this file) is the primary means of distributing basic information about the course. It contains the: Syllabus and schedule of classes, Pdf versions of slides used in the lectures (see previous section), Assignments of readings and homework, Electronic versions of major homework exercises, and A variety of software that students can use in the course Students will be using Treeage© (student edition) to work on assignments. Recitations Weekly problem-solving sessions will occur at times the instructors will establish in consultation with the class. Prof. de Neufville will be available for at least half an hour after each class for immediate questions and comments. Students can also make appointments with him for personal discussions. Grading The teachers will base grades principally on written material: homework, the mid-semester quiz and a final examination. The approximate weights are: Homework: 40% Mid-semester quiz: 20% Final Examination: 45% They will modulate the final grade by an appreciation of the participant's progress throughout the semester. Those who finish strongly and demonstrate that they have, at the end, mastered the material will receive more credit for these final grades. Examples of previous mid-semester quizzes are posted on the web page, in the "Exercises" section, as Exercises 15 -- 17. These indicate the kind of questions that will appear on future mid-semester quizzes. However, note that their content may not match the current syllabus, so that future quizzes may cover different material. Absences Students should complete all assignments on time. The teaching assistant will mark down unexcused late assignments. Likewise, students should plan on being at the mid-semester quiz and the final examination. Students who have conflicts should discuss them with Prof. de Neufville at the beginning of the semester to see what arrangements might be made. No one should expect special treatment or the extra effort to write equivalent examinations and give them at alternative times. Prof. de Neufville will, of course, accept reasonable excuses (family emergencies, sickness) when presented near the event. Academic Honesty To avoid any potential confusion that might result from different expectations in other courses or establishments, please note the standards that apply in this subject. Anyone found cheating in a quiz or examination (copying from another student or using unauthorized materials, etc) will receive a zero for the event. Assignments turned in for grading are to be done individually, although the instructors expect that students will discuss the issues involved in problem sets and often learn best collectively. In practice this means that students may lead each other to the proper understanding of the material and collaborate on setting up computer runs. However, students should ultimately prepare their own reports for each assignment individually, in their own format and words. Demonstrated evidence of copying (exactly the same presentation, same wording of sentences, etc.) will result in zeros for each paper with this evidence.