Syllabus

Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Recitations: 1 session / week, 1 hour / session

This MIT OpenCourseWare site is based on the materials from Professor de Neufville's ESD.71 Web site. Additional materials, updated as needed by Professor de Neufville, can be found there.

Important Notes

• This course emphasizes the development of "application portfolios". These assignments show how the course material applies to each student's own professional interests (see the assignments section). Students have routinely incorporated these applications in their research, thesis, and professional presentations.
• The subject assumes that participants are competent in the material covered by ESD.70J, the 3-unit micro-subject that covers Excel spreadsheet analyses. Go to that site for a self-assessment of whether you need to audit that subject (experience indicates you probably do).

Organization of Subject

This subject focuses on the flexible design of engineering systems. It recognizes that the future is necessarily uncertain, and that we need to deliver good value for the range of possible scenarios. Flexible designs enable system operators to adapt their project to future circumstances, to avoid downside risks and to take advantage of upside opportunities.

Many researchers and practitioners believe that flexible design will revolutionize the way we develop and manage complex projects. Indeed, case studies indicate that the approach can improve expected performance by around 25 percent. These are significant opportunities.

The course shows how design flexibility can substantially increase the expected value of a system. It presents an integrated approach that

• properly deals with evaluation over time in risky situations, and
• pinpoints the value of specific design elements.

The course consists of 3 major blocks.

Basics: Recognition of Uncertainty, Valuation Fundamentals, and Timing Issues

This introductory block establishes three fundamental issues and provides the economic motivation for flexibility in design:

• Recognition of Uncertainty is the crucial starting point. The understanding that the future is uncertain and that we must design our systems to operate in many possible scenarios provides the motivation for making our systems adaptable, for building flexibility into them.
• Valuation Fundamentals covers the main analytic and conceptual issues associated with the valuation long-term projects. Here, the primary concern is with the relative value of the projects over time.
• Timing Issues discusses the design issues — principally economies of scale and learning curves — that affect the tradeoff between building larger projects initially versus developing systems incrementally over time.

Uncertainty Modeling and Flexibility Valuation Methods

This is the core analytic section of the course. It presents Decision Analysis and Lattice Analysis as the two means to assess the value of flexibility in design. Both provide ways to think through the many ways in which scenarios will occur over time, and correspondingly how system developers can react effectively to these alternate futures. Decision Analysis makes is possible to look at more complex futures, while Lattice Analysis is computationally much more efficient. Analysts need to understand the relative merits of each approach and which to use when, either singly or in combination.

This section builds upon the Monte Carlo simulation methods presented in the Excel mini-course (ESD.70J) given at the start of the semester.

Flexibility Identification Methods "in" Systems

This section explores the question of how designers can identify the parts of the system that should be flexible. The issue is that any significant system could be flexible in many, many different ways and it is important to identify which elements might most effectively contribute to increasing the expected value of the overall system. This is a primary area of current research, and the course will showcase current and recent doctoral research and other projects at the forefront of the field.

Prerequisites

This subject builds upon a basic knowledge of calculus and probability.

Students should be proficient in the use of spreadsheet programs at the level covered by ESD.70J, the 3-unit intensive short course designed to bring them up to speed in Excel. In general, everyone will benefit from participating in this offering.

Course Materials

The primary text for the class consists of draft chapters from the new text being written for the MIT Press. Prof. de Neufville will distribute these electronically throughout the semester.

This material is supplemented by chapters from:

de Neufville, Richard. Applied Systems Analysis. New York, NY: McGraw-Hill, 1990. ISBN: 9780070163720.

Extensive references and papers are available from the course Web site.

All students will be expected to have an up-to-date full version of Excel. They may also want to try the following optional add-ins:

TreeAge Pro can be downloaded for a 21-day trial from: TreeAge Pro Trial Version Download, and student licenses can be obtained from: The TreeAge Software Store.

Crystal Ball information is available here: Oracle Crystal Ball Classroom Edition.

Participants can view and download PDF copies of the PowerPoint slides on the course Web site. As the instructors routinely improve their presentations as the class proceeds, the Web versions of the slides change from time to time. Students may wish to verify that they have the latest version before downloading the slides for reference in class.

Recitations

There will be regular weekly problem-solving sessions. Prof. de Neufville will schedule these in consultation with the class during the opening session.

Assignments

The graded assignments for the class mainly involve the "application portfolio". This is a collection of applications, on topics individually selected by each student, using the methods presented in class on an issue. This has two phases:

• Individual assignments throughout the semester.
• A final portfolio that builds upon the individual assignments and the feedback during the semester. It will present an integrated whole so that each student will each have a completed case study demonstrating how they can use design flexibility to increase the expected value of their systems.

Ungraded problems drawn from the Applied Systems Analysis text are distributed throughout the semester. Students are advised to complete them as a way of insuring that they know how to complete the applications — and pass the tests! Solutions to these problems will be posted so that students can grade themselves and get immediate feedback.

Grading

Grades depend principally on the application portfolio and tests, but include an allowance for class participation. The approximate weights are:

Students should complete assignments on time. The teaching assistant will mark down unexcused late assignments.

The instructors will modulate the final grade in 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 the final grades.

Previous quizzes and exams are posted in the "Exercises" section of the Web page. They indicate the kind of questions likely to appear on future exams. However, their content may not match the current syllabus, which is evolving along with research advances.

Academic Honesty

To avoid confusion that might result from different expectations in other contexts or establishments, please note the standards that apply in this subject:

• Assignments turned in for grading must be done individually. The instructors understand that students will discuss the course and often learn best collectively. However, students should prepare their 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.
• Anyone found cheating in an examination (copying from another student or using unauthorized materials, etc.) will receive a zero for the event.
• Material copied from other sources (articles, reports, Web pages, etc) must be properly cited. Evidence that material has been taken from elsewhere without citation will be treated as plagiarism.
• Prof. de Neufville will place a note in the student record of each person associated with plagiarism or cheating. MIT views these infractions seriously and routinely expels students who seriously violate our academic standards.

Any questions about this policy should be addressed to the instructors.