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Project Information

Finding Teams & Projects | Topics | Analysis


How do I find a project team and project topic?

First, you should form a group of 3 or 4 people.  If you are looking for a group, you may post information to others looking for group members, or view postings of others.  Also, we will have a pizza social on Monday, April 8, to help you meet team members and discuss project ideas.  The social will be from 5:30 - 6:30 in the outdoor area by the "Nuts & Mud" cafe, in the basement of Terman.  Submit your team name and members by Wednesday, April 10.

Then, the group should develop a topic.  The responsibility for finding a topic ultimately rests with the group.  The teaching team can provide you with suggestions or advice, but do not expect them to match you with projects.  The topic may come from one of several sources:

  • your own personal contact at a company in the area
  • one of the contacts through Prof. Weyant (see Project Leads)
  • an "at a distance" project with a company of your choosing, working on a particular, well-defined strategy problem but without a real client contact
The first two sources involve working with a personal contact at a particular company.  Contact with a real world client is not required, but it will likely make your project more complete, more focused, and more rewarding.  A preliminary project description is due by April 18, but you have until the project proposal on May 2 to fully define and scope out your project.

What sort of topic is appropriate?

Projects are most easily framed by focusing on a corporate decision of strategic importance at a particular company.  By strategic decisions we mean those that will have important consequences for future products, markets, or revenues.  Projects may also analyze more general strategies or market behaviors, but they should be tightly focused on a particular issue or problem.  Examples of problems addressed by a project include:
  • large, one-time investments (e.g., market entry, new product launch)
  • optimal product positioning and development strategies
  • pricing strategy
  • Examples of past projects are also posted on this web site to give you an idea of what an appropriate topic might be.  You should base your project on a real problem encountered by a real company.  The audience for the project should be assumed to be a senior decision-maker with a quick mind but only a passing acquaintance with economics, engineering, or mathematics (e.g., a sharp CEO or Strategy/Planning Marketing Vice President).

    What kind of analysis is expected?

    The analysis should use analytical methods based on MS&E core courses and lecture topics to structure the problem and gain insights into recommended courses of action.  Some conceptual strategy ideas (like Porter's 5 forces, core capabilities) from the reading will likely be useful in framing and motivating your analysis.  Students have a great deal of flexibility in choosing which particular analysis tools they would like to apply in their project.  The marketing analysis tools of new product diffusion and conjoint analysis will be stressed in the lectures and may be relevant to your project.  The lectures will also introduce real options and game theory topics, which you may decide to incorporate into your projects.   Also, MS&E tools like decision analysis, economics, finance, and optimization are encouraged when appropriate.  Finally, don't feel limited to the tools that have been presented to you.  You are encouraged to explore and find other quantitative marketing and management science models that fit your project.  An excellent marketing reference is Marketing Engineering by Lilien (1998).  Above all, be creative, resourceful, and relevant in your choice of analysis tools.

    With so many choices, how do we choose which analysis tools to use?

    Whichever ones are relevant to your project.  There are no requirements or checklists for using particular types of analysis.  With so much flexibility, though, it will be especially important for you to develop a strong focus and framework for analysis.  Choose a small subset of the tools available to you, and focus on developing insights using them.  Given the time pressure, we would prefer you to be narrow and deep rather than shallow and broad in your analysis.  In this class, the problem comes first, and the tools are just there to support your analysis.  At least as important as your actual application of tools is how you structure and set up the problem (making simplifying assumptions; choosing a framework for analysis).  This may be different from what you are used to in most engineering courses, where the problems are just exercises in using the tools.  Here is an example of how you might approach a problem in this class:
    • Start by framing the problem and the important objectives.  Ideas from conceptual strategy will be helpful here.  Limit the scope and focus, keeping in mind you only have a little more than a month after you really get going.
    • Sketch out a value model that will relate the objective to important decision variables and uncertainties.  Decision analysis, economics, and finance each offer useful frameworks for building the model.  Make simplifying assumptions to reduce the complexity of the problem down to something you can get your arms around.  (Assumptions don't have to be haphazard -- you can use methods like sensitivity analysis for deciding which factors to keep in your model and which to throw out.)
    • Flesh out the value model with details.  Marketing models may help you with forecasting values of revenue, market share, etc.  You might see opportunities to come up with your own optimization or probability models to help you understand critical pieces.  Or you might think about downstream decisions in your project (real options), or the role of competitors (game theory).  Think about the tradeoff between added insight and added complexity to your model.
    • Now that you have a model of the problem, you can draw insights about the best course of action for the company.  What important limitations or assumptions are built into the model?  Are your recommendations robust over lots of different scenarios?  Perhaps you can think of new alternatives at this point?
    Of course, this is just an example of a process you might go through.  Some projects will be a little more fuzzy, and explicit value models may be difficult to create.  For example, some past projects have focused their analysis primarily at the conceptual strategy level, with a little support from more quantitative models like new product diffusion or game theory.  You might focus more on a general market analysis and strategy rather than a specific decision.  Still, it will be very important to try to structure and focus your problem to reduce its complexity.  Only when you can convincingly reduce the complexity of the problem will your recommendations be credible.  We do not want "laundry lists" of recommendations - we would like focused recommendations supported by convincing insights and analysis.