Today’s guest post is by Prof. Howard Weiss at the Fox School of Business, Temple University. Howard is also Director of the Fox EMBA program. You can view Howard’s syllabus by clicking here.
As the developer of POM for Windows and Excel OM, I am naturally biased about the use of software in an OM class. I believe that students should not be bogged down in the mechanics of computations but rather should understand concepts, inputs and outputs. While 90% of the homework problems in the Heizer/Render text can be solved with my two programs, I see four types of categories of problems that are strong candidates for assigning students using the software.
(1) Large problems, such as project management are good example of models with simple but tedious computations. There is no reason to ask students to solve CPM models with more than 8 activities by hand. In forecasting, I want students to understand the meaning and use of the trend and the error measures rather than spending time computing the intercept and slope. For control charts, if a student has computed results for 5 samples by hand or with Excel does it really make sense to ask the student to calculate the results by hand for 30 samples?
(2) Iterative Models, such as LP, assignment, and transportation, should focus on the formulation of the problems and the interpretation of the results.
(3) Models with multiple methods, where it is useful for students to compare the results of these different methods without having to try every method by hand themselves. Models that come to mind are time-series analysis, assembly line balancing and one-machine scheduling. In addition, it is much easier to change the number of servers in a waiting line model in POM or Excel OM than by hand.
(4) Models for which the software goes a step further than the text, such as: machine scheduling, where Moore’s method is available to minimize the number of late jobs; Wagner-Whitin for lot-sizing; LP for a ranging analysis.