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Submitted to the Policy Subcommittee of the Task Force:
February, 1996
Since the abolition of accreditation requirements for OR/MS materials in business school curricula, the field has seen a dimunition of its role in the education of future managers. A national survey of OR/MS teachers and structured interviews with administrators of the top MBA programs in the US both confirmed this fact. The causes are multiple, but prominent among them is a mismatch between traditional OR/MS course topics and the skills demanded by employers. Some faculty members are already beginning to respond in ways that mesh with the views of MBA administrators. We recommend that individual faculty embed their analytical material strongly in a business context, use spreadsheets as a delivery vehicle for OR/MS algorithms, stress the development of general modeling skills, and work toward effective collaboration with colleagues in the functional areas of business. We also recommend that INFORMS sponsor development of teaching materials in OR/MS, especially case studies with analytical content, and that it foster communication and networking among members who teach in business schools.
In July 1994, the Presidents of ORSA and TIMS, Dick Larson and Gary Lilien, chartered the INFORMS Business School Education Task Force. The Task Force was established in response to a sense that OR/MS was becoming less influential in the education of the next generation of business leaders: "OR/MS, as originally conceived and defined, should play a major role in the training we give the managers of the future. Yet programs all across the country are decreasing their OR/MS offerings and downsizing their faculty in the area."
These negative developments followed radical changes made in April 1991 to the AACSB accreditation standards for business school curricula. Approximately 250 of the 800 MBA programs in the US are AACSB accredited. That subset of 250 is highly influential and sets benchmarks for the remaining programs. Previously, OR/MS had a protected position as part of a "common body of knowledge" that every MBA program had to provide. Afterwards, schools were free to define their own, individual missions and organize curricula solely around that mission; there was no specific requirement that OR/MS be included in any way.
The period after the change in accreditation standard was one of retrenchment for OR/MS. In January 1994, Kathleen Hilbert and Gary Lilien released an influential report, "The MS/OR Business School Crisis", which summarized a telephone survey of 21 US business schools. They concluded: "There is general agreement among MS/OR academics that the role of the MS/OR programs has declined and that it plays only a small part in business programs today."
Against this background, the charge given to the Task Force was twofold: "1. Develop recommended actions for individual OR/MS academics to enhance their role/value in business school education. 2. Develop recommended actions for INFORMS leadership to help enhance the role that OR/MS plays in business school education." The Task Force was organized into two subcommittees: an Operating subcommittee to develop information on the nature and extent of the problem and the desirability of plausible responses, and a Policy subcommittee to make recommendation to the INFORMS board. This document is the final report of the Operating subcommittee.
The Operating subcommittee conducted two major data gathering operations. With the cooperation of the INFORMS administrative office and Duxbury Press, it mailed a survey to 2,200 university teachers of OR/MS. The goals of the survey were to document impressions of the extent of the problem, the causes of the problem, and the viability of possible responses. The subcommittee also conducted structured telephone interviews with program administrators at 21 of the leading MBA programs in the US. These interviews documented perceived needs for quantitative competence in MBA graduates, the curricular mechanisms now in use to supply that competence, and the attractiveness of possible INFORMS initiatives. Sections 2 and 3 below summarize the findings of the mail and telephone surveys, respectively. Sections 4 and 5 present findings and recommendations to the Policy subcommittee, respectively. Appendices containing detailed responses to both surveys are included so that the many perceptive (and sometimes poignant) comments received by the subcommittee will not be lost. These voices are worth hearing, and we recommend that any reader sample these comments to get a feel for the sentiments surrounding these issues.
We worked with Duxbury Press to create, mail, process and analyze a survey instrument aimed at professors who teach OR/MS in business schools. Duxbury developed a list of 2,200 such faculty from the INFORMS membership list and the records of their own sales force.
The survey was mailed on March 15, 1995, and 306 usable returns were received through May 16, 1995. The response rate was 14%. Although this is a respectable response for a mailed survey, the 86% nonresponse rate leaves open the possibility that the respondents' opinions were biased relative to the larger group. Respondents were likely to have a higher than average concern for teaching issues or to be teaching at a school where retrenchment is serious.
The 306 respondents represented a wide range of schools, from small, teaching-oriented colleges to large research universities. The median respondent had taught OR/MS about 15 times in his/her career. About 27% reported teaching undergraduates only, 20% reported teaching MBAs only, 51% taught both, and 2% taught neither (presumably, they taught other MS and Ph.D. students). The median numbers of students taught per year per respondent were about 100 for those teaching undergraduates and about 75 for those teaching MBAs.
The survey asked for information on the following topics:
This section reports the questions and distributions of
responses. Percentages may not sum to 100% due to rounding and
because multiple responses were allowed for some questions. The
percentages apply only to those respondents answering the
questions; for the most part, the number of respondents not
answering any question was at most a few percent of the total of
306.
1. What is the role of MS/OR in your undergraduate program today?
2. What is the role of MS/OR in your MBA program today?
3. How does the role of MS/OR in your undergraduate or MBA program compare to the program 5 years ago?
4. Relative to today, what is your best guess about the role of MS/OR 5 years from now?
5. Which of the following "fixes" have the highest potential to strengthen the role of MS/OR in your particular school of business?
6. What are the principal teaching problems or student learning problems that exist in offering your course?
7. What changes are you planning to make in your MS/OR course in the near future?
8. What is the role of the computer in your course?
9. What are the important criteria you use to evaluate textbooks?
10. What supporting materials to your text do you use or would view to be important to your course?
11. What actions/activities might INFORMS undertake to improve the status of MS/OR in schools of business? (See Appendix A for suggestions received.)
The sense that OR/MS is in trouble in business schools is widespread. About half the respondents characterized the role or OR/MS in both undergraduate and MBA programs as "small"; fewer than 10% described it as "large". Furthermore, only 13% felt the role is greater now than five years ago. Looking five years ahead, only 21% expect the role to be greater five years in the future.
Of the list of possible fixes, only two were commended by a majority of respondents: "More use of cases and real world examples" (60%) and "More emphasis on modeling skills and numeracy and less on algorithms" (53%). Both represent a departure from the traditional algorithm-centered course.
Of the list of possible sources of difficulty in teaching, there was strong agreement on the primacy of problems with the mental state of the students: "Math background of students or fear of mathematics" (77%) and "Student motivation or students not recognizing the importance of MS/OR" (76%). The latter is a problem that should be ameliorated by the two fixes cited most frequently above. Improving students' math background was frequently cited (49%) as a possible fix, but may be beyond the immediate control of the OR/MS faculty.
Of the list of possible course changes, the only one cited by a majority of respondents was "More emphasis on modeling and less on the teaching of algorithms" (55%). Again there is consistency among the primary sources of difficulty, the preference for responses, and the intended response. Also consistent are the intentions to use computers more (43%), increase the use of spreadsheets (37%) and do more case analysis (34%) and projects (30%). All these moves will have the effect of changing the style and content of the OR/MS course.
The computer already plays some role in the teaching of 95% of the respondents. The modal role (31%) is to "use spreadsheets to model and solve homework assignments".
It is noteworthy that, while 60% of respondents listed greater use of cases as a promising fix at their school, only about half that number are planning greater use of cases in their classes. Among the list of possible supplements to textbooks, the greatest agreement (65%) was on the importance of case studies. This suggests that the large gap between recognizing the importance of cases and plans to actually teach them can be traced to the dearth of OR/MS cases in current teaching materials.
We designed a telephone survey to elicit the observations and opinions of officials responsible for MBA programs at the leading US business schools. These officials were generally associate or assistant deans. We solicited their views because they are knowledgeable and influential in the system INFORMS wants to influence.
We targeted schools listed in the "top 20" of either the U.S. News and World Report or Business Week 1995 rankings of MBA programs. These schools are powerful models for the majority of business schools in the US, so successful initiatives in OR/MS education in these schools would probably see rapid imitation. We conducted the interviews between December 1995 and February 1996. Of the 21 schools on this combined list, we received responses from 21.
We conducted structured telephone interviews using the instrument shown in section 3.2. We asked questions in three areas: the need for quantitative competence among MBAs, curricula to develop this competence, and the potential helpfulness of several proposed INFORMS initiatives.
The detailed responses of the deans are listed in Appendix B. In this section, we list the questions we asked and give summarized the responses.
Needs: How does your school view the need for "quantitative competence" in its graduates?
a) What particular sets of quantitative skills are in greatest demand from employers of your graduates?
Interpretation of responses: Demand for particular "hard" OR/MS skills is very low. Where technique is needed, it involves statistics more than OR/MS. There is demand for general skill in model formulation and interpretation and in quantitative reasoning.
b) What level of competence is appropriate for MBAs?
Interpretation of responses: MBAs need to be able to use spreadsheets and statistical software at the level of the "educated consumer".
Curriculum: How do you provide quantitative competence to your MBA students?
a) Requiring core courses in the quantitative disciplines
Interpretation of responses: OR/MS has a small but persistent presence in the MBA core; however, it is rare to have a pure OR/MS course in the MBA core.
b) Blending the quantitative material into more general courses
Interpretation of responses: Marketing, finance and operations courses are the most likely to contain OR/MS materials. There is a specialized service role for OR/MS faculty in supporting second year courses in these areas.
c) Offering quantitative concentrations
Interpretation of responses: Quantitative concentrations are rare and small.
d) Relying on elective courses
Interpretation of responses: There are opportunities to teach small, specialized courses, but often in conjunction with subject matter from the functional areas.
e) Other
Interpretation of responses: There are no significant curriculum opportunities for OR/MS besides those listed above.
INFORMS Initiatives: There are many possible ways that INFORMS might work to revitalize the contribution of OR/MS to MBA education. Please comment on whether the following INFORMS initiatives would be helpful in your particular program.
a) Sponsoring development of teaching materials in OR/MS (cases, videos, texts, software, games)
Interpretation of responses: This was clearly the
initiative most attractive to the deans. There is great interest
in development of quantitatively-oriented case studies.
b) Offering workshops to improve the teaching skills of OR/MS faculty
Interpretation of responses: There was little enthusiasm for this initiative. Most deans think their faculty are already excellent teachers and would not participate.
c) Fostering communication and networking about teaching among OR/MS faculty at different schools through newsletters, home pages, conference sessions and workshops.
Interpretation of responses: This was the second most popular initiative, perhaps because it doesn't have the punitive aspect of (b) and could advance the work of (a).
d) Influencing faculty to shift focus from technical aspects of OR/MS to modeling and business issues
Interpretation of responses: This was not a popular option. While the deans see this shift as important, they believe it has already taken place at their schools.
e) Encouraging OR/MS faculty to form partnerships, including joint teaching, with other functional areas (information systems, operations management, finance, marketing, etc.)
Interpretation of responses: This was not a popular option. Again, the deans see this as important but either believe it is already happening without INFORMS or don't believe that "algorithm" faculty will make the transition.
f) Increasing faculty and student awareness of management career paths with a quantitative focus
Interpretation of responses: This was not a popular option. There was tepid support, but few deans thought the effort would be successful at their schools.
g) Increasing awareness of OR/MS within the business community
Interpretation of responses: This was the least popular option. While the deans felt that success here would have a great impact, they either don't believe that the job can be done or they deny that OR/MS has such a central role in the MBA skill set.
h) Other
Interpretation of responses: Suggestions had to do with developing faculty who are not ignorant of business, are not exclusively focused on theoretical work, and are rewarded for applied work.
Which of these activities do you think INFORMS should give the highest priority?
Interpretation of responses: The clear winner was the initiative to develop teaching materials.
There is little support for the role of the solo OR/MS faculty member providing advanced, specialized education in the framework of an MBA program. This is not to say that there is no role at all for OR/MS, but it is more complex. The role requires extensive collaboration in core courses, carefully arranged support of a few advanced courses in functional areas, and a willingness to anchor any course on fundamental business issues rather than OR/MS technologies. INFORMS and individual members who serve as dissertation advisers might make clear that Ph.D. graduates hoping for teaching careers in top business schools will have to function in this less mathematical, more team-oriented, more eclectic environment.
There is clear evidence that there must be a major change in the character of the OR/MS course in this environment. There is little patience with courses centered on algorithms. Instead, the demand is for courses that focus on business situations, include prominent non-mathematical issues, use spreadsheets, and involve model formulation and assessment more than model structuring.
Such a course requires new teaching materials. The deans were clearly most enthusiastic about potential INFORMS initiatives to develop teaching materials, especially cases with analytical content.
The mail survey of OR/MS teachers documented agreement that the role of OR/MS in schools of business is not large now, was better five years ago, and is not expected to improve in the next five years. However, the profession seems to have already initiated a diagnosis and response. The major cause of the current problems is seen to be a gap between students' interests and mathematical abilities on the one hand and the emphasis in the traditional course on mathematics and algorithms. Instructors are planning to change their courses to place more emphasis on using cases and developing skills in modeling and computing, including use of the spreadsheets that are already familiar to business students. However, it appears that further improvement will depend on the development of case-based teaching materials.
The telephone survey of MBA program administrators revealed that the current role of OR/MS is relatively minor in the core curriculum. There was more concern for competence in statistics than in OR/MS. The deans' reading of the market was that MBAs do not need a high level of technical proficiency in OR/MS to be attractive to employers or effective in their jobs. They also believe that additional technical material can be provided in courses about the functional areas or specializations. Those who teach OR/MS were criticized as sometimes too uninterested or unschooled in business and uninspiring in the classroom. However, there was strong support for the notion that MBAs should be strong analytical thinkers who are able to commission and use models of all types. If OR/MS teachers were to stress general modeling skills and to embed their analytical material in substantial business cases, they would have a more important influence on the MBA degree. Consistent with this, the MBA administrators clearly singled out development of case materials as the most promising initiative for INFORMS to undertake.
It is clear that OR/MS is not generally in a strong position within schools of business in the US. Believing that the potential contribution of OR/MS is still great, we recommend that the following steps be taken by individual academics and by INFORMS.
Individual OR/MS teachers should:
INFORMS should:
There are several means by which INFORMS could pursue these initiatives. Development of teaching materials could be promoted by:
Likewise, INFORMS could foster networking by:
Below are comments offered by survey respondents about "What actions/activities INFORMS might undertake to improve the status of Management Science/Operations Research in schools of business". These comments provide a comprehensive sampling of opinions and suggestions. The comments have been lightly edited to improve clarity. The numbers at left are the respondent's serial number.
4. Develop MS/OR cases to be used in classes. Teaching notes for each case are critical.
6. 1. work on integration with functional areas, i.e., Finance, Marketing, Strategy
2. work to move MS/OR into courses as analysis support and reduce image as stand- alone "barrier" to degree (and perhaps not vital to real management decision making).
7. Link material more directly to business examples, in a broader managerial context.
8. Emphasize modeling and managerial issues.
9. Develop modules for topics which show all levels of treatment:
1. some key insight for anyone-even if never doing OR/MS
2. simple technique to solve a personal problem everyone faces (i.e., buying car and using multiattribute weighing of attributes)
3. entry level MBA job which uses this approach in non-manufacturing area
4. advanced application (i.e. large model version).
10. Perhaps develop a set of guidelines or minimal knowledge requirements for "certification", like APICS or CPA exam.
11. Informs must integrate with the societies representing the clients, e.g., Academy of Management, AEA, etc. through joint conferences, journals, etc.
12. I see only the "functional areas of business" enjoying widespread faculty support. The majority of students are mathematical illiterate (as are most professors) and want to stay that way.
13. Encourage instructor to embrace spreadsheets the way the business community has.
14. Create more material that shows the success of practice.
17. More jobs, higher visibility in management areas.
19. Encourage spreadsheet modeling.
20. Inform non-management science instructors to get aware of the usefulness of the topics. e.g., faculty for marketing, management, economics, business law think that this area is just an academic field.
21. 1. Encourage innovative teaching
2. Help develop cross-functional class room examples
3. Study use of graduated MBA, for MS/OR.
24. Provide persuasive arguments about how/why MS/OR should be taught at business schools.
25. Continue the emphasis on spreadsheet modeling, especially in business-related areas (finance, marketing).
26. Better marketing to business executives and clients through some sort of image improvement planning.
33. Facilitate greater communication with and participation from corporate INFORMS members in the region.
36. PR, promote TV sit-com about OR/MS analyst; deal with relevant management problems rather than the esoteric.
37. Partnership with Microsoft to develop version of Excel with better solver, statistics functions and decision tree add-in.
39. All of these are not very relevant. My college has gone in 5 years from requiring every undergraduate and MBA to have at least one MS course to requiring none of them to. Loads of MS courses have been eliminated. HELP! The issue is existence, not just "status". We have only one MS course left in our course that is regularly offering! My morale is low!
40. There is not enough space to answer this. It appears as though there is a strong anti-MS/OR ( quantitative material in general) has in business schools - however, I hope that we all outlast the current "fads"!
43. INFORMS workshops and a forum for exchange of successful teaching methods.
45. Make more plant tours available to classes.
46. Publish applications of ms/or techniques in the OR/MS Today magazine, make these applications specific to those topics discussed in an undergraduate or MBA management science course. These applications need to be current industrial and service applications.
61. Focus on where we help/interact with the functional areas.
62. I don't know but I believe or/ms is in a crisis stage in MBA curricula. Illinois is proposing to go from a required semester course in management science to an optional 7 week module. The dean does not want to produce MBA's who are "quant jocks". I've heard that similar reductions are being made in other MBA programs.
63. Find a way for students to see a need for OR. Accounting students used it on old CPA exams, but not any longer. Most businesses do not use OR, so students are not motivated.
65. More examples of real applications.
69. Retool the good ol' boys in using a) spreadsheets as a tool to teach ms/or concepts b) get away from algorithms. c) focus on real examples that emphasize the true use of MS/OR assisting the decision maker.
70. Produce materials such as video, cases, games.
72. INFORMS workshops.
73. Arrangements for professionals/practitioners to visit classrooms.
74. Modernize the curriculum to reflect the ubiquity of good computing tools. There is no excuse for textbook authors assuming that students are restricted to working with a hand-held calculator.
75. Summer Internships.
76. Keep schools abreast of what other schools are doing. Number of required courses, math prerequisites, topic coverage. Provide links to other disciplines, marketing, finance, etc.
77. Help us identify job opportunities for students. Help promote industry to hire strong MS students. At the undergraduate and MBA levels, course enrollments are job driven!
78. 1. Create a library of good cases and provide at minimal cost
2. Publicize MS/OR through success stories. TV coverage, newspapers would help.
3. Concentrate on strategies to create awareness of MS/OR among employers nationwide.
80. Need to increase awareness among deans and other high-level officials. The profession need to have an image of a profession, rather than just an academic endeavor!
84. Courseware design.
85. Develop a base of case studies/applications to use, which would motivate students to better appreciate OR/MS potentials.
87. 1. Stress the importance of a good foundation in MS/OR
2. Involve professions from functional disciplines of business and demonstrate to them, through seminars, on-site visits, etc. the role of MS/OR.
3. Make presentations to students of real cases involving MS/OR concepts.
89. More interaction with industry.
93. Our school is relatively small (1200 BBA graduates, 100 MBA, 50 Part-time MBA, 35 executive MBA). We have chosen to emphasize operations and information technology, with quant/OR/MS in supporting role.
94. 1. Produce videos that are not too simplistic/trivial, but show how MS/OR is used in business.
2. Publish case-studies/real-life problems for both introductory and advanced level students.
95. More realistic cases, and a willingness to jettison those methods that in all honesty are not that useful! Elegant theory is great for Ph.D. but not MBA!
97. Less theoretical, tie to other related disciplines.
98. Assume minimal mathematical understanding even with math pre-requisites for the course.
101. Teaching-oriented journal with ideas, topics, problem sets, etc.
102. Improve job market or at least make the students/employers recognize the value of learning a difficult subject.
105. 1. Document what other schools are doing ( publish program requirements of schools)
2. Compile database of popular press articles highlighting MS/OR success stories
3. Publish cases focused on functional areas but with "neat" MS/OR solutions.
106. Deal with the question of what does a typical MBA student need to know about MS and why. Is it different for those in service industries vs. those in manufacturing? How do you move away from algorithms and still teach rigor and critical thinking?
108. Put together good case examples of OR/MS modeling tied to the introductory OR/MS courses (not advanced modeling). Anything that promotes/demonstrates the value of OR/MS to the business community.
110. Would like to see a few really good videos showing OR techniques at work in industry. One of these from ORSA, "OR + You = An Exciting Career" about OR at Disneyland is a little corny.
112. Emphasize multicriteria decision making.
113. Who knows?
114. Compile a large set of problems and cases in OR/MS.
117. Seminars on teaching MS/OR; some promotion with schools and perhaps AACSB, the accrediting agency.
118. 1. Recognize that MS/OR is not a "service" course for other functional areas. MS/OR content has value above any specific usage in other courses.
2. Demonstrate the need for MS/OR to colleague through the use of real application.
119. Students will be attracted to the materials if they see it will get them jobs. Sponsoring OR summer corporate recruiting will show that linkage.
122. To provide a vehicle for consistent teaching in topic coverage and textbook material.
125. Make students recognizing the importance of MS/OR; more job opportunities.
127. Integration of MS/OR applications across functional areas.
129. Get the word out about success stories! OR applications are hidden!
131. Promote through educating people about usefulness of MS/OR and applications to real world problems. Generate videos or case studies. Market the subject and its applications.
132. Need MS application examples in other disciplines (texts). MS is currently too "stand alone".
134. Educate general public about the important role OR/MS plays in business world.
135. Bring texts out of the 1950's algorithm focus and get some decent decision analysis materials in them.
136. Publish a survey of MS/OR software.
138. Combine with production and operations management.
139. 1. Encourage improvement in math skills.
2. Stop dumbing down quantitative books that are already 1000 page tomes of pablum with little meaningful analytic content. Stupid books make stupid students!
141. 1. Demonstrate its applicability to Deans and college administration
2. Right now, corporate folks always like the "soft stuff" as most important. This needs to change.
145. Workshops on using spreadsheet.
146. Workshops on the importance of MS/OR for business faculty.
149. Not allow papers at meetings unless the method was used in the real world.
153. Provide real-life case studies to schools. Publish easy-to-read problems and solutions in an INFORMS journal for students to understand.
154. Target awareness programs at business students.
155. Convince business practitioners of importance of OR/MS and then convince them to tell business schools of its importance. Business schools are becoming less quantitative because they believe this is what business wants and NEEDS.
156. Motivate students to major in the subject by encouraging industry to provide internships, employment opportunities, active on-campus recruitment.
157. Show the way in which MOST companies are using OR/MS. Business schools teach what they think business wants and needs. Convince the business community of value of OR/MS and they will convince business schools of its value.
158. Standards of curriculum, library of case studies, evaluation of software, guidelines for multimedia tools that publishers could develop.
165. Create a multimedia base for instructors to access over Internet. Encourage development of multimedia resources for teaching MS/OR topics. Create another resource base for programs (shareware-type) for advanced methods such as goal programming, nonlinear programming, etc.
169. More of this type assessment, but with feedback to the sources of the information/schools.
170. Fight the case that it will make a difference in getting a job or a higher salary for business graduates. They don't care about intellectual exercises that do not add to the bottom line.
171. Get the information of what we do before the public, i.e., employers.
174. Start an MBA case competition?
176. Continue actual support for publication of real application. Support development of cases based on real applications.
177. Link to other business areas could be improved.
179. Teach problem finding and problem solving, not math appreciation.
180. Promote OR/MS to corporate America, so they will hire students with OR/MS skills.
184. Make it a requirement.
185. I am afraid it is too late-the damage is already done. Think in terms of a long-term agenda. If businesses use MS/OR, business schools will have to teach it.
187. Change the image of the discipline to something with more career appeal.
188. Contact with AACSB will be extremely helpful.
189. Development of MS/OR curriculum.
190. I don't think it can be fixed. It's dying - rightfully so.
191. We need to promote the concept of the "math-skilled MBA" who knows just about as much as any other MBA but has strong statistical, OR/MS, and multi-platform computer skills.
192. Video tapes showing real-world applications.
195. Prescribe its role in the general MBA curriculum.
196. Show relevance of topic to enhancing students employment opportunities.
200. If INFORMS is to succeed, it needs to address the real problems of administrators in the private and public sectors. Much of the work done by MS/OR professionals and educators is still a collection of solutions in search of problems. The directions of the MS/OR agenda must be changed.
202. Application videos; abridged Interfaces articles (undergraduate reading level).
206. Start a newsletter (or a journal?) on MS/OR teaching. Clearinghouse for OR/MS cases.
207. I think we are heading in the proper direction.
209. I think the development of cases based upon the Edelman awards that include video (or multimedia) showing the plant site, describing the problem, and management statements about value of solutions.
211. Support or publicize spreadsheet integration for introductory courses.
213. Videos emphasizing practical applications.
214. Undertake an effort to educate both the business community and academics in other disciplines (marketing, finance, etc.) about the importance and relevance of MS/OR. Encourage non-methodological and applications-oriented research in journals.
216. Relate textbooks to actual (successful) practice. Emphasize data development
217. Get closer to POM area to show MS/OR applications.
220. Teaching workshops.
221. 1. Selectively improve readability of MS.
2. Have survey and/or summary articles in MS (as well as the present mix).
3. Try to focus in MS/OR in service systems.
224. Provide help and encouragement to textbook publishers to produce more up-to-date, spreadsheet-oriented, modeling-oriented textbooks. Most textbooks have tables of contents and treatments of topics that represent OR/MS as it was in the late 1950's. Who cares any more abut the Hungarian algorithm or the minimax or maximax criteria for decision making under uncertainty? Teaching modeling skills!!
225. Describe how MS/OR is an important technology for modern management and specify how it can be easily delivered through information systems for management.
228. Showing the importance of MS/OR in decision making process through case study.
229. I do not know, because I work for an engineering school and probably focus and approaches are different.
230. Integration with other functional areas.
232. Workshops on effective OR/MS teaching and promote the emphasis on business application cases.
236. Develop opportunities for case studies.
237. Combined structure of contents with statistical concepts/application and MS techniques (e.g., forecasting, decision making).
239. Let the students know that there are MS/OR jobs!!
244. More emphasis on teaching of MS/OR at meetings, promote the development of more video material on applications that can easily be edited to emphasize modeling or managerial implications.
247. Your questionnaire is presented on the assumption that MS/OR's importance should be increased. Given that I vehemently disagree, I cannot answer positively. My concept of MS is different. I believe in a science of management which deals with problems and decision making in a non-mathematical way.
248. More case study development programs. More videos.
250. Need a new committee to (a) study what is happening as many B-schools seems to be de-emphasizing MS/OR, and (b) what response should be made.
251. Educate faculty, students, and administrations about the role of quantitative decision making in business.
256. Would like to be associated with other developers of cases, also.
261. Greater dissemination of information regarding the essentials of using quantitative methods in decision-making. Students often graduate without knowing the value of QA; they just learn it cursorily, but students should be able to critically analyze.
265. Insightful and affordable teaching material.
266. I wish I knew. I do have some ideas, but they don't reduce to simple bullets.
268. Help with materials to answer: "Why do I need to learn this stuff? What good is this going to do me?"
269. Talk to deans.
270. Get the AACSB to re-institute quantitative methods and POM courses as requirements of all business students.
271. I have been working on an article about MS/OR in MBA and EMBA programs: A case is discussed in the article. After it is completed I will be more than happy to send a copy to INFORMS.
273. More exposure in industry to draw upon these techniques. More case analysis development.
274. More PR and guest speakers of renown.
275. 1. Workshops 2. Textbooks
276. 1. Write a supplement or small companion containing up-to-date case studies - using companies who are well known to students (Microsoft, Nike, etc.)
2. Design a video to bring "real world" into classroom.
277. Strongly encourage business faculty to do MS/OR research with real business applications. Support this by publications on real business applications in Management Science. Discourage theoretical publications in the society journals.
280. "New Perspectives for OR/MS/OM/MIS Courses," scheduled on April 23, 1995.
281. Continue to hold tutorials on 1) teaching MS/OR 2) applied courses of MS/OR such as Operations Management, Marketing Management.
283. At my school, I fear that with the current anti-technical faculty and administration in the B-school, it's really hopeless.
284. Provide well-written, attractive, informative brochures to distribute to students who are selecting a major or enrolling in elective courses.
285. Drop emphasis on mathematically "neat" topics. Focus on things non-OR/MS majors will actually use: general model formation skills, effective spreadsheet use, decision analysis, basic forecasting models, Monte Carlo. Forget impressing the professor for once, and focus on realistic needs of mainstream business students!
286. Develop and distribute course material (e.g., videotapes), create workshops (particularly for junior faculty) on teaching, create workshops on teaching particular subject matter (e.g., modeling, applications in X), provide clearinghouse for faculty-practitioner interactions.
288. MS/OR should be a mandatory 4-credit hour course.
289. More practical problems for students to work on. Make CPMS tapes available to our institute at a reasonable cost! I have no budget but would love to show MBA students a tape or two.
293. Publish material showing applications in real life.
294. 1) Advertise MS/OR better: give a more business oriented perspective of the MS/OR folk and applications and practice.
2) Preserve the field through better publicity with the business world and academe: all functional areas have adopted OR techniques - no room for OR.
298. 1) Develop real world problem examples and cases.
2) Produce a series of short video clips about people using MS/OR in real organizations.
299. Develop a report similar to University of Chicago/ASA report on Business Statistics - New Approaches, workshop to further gather opinion.
300. Convince our dean! (There are NO undergraduate courses!!)
301. Sponsor "practical" industrial/real life applications workshops.
302. Push importance with AACSB.
304. Provide a forum on the Internet/WWW for sharing
information on MS/OR courses - outlines, format, cases, exams,
etc. to enhance effectiveness of MS/OR courses. Discussion
sessions on this topic at INFORMS meetings.
Shown below are the detail responses we received from directors of the top MBA programs in the US. Because we promised our respondents confidentiality, we will not list which schools responded, we have scrambled the order in which we present the responses to each question, and we have edited the responses.
Statistics (data analysis) and general spreadsheet modeling are considered essential. Students' ability to take structured approaches to problems is being tested increasingly via direct case study analysis in interviews. This mode of thinking is being increasingly rewarded by employers.
Two areas that are most quantitative are marketing research and finance. In both, statistics, especially regression analysis, are important skills. Not as much need for optimization. The Operations Management (OM) group is in flux, and is not the same as OR.
Areas that require the most quantitative skill are marketing, consulting, and accounting/finance. Statistics, including regression analysis, and general spreadsheet modeling are very important skills expected of our MBAs.
The greatest demand is for skills
in computing and information systems (IT skills). We have a large
concentration in Information Management (IM), about one year old,
which was selected by about 1/3 of the MBA class of 1997. We
can't produce IT majors fast enough. Elements of the IM
concentration will eventually be incorporated into the core. In
general, employers want MBAs who can apply the full spectrum of
quantitative skills (Statistics, Operations Management, OR/MS,
IT) to business problems. They also want employees who can
communicate, work in teams, and solve problems. Entering MBAs are
required to know some differential calculus and how to use a
spreadsheet.
In general, the ability of
students to think analytically, i.e., to structure the situation
into a model, to analyze it and reach conclusions rationally.
More specifically, not knowledge of rigid methodological
approaches, but the ability to think analytically when faced with
unstructured situations.
Must know how to formulate a
problem and interpret managerial implication of results. Quant is
alive and well here.
Greatest demand: statistical
analysis (e.g., regression), ability to think using the structure
of formal models.
It is essential that graduates
have analytical skills.
Success factors for MBAs::
communication skills, working with others, hard knowledge, being
at cutting edge. We are good at getting them to the cutting edge.
Faculty is divided on importance
of quantitative competence. Core finance and accounting courses
are fairly strong quantitatively, but weak in second year. Core
is weak on data and statistics. Difficult for marketing (for
example) to leave strategy arena, but hard to teach quantitative
skills.
In consulting, the need for
advanced techniques is not that great; college algebra does well
enough for most. In finance, the more math the better, including
statistics, calculus (preferably stochastic calculus), linear
algebra. In manufacturing, linear algebra is sufficient. Demand
for OR/MS is small, e.g., OR is hot in transportation sector
lately, but only a few of our students go into that sector.
The bulk of MBAs go into finance
and consulting. Employers don't expect sophistication but do
expect mastery at the "high competence" level; for
example, employers interested in quality control would not expect
knowledge of design of experiments, but would expect knowledge of
Pareto diagrams, fishbone charts, scatterplots. Employers want
computer literacy, spreadsheet modeling skills, and
"conditional thinking". The latter means accounting for
uncertainty, identifying and articulating assumptions and tracing
their consequences, then examining the consequences conditional
on a new set of assumptions.
They must be able to interpret
quantitative information and reach conclusions.
Recruiters are expressing need for
grads to be able to interpret data.
Analytical reasoning is more
important than tools and techniques. This means framing
arguments, tight reasoning, capturing the essence of a problem.
Sufficient familiarity to be
intelligent users of information from quantitative models,
knowledge of appropriate uses of different models.
Should be able to do simple
multivariate regression analysis. Faculty disagree on whether
MBAs should be able to do much quantitative analysis themselves
beyond regression. The students who get a Masters in Management
of Manufacturing get much more OR than the MBAs.
Quant competence means
probability, statistics, LP/modeling. We have a highly
quantitative program.
Spreadsheet knowledge and
classical statistics, including regression, are expected as part
of background knowledge. Details of specific MS modeling
methodologies are not essential so long as students can
"think on their feet" given novel situations.
Should be able to do regression
analysis and "What if?" spreadsheet modeling at a high
level of competence (build, analyze and interpret models).
Awareness of concepts of decision modeling under uncertainty
(decision analysis) and optimization modeling (LP and sensitivity
analysis) is important. Ability to access and/or design
information systems to integrate data into spreadsheet analysis
is also considered important.
The appropriate level of
competence is to be able to: 1. recognize the need for
quantitative analysis; 2. select the appropriate methodology and
software; 3. apply the software to the appropriate data,
interpret the results, and apply them to help solve the problem.
Theoretical and computational bases for the above methods (e.g.,
teaching the simplex method or duality) is not needed and not
well received by most MBAs.
Here are examples of the level
expected. Regression: expect significant ability to interpret
output of statistical packages; to identify assumptions; to check
the model for reasonableness; to critique the model. Polls of
customer views: be able to interpret results in the light of
margins of error. Simulation: be able to build spreadsheets that
incorporate uncertainty. Equations: be able to discuss and model
relationships using equations.
Essential to be able to apply data
analysis and spreadsheet modeling to management problems.
Concepts of decision modeling under uncertainty (decision
analysis) and certainty modeling (optimization) is important. Use
of simulation and project management (PERT/CPM) to model
uncertainty in spreadsheet models is a useful skill.
They should know enough to ask
questions and invest in the right product or project, i.e., be
"educated consumers".
They must be able to work with
numbers and use models to make decisions.
Analytical abilities are demanded
in marketing, accounting, finance. Required skills are more
generally analytical than purely quant.
The leadership here thinks quant
skills are less important than communication, ethics, global
issues, etc.
Depends on field. In consulting,
not much is required. In finance, the more math, the better. In
production, linear algebra is enough.
Need to know what can or should be
done with quantitative analysis.
Quant emphasis here is medium
moving to medium high. Spreadsheet modeling, especially of pro
formas, is becoming a fundamental skill for all MBAs. Not just
passive analysis is needed; MBAs are expected to be able to build
and analyze their own models.
Quantitative MBA core courses:
Statistics (3 hr.), Operations Management (3 hr.), Strategic IS
(1 hr).
Require 1 semester of Operations
Management. Require 1/2 semester (7 weeks) of MS, which covers
general spreadsheet modeling, decision analysis (including
probability and Monte Carlo simulation), optimization and project
management. Require 1/2 semester of Statistics (incl. regression,
survey design and classical statistics.). Also require a 5 week
module on information systems which increasingly will build upon
the MS topics. Game Theory is covered in the Microeconomics
course.
Require 1 quarter of Operations
Management. Require 2 quarters of Decision Sciences, which covers
decision analysis (including probability), statistics and
regression, general spreadsheet modeling, optimization, database
and information systems. The LP portion is systematically being
reduced to emphasize integration of database and info. systems
design into modeling issues.
Require 1 quarter of Operations
Management and one quarter of Statistics. The core MS course
became a constrained elective and more recently has been moved to
a pure elective course (still popular and well subscribed, but no
longer required).
Require 1 quarter of Operations
Management, but this has become less technical over time. Require
2 quarters of Decision Sciences, which starts with 4 weeks of LP
and goes on to basic probability and statistics. There is
discussion about dropping the LP portion.
Two core courses, one covering
probability and statistics and another covering decision
analysis, linear programming, and simulation.
Yes. There are required courses in
the "preterm" (3 weeks in August): 18.5 contact hrs
in Economics, 20 hrs in Statistics. In the core, there is a
halfsemester each of Statistics, Management Science, and
Managerial Economics (calculusbased). Management Science course
examines art and cost of modelbuilding. Features a diversity of
applications.
First semester: Management Ec
(includes LP), Data (probability, hypothesis testing,
regression), OB, Accounting; Second semester: Individual
Decisions (game theory, queuing), Marketing, Finance, Political
Economy, Production (take 2 out of last 4).
They have only a small core (i.e.,
not all of first year is required). Quant methods covered are
statistics and probability. Operations covers LP, simulation,
inventory. Quant content has stayed constant over the last 510
years. Marketing, for example, can be more or less quantitative
depending on who is teaching. Even Organizational Behavior has
become more quantitative.
Yes. The core quantitative course
meets for 1.5 hr sessions 3 times per week for a semester. It is
mostly an introduction to data analysis with a 2 week OR module.
We do not expect OR to be main job of graduates, but they benefit
from analytical discipline.
There is a two semester QA course.
The Fall term tests for ability to treat uncertainty, put
together a model, run the model, understand from a simulation all
the interconnections among the parts of the system, draw
conclusions, and explain reasoning. For instance, if the issue is
whether to accept an order, the MBA should be able to consider
bottlenecks in the plant, unreliability of suppliers, costs of
accepting the order and not delivering or of declining the order,
etc. The Spring term features sampling, regression, reading and
interpreting data, and simple time series models (e.g.,
exponential smoothing, seasonality).
They have done away with the
Managerial Economics department, and the Man Ec course (which
included 3540 sessions on quant) will not be given after this
year. Thus after this year no core course covers MS/OR or even
statistics. They will try to cover these topics in
preenrollment. Even the Operations courses are not very
quantitative. He blames both total commitment to the case method
and the dominance of strategy.
Yes. One semester course in
statistics and 1/2 semester course in Decision Models.
Yes, we do this.
Quantitative material mostly
blends into marketing research and finance courses.
Quantitative material directly
supports the Marketing, Operations and Finance courses; with
indirect support elsewhere.
The key opportunity is for the
quantitative faculty to work with the marketing and finance
faculty to support their core courses. The key indicator of
success is whether the non-QA courses use QA materials. Right
now, there are missed opportunities; for example, finance treats
risks by adjusting the cost of capital, whereas QA models risk
explicitly. These two groups should address the difference in the
way they treat risk. This would be more important than having the
quant faculty provide mutual support for their advanced courses,
which happens now anyway.
Second year finance courses are
sophisticated in quant. Two faculty teach modeling in three
courses: Production, Quality, and Quant Modeling for Public
Policy.
Other MBA core courses with
significant quantitative content: Financial Management, Financial
Accounting, Managerial Microeconomics, Marketing Management.
There are explicit initiatives
underway to better integrate the decision science topics into
other core courses (Marketing, Finance, Cost Accounting and
Operations). This may result in some streamlining of some of
these courses to reduce overlap.
Quantitative material directly
supports the Operations (via inventory theory models) and Finance
courses (spreadsheets used to model efficient portfolio
frontiers), with indirect support elsewhere.
Quantitative material directly
used in a wide range of electives with indirect support
elsewhere. The electives include traditional MS courses and
non-traditional approaches, including novel uses of decision
analysis and game theory in several popular electives.
Yes, more specialized quantitative
materials introduced as needed in both core functional area
courses and in electives.
Yes. One semester each of OM,
Finance, MicroEconomics, and Accounting.
Yes,. We may be the most generally
quantitative of all the leading business schools.
Yes, the core Operations
Management course and Finance electives contain quantitative
material.
Yes. Also, we try to coordinate the core Operations Management course with the Decision Models course.
The most notable example is the
required course in Operations Management. This course uses
probability models for queues and other OR materials. Several
OR-trained faculty teach OM. The other clear blends occur in
finance and marketing courses. Other courses have almost no
blending: Human Resources, Strategy, Ethics, Accounting (although
Accounting does support OM).
We have no quantitative
concentrations.
Don't have any concentrations.
There are no concentrations here.
There are no concentrations here.
There are no concentrations at our
school.
Once had a real competence in
Decision Analysis. A lot of the faculty worry about the total
lack of coverage now. One possibility is that it will covered in
a new core course on negotiation.
We do this, but very few students
choose them.
Yes. Not very popular, only a few
students take them.
No, we have no quantitative
concentrations, though we have concentrations that become very
quantitative. Financial Engineering has a very quantitative
finance course, but it is not like a typical OR/MS course. Our
marketing group is the most quantitative in the US, but not many
students take these courses.
We have two quantitative
concentrations: 1) Information Management (IM), which about 25%
of first year MBAs elected in Fall '95; 2) Operations Management,
which is much smaller but may grow after first years take the OM
course.
Yes. There is a major in MS. The
department offer 3 majors: IS, MS, and OM. Only 5% are MS.
Courses in decision making under uncertainty and optimization.
They are instituting
specializations, not quite majors. One is Financial Engineering;
others are Semester in Manufacturing, possibly Environmental
Management, Marketing and Distribution. These specializations
allow them to do more challenging material, including quant,
because the students are selfselected.
Yes. Concentration consists of 4
elective courses beyond the core.
Yes. Also, we try to coordinate
the core Operations Management course with the Decision Models
course.
Strategy group is
economicsbased.
12 MBA elective courses have
significant quantitative content; 8 are taught by OR/MS faculty.
Many elective courses expect
spreadsheet and modeling skills.
Perhaps 10-12 courses are highly
quantitative. These have small enrollments, except in marketing
research and finance. Course on futures and options includes some
differential equations.
Many elective courses expect
spreadsheet and data modeling skills.
Yes. Primarily a special topics
course.
We offer one popular elective:
"Applications of Decision Theory to Financial
Services".
A limited number of electives
serve as background for careers in other areas (e.g., Finance).
Yes.
Electives with high technical
content include a course on managerial decision models (utility
theory, advanced simulation) and a course on design of
experiments (where statistical software eases the technical
burden).
There are courses in other
departments (e.g., computer science).
The 1/2 semester of MS was dropped
from the core 5 years ago, largely because of unpopularity, but
has been reintroduced this year on a trial basis with hope of
its continuation.
Each concentration has some
required courses, as do tracks within concentrations, some of
which are quantitative. Many of the IM core courses are
quantitative.
There is a 1-week math (algebra)
review before classes start.
Spreadsheets: current graduates
are weak. Incorporated in the Finance course. Thinks it will
improve in the future as all admitted students will know
spreadsheets when they arrive.
All students are expected to be
spreadsheet literate before starting classes. There is a
preenrollment math review and a separate spreadsheet review
before classes start.
Important and should be pursued by
INFORMS.
This is a really good idea.
This is an excellent idea.
Yes, absolutely.
This is very important and a
superb initiative for INFORMS. We are already very good at this
and could help.
Would be very interested in this.
Definitely need materials,
especially cases, with a problem focus. Allow students to learn
methodology in the context of a real problem. Should show
relevance to functional areas.
Good cases would help. Harvard
cases too simplistic; quant methods should be in the background.
There are no good LP cases. Need large scale applications , not
mickey-mouse examples.
This is a good idea. Harvard cases
are of little or no use because they do not stress the analytical
aspects of the cases. Those that attempt to do so are too
cookbook and do not challenge the students analytically. This is
a vacuum that INFORMS can fill: to provide cases with more
analytical depth than found in Harvard cases and in the
toosmall problems found in textbooks. Cases with enough data
(via the Internet) and fostering alternative modeling approaches
are needed. The other items (video's, software, etc.) are also
good, but difficult to evaluate in advance.
New textbooks are badly needed.
Seems like nothing new has been published in 40 years: new books
slavishly follow patterns of old books. Books need more emphasis
on: conceptual foundations, the mode of thinking, the context of
OR applications, and the assumptions behind models. No need to
avoid intellectual challenge. Can explore deeper ideas, like
complexity, but in a management context. We sometimes use the
Edelman tapes, but they are not really teaching tools. Interfaces
articles are assigned as optional readings; sometimes are the
basis for cases. Always looking for "motivators", that
is, articles in business press (WSJ, Fortune, Forbes)
where business leaders make pronouncements using quantitative
notions (e.g., marginal pricing).
Develop teaching materials,
especially cases.
Yes; we are always looking for new
materials, and there is little professional reward for faculty to
develop them.
This is a great idea. But there
will be a problem with MS textbook authors.
No, it is not a question of teaching materials.
Important and should be pursued by
INFORMS.
Maybe, if made part of a regular
MS conference.
Always a good idea, except our
teachers are already good. Some OR/MS faculty may need help in
adapting to teaching in new areas., e.g., OR in OM, OR in
finance.
Yes, if done well, but I'm
skeptical that they will be better than our own programs.
Would be difficult to get faculty
to attend.
Would be surprised if any of his
faculty would attend.
Not of much value to our school.
This is the least helpful option
for this school. The teaching skills in the QA area are already
superb. Faculty wouldn't attend such workshops unless they
perceived that the other participants were equally adept.
Already done locally, so unclear
advantage to us.
Our OR/MS faculty are good
teachers and don't particularly need these workshops.
Could try to do this, but don't
know how successful this would be. It is hard to do and not as
helpful as having a good mentor.
Excellent idea, particularly using
home pages. There tends to be more relevance and credibility
within peer groups than through larger organizations.
Absolutely.
Another good idea.
Another good idea. However, if
scheduled at same time as normal conferences then they conflict
with the research-oriented conference agenda, which will win out.
Separately scheduled and advertised workshops might be a better
alternative if they do not conflict with the research program.
The other items are nice, but like apple pie, hard to criticize
in advance.
Some kind of clearinghouse for
teaching materials would help. We would be happy to share our
work.
Important and should be pursued by
INFORMS.
Further networking about teaching
is good idea.
All these would be good ways of
publishing the best teaching materials.
This is a good idea that would
help any faculty. One member of the faculty will be teaching such
a workshop at a national meeting later this month.
I guess this could help, but
faculty don't really talk about teaching, do they?
One of most important since
outward looking.
All for it. An essential
prerequisite is converting faculty colleagues (both within and
without MS) to learn spreadsheet modeling well so the MS
contributions can be picked up within MS and amplified in other
nonMS courses.
Could be very important.
Yes, this is key. Applicable cases
are much better than theory.
Yes; we've made big strides in
this direction.
Already happening on the teaching
side, as with the OM core course.
Already the case on the core
course teaching side.
This is already taking place here,
so it is not needed.
Already doing this. INFORMS could
emphasize even more the prizes awarded, which now are already
well done and received, to reward such shifts.
There is a question of how to do
this. Training and background of quantitative faculty is a
problem.
Not sure what this means, but
probably no.
Comment on b), c), d): there is a
limit to how much you can ask of faculty.
Should encourage faculty to
partner with functional faculty.
Yes, this is working well here.
Probably helpful. Quantitative
partnership with Finance has worked well for us.
This is very important with regard
to linkages among core courses, and is already taking place.
The Decision Sciences core course
already integrates regression, optimization and database examples
into Marketing and portfolio optimization into Finance. Topics on
integrating constraintbased accounting issues from Cost
Accounting and Operations Management topics are underway now.
As with d) above, all for it. An
essential prerequisite is converting faculty colleagues (both
within and without MS) to learn spreadsheet modeling well so the
MS contributions can be picked up within MS and amplified in
other nonMS courses.
One of the most important since
outward looking. Forming partnerships is a particularly promising
strategy, and has been very successful here. In fact, if OR/MS
does re-enter the MBA core, it is likely to be in combination
with IT. It is also worthwhile to offer OR/MS--based courses that
complement other concentrations. This is happening in IM,
Operations Management, and could/should happen in other areas,
e.g., Marketing, Finance, Accounting.
Along these lines, we offer (or
plan to) courses in financial engineering. Hard to find
applications in marketing.
The Decision Sciences core course
uses regression examples from marketing and finance. Doesn't
think much is happening outside the core, where coordination is
almost impossible.
Good idea, but very specific to
individual universities. Little or no role for INFORMS.
Yes, but I'm having trouble
imagining how INFORMS could make progress on this issue.
This could be helpful, but we are
more interested in having the statisticians pal up than the OR/MS
people. The hot area in b-schools is strategy, so OR/MS must show
relevance to strategy. A lot will depend on the OR person. They
will have to go to the other area and learn it; the discipline
won't come to OR. But why would a tenured OR person bother to do
that? It is much easier to just keep teaching OR courses.
"Algorithm" faculty do
not do appropriate research for a management school. Some years
ago, we moved OR out to Applied Math. This was a group a
marvelous teachers, but they were not doing management research.
Could be very useful, particularly
if made substantive.
Should research and advertise
quant career paths.
Students interested in consulting
and investments need to know importance of quantitative work.
Placement office tries to communicate the qualities and
qualifications needed for success in various fields.
Placement Office gives seminars on
careers. Might help if they had more info.
One of the most important since outward looking. The success of our current partnering is largely due to (f), since MBA students are aware of the high demand for IM graduates.
Not much happening now, but could
be useful.
Depends on the school. For us,
it's a given.
Maybe, but how do you disseminate
this?
Very difficult to do at the MBA
level. Could possibly be done constructively for undergraduate
business schools.
This would help, but it would be
more helpful to increase employers' interests in OR/MS.
Not important for us.
No. Neither interest nor demand is
there.
Always a good idea.
An OK idea.
OK idea, but if companies really
want OR/MS, they look to the Industrial Engineering department.
OR/MS Today and Interfaces
are doing a good job, showing the best of applications.
How? Has not worked historically.
OK idea, but not very successful
historically. Better to emphasize the role MS plays in larger
systems efforts which integrate data and decision making.
May need to do some work here, but
it is a long range process. Start with "future business
leaders", that is, the students in our classes.
Suggest a poll of hiring firms
(mostly investment banking and consulting); if the recruiters
wanted more quant even our faculty would listen. The only hope
for quant is to have external constituencies demand more quant.
Should pitch especially to
consulting firms, so they start looking for OR skills when they
hire. It will take a while, but the students will follow. Banks
are already looking for math, computer programming and OR. I
would do focus groups with recruiters for consulting and
investment banking firms. Ask them what skills they want. If they
say they have no reason to hire OR skills, then you won't win the
battle.
This is not helpful because there
is no OR concentration and we don't emphasize this level of
technical skill.
No.
Major contribution by INFORMS
would be to help break the incentive loop in the business school
publicationpromotion process for young faculty to encourage
more applied work. That is, INFORMS should help to reward work
that applies theory, i.e., a return to the original roots of MS.
One approach would be to create journals (or expand existing
ones, like Interfaces) that are refereed and focused upon
scholarly contributions of extant theory and concepts to applied
problems that result in reproducible lessons.
We "get no respect".
There may be some need for improving our image, i.e., the
"nerd" in the back room grinding out the numbers.
Change Ph.D. programs so that
quant grads learn to teach and to apply their theoretical
knowledge. To be successful in the MBA world, Ph.Ds must be
appropriately trained. They are far from that now: too
theoretical, no business experience and often no interest in
business.
[Results compiled as in approval voting]
a) teaching materials: 12
b) teaching workshops: 2
c) networking: 8
d) shift focus: 3
e) partnering: 3
f) career awareness: 2
g) employer awareness: 0
h) other: 2
When asked whether OR/MS is fading
away, he said no. The OM area is making a comeback, and he hopes
the Decision Sciences area will too. The faculty have evidence
that the students are not as challenged as they could be in the
quantitative area, and they want to restore some measure of rigor
by becoming more quantitative in the future. [Note: My
observation is that this respondent, while knowledgeable about
OR/MS, seemed to define "quantitative" primarily as
statistics.]
The role of Decision Science
topics is being reviewed by a faculty committee. This will likely
result in some recommendations to streamline the core courses via
some form of modularization of topics, the success of which will
depend upon how well MS is integrated into the functional areas
(Finance, Marketing, Accounting and Operations).
Quant skills are alive and well at
this school. They do not have a strong strategy group, having
decided only recently to build one. The keys to quant at this
school may be the lack of strong strategy group (i.e., lack of a
strong competing paradigm that is aggressively nonquantitative)
and the specializations they offer.
The MS core course was eliminated,
not because of unpopularity, but because (1) it was dropped as a
prerequisite for the OM course some years ago and because (2) it
was not considered sufficiently foundational for other courses.
The MS electives are still very popular and MS topics are
integral in many other MBA courses.
Quant is being pushed out because
it is falling below the line of critical topics, not because it
is not considered important. Allegiance to the case method works
against teaching quant well.
Dean expects curriculum to swing
back toward the analytic. Teaching quality is the key.
Integration of quant courses and functional areas are also key.
Quant is not on the decline here
or elsewhere. Although the number of people who classify
themselves as OR has declined, many others are highly
quantitative and use OR/MS tools in their functional areas.
Quant/analytic methods are best taught by functional area people
who use quant methods in their research.
Is OR dead in B-schools? Was it
ever alive? If it hadn't been required, would we have ever had
it? Every B-school is moving toward more electives. OR is no more
dead now than it used to be, but students don't have to take it
now. The key thing is teaching: Is it important to OR groups?
Another school had its quant group wiped out; they were bad
teachers and not relevant. They taught technical material without
making it exciting. Some very technical courses can be successful
because the teachers really motivate the subject.