0-11430000QUEEN’S SCHOOL OF BUSINESSProject ReportAssessment of MBA Class expansion opportunity MBAS861Team 412<br /><ul><...
Muneet Bhatia_________________
Ornila Rahman_________________
Peter Szaflarski_________________
Pranab Pandey_________________
Tony Wang_________________
Vishal Sajnani_________________</li></ul>Contents TOC o "1-3" h z u Contents PAGEREF _Toc304788716 h 2Executive Summary PA...
Reputation: through BusinessWeek ranking, word of mouth publicity, prominent alumni presence in the industry etc.
Awareness: through online marketing campaigns, MBA fairs and information sessions, visits to school, scholarships etc.
Number of applications to admission offer ratio 6:1.
Placement rate for current year should be around 90% to achieve desired quality of applicants for the next year class. We ...
Offers accepted = Class size, we have ignored the candidates who accept the offer and then don’t show up on the registrati...
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Business Decision Models

  1. 1. 0-11430000QUEEN’S SCHOOL OF BUSINESSProject ReportAssessment of MBA Class expansion opportunity MBAS861Team 412<br /><ul><li>Kenneth Chow _________________
  2. 2. Muneet Bhatia_________________
  3. 3. Ornila Rahman_________________
  4. 4. Peter Szaflarski_________________
  5. 5. Pranab Pandey_________________
  6. 6. Tony Wang_________________
  7. 7. Vishal Sajnani_________________</li></ul>Contents TOC o "1-3" h z u Contents PAGEREF _Toc304788716 h 2Executive Summary PAGEREF _Toc304788717 h 3Introduction PAGEREF _Toc304788718 h 4Industry Analysis PAGEREF _Toc304788719 h 4Challenges posed by the industry PAGEREF _Toc304788720 h 4Scope of Modeling PAGEREF _Toc304788721 h 5Components of Model PAGEREF _Toc304788722 h 6Assumptions PAGEREF _Toc304788723 h 6Considerations PAGEREF _Toc304788724 h 6Data Collection PAGEREF _Toc304788725 h 7Model description PAGEREF _Toc304788726 h 7Modeling outcome PAGEREF _Toc304788727 h 9Business impact PAGEREF _Toc304788728 h 9Analysis PAGEREF _Toc304788729 h 10Advantages and Benefits PAGEREF _Toc304788730 h 10Disadvantages and Limitations PAGEREF _Toc304788731 h 10Conclusion PAGEREF _Toc304788732 h 11Future work PAGEREF _Toc304788733 h 11Appendix PAGEREF _Toc304788734 h 12<br />Executive Summary<br />With the expansion of Goodes Hall, there is an opportunity to expand the class size of the MBA program and hence increase the profit. MBA office recognizes this opportunity and has requested T-412 Consulting LLP to study the scope of the opportunity and propose the recommendations to the office. <br />T- 412 have conducted an extensive research on the management education industry in North America and recognize various challenges while considering the opportunity at hand. The team has also conducted interviews of various stake holders in the process: Marketing Manager, current MBA and commerce students and alumni of the school. While this exercise was done to gain an understanding of thought processes of these important stake holders, we have built a mathematical model to gain an insight in to the tangible gains from this opportunity as well. This way, the team has taken both quantitative and qualitative factors in account while analyzing the situation and coming up with final recommendations. <br />The team has figured out from the model that over a period of next ten years, the class size of 270 will maximize the monetary gains. But at the same time, we have also realized that Queen’s MBA is a preferred choice for a large number of stake holders due to its smaller class size as compared to most of the competitor schools in North America. Hence, by increasing the class size from 120 to 270 in one step, we may run the risk of losing its unique competitive advantage. The prospective applicants who consider Queen’s as their first choice due to its personalized and integrated learning environment might not look at Queen’s the same way they do today. <br />Considering these factors, we recommend to the MBA program office to take a more cautious and incremental approach to the status quo. The MBA program office can look at increasing the class size by 10-15% every 2-3 years. This way, the program will slowly adapt to the increased class size while not compromising on the experience of the students. This approach will also provide ample time to the school to slowly create awareness about this change in the prospective MBA applicant community through its strategic marketing campaigns. <br />Introduction<br />According to a report published by the Graduate Management Admission Council (GMAC)--a global non-profit education organization-there has been a marked increase in demand for a MBA education in recent years. While the demand for MBAs in the North America is on the rise, it’s exploding at unprecedented levels in many emerging markets around the world. The hottest markets are: India, where employer demand for MBAs was up 43% last year; Brazil, where demand jumped by 25%; the United Arab Emirates, up 22%; Russia, up 22%, and China, where employer demand for the MBA degree shot up 19%.<br />For highly ranked consulting firms like McKinsey & Company and innovative companies such as the search-engine giant Google, MBA graduating classes are optimal places to find new professional staff. This trend is starting to be felt far outside the consulting realm, as companies in a range of industries such as telecommunications, finance, manufacturing, etc., are looking at MBA graduates and experience as a necessary requirement or a highly helpful determinant when examining candidates to join the management team. As more and more corporations are becoming global, demand of experienced and high quality management talent is expected to grow in the future. Global integration is real and it is not going to stop. <br />Industry Analysis<br />For the purposes of this assignment, Queen’s University is in the “MBA business school” industry; more specifically, it is a business school that offers a Master of Business Administration degree. Typical industry analyses do not work for this model since there are suppliers per se and the consumer does not purchase a tangible product. Still, there are many aspects that can be explored within the industry. <br />Challenges posed by the industry<br />Though Queen’s has somewhat of a first mover advantage (since it is the first business school in Canada), it faces competition from older schools outside of Canada and new innovative programs everywhere in the world. The Queen’s MBA is not a low-cost producer, since there are many programs that are significantly less expensive. Queen’s instead targets a niche market (those students who are interested in moving to Canada, willing to pay more for the Queen’s experience, the team-based environment, the Queen’s reputation etc.), so there is difficulty in expanding the class since there may not be enough number of the right kind of students available, and if they are available they may already have found one of Queen’s many competitors.<br />In additional to this, new entrants are offering MBA degrees at lower cost and sometimes online via distance learning. If the goal of our target consumer is simply to get a degree then the new entrants offer the same thing for lesser cost and attracting these students to Queen’s seems unlikely. Also, substitutes, such as the Master of Global Management and other non-MBA business degrees, are becoming a popular alternative to the pricey MBA.<br />All of the industry challenges mentioned above give prospective students more bargaining power for price while also giving them alternatives other than a Queen’s MBA. These challenges have to be considered when deciding to increase the MBA class size but fall outside of the scope of the model.<br />Scope of Modeling<br />We have chosen to use a probabilistic simulation model for this problem. Some of the limitations of the model have been mentioned in the previous section and others will be covered in later sections. for now we will explore why we chose to use this type of model.<br />We chose to make this a probabilistic model because we realize that there is a certain amount of randomness in creating a class of a certain size. The Queen’s MBA program currently has a target class size of 120, and to achieve this target size the program administration currently have a policy of accepting more than 120 students in anticipation of a certain proportion rejecting the offer. Since the exact number of rejected offers is essentially random, the class size is likely to be different from the target class size; we have incorporated this aspect into our model with a binomial distribution offer rejection probabilities based on information from the program office.<br />Another probabilistic aspect is the effect of placement rate, scholarships and marketing tactics on the prospective applicants. The admissions team uses all of these aspects to try to gain as large an applicant pool as possible which, in turn, allows the Queen’s MBA to choose the best possible candidates. The reliability of these tactics is modeled with a normal distribution with a standard deviation that is 10% of the prediction based on numbers from the previous years.<br />The last probabilistic element of the model is the job placement rate. Queen’s has a track record of success when it comes to job placement, but it is dependent on acceptance offer percentage of students that apply to the program. If Queen’s does not get a large enough applicant pool, then it will have to give a larger percentage of acceptances and allow some candidates into the program that, under ordinary circumstances, would not be admitted into the program. This aspect is approximated by the “transformation function”, which takes the percentage of applicants who are given offers and transforms it into a predicted placement rate. The actual number of students placed is modeled as a binomial random variable with n = the class size and p = the predicted placement rate, therefore the actual placement rate is the actual number of students placed divided by the class size.<br />The advantage of the simulation is that we can take into account some level of randomness while still gaining some insight into the future about our decision. The model also allows us to adjust the level of randomness by changing the standard deviation and the desired acceptance offer ratio relative to the expected placement rate. A probabilistic simulation model most accurately describes what would happen as a result of a class size expansion decision. <br />Components of Model<br />Assumptions<br />While developing the model, we had to make a number of assumptions. In some cases data was not available where as in other cases, some data was available on public forums or was obtained from Queen’s MBA office. Following are the assumptions made in the model:<br /><ul><li>Two sources of applicants:
  8. 8. Reputation: through BusinessWeek ranking, word of mouth publicity, prominent alumni presence in the industry etc.
  9. 9. Awareness: through online marketing campaigns, MBA fairs and information sessions, visits to school, scholarships etc.
  10. 10. Number of applications to admission offer ratio 6:1.
  11. 11. Placement rate for current year should be around 90% to achieve desired quality of applicants for the next year class. We have linked the placement rate to the quality of the students in our model. Higher the placement rate, higher would be the quality of applicants for next year class.
  12. 12. Offers accepted = Class size, we have ignored the candidates who accept the offer and then don’t show up on the registration day.
  13. 13. Applicant pool through reputation grows at 2.5% annually.
  14. 14. Applicant pool through awareness will largely depend on marketing expenditure and scholarships.
  15. 15. Every student in the class takes 22 courses of full credits (combination of full and half credit courses)
  16. 16. Maximum seating capacity of a class room is 75.
  17. 17. Its hard to attract higher than desired quality applicants through marketing campaigns. </li></ul>Considerations<br />While modeling the problem, we considered a number of factors which are as follows:<br /><ul><li>Historically, around 50% of the international applicants accept the offer made, while this ratio increases to approximately 70% for the domestic students.
  18. 18. We take conservative approach while rolling out the offers, especially towards the end of the cycle. We do this to avoid having more than expected students turning up on the registration day.
  19. 19. The number of applications follow multiple peaks and troughs throughout the application cycle and the admissions decisions are made on a rolling basis, but we have not taken this in to account in our modeling process
  20. 20. The offer decision also follows a peak and trough pattern but we haven’t taken it in to account.
  21. 21. We have taken a simple approach when taking in to consideration uncertainty around application submission, offer roll out and offer acceptance pattern.
  22. 22. We have not taken in account additional team rooms required in our cost structure.
  23. 23. We have not considered expenses related to Fit to Lead program.</li></ul>Data Collection<br />The team interviewed Marketing Manager, Kerri Regan and some of the other staff in MBA office to gather the data. Some of the data points shared were:<br /><ul><li>Number of information sessions / MBA fairs participated in Canada and other international locations
  24. 24. Approximate costs of the these sessions
  25. 25. Approximate percentage of applicant pool from Canada and international locations
  26. 26. Approximate offer acceptance rate from Canada and international locations
  27. 27. Approximate mix of the class from Canada and international locations
  28. 28. Approximate scholarship budget for the year</li></ul>Other data that MBA office could not share with us due to confidentiality reasons and had to be estimated:<br /><ul><li>Faculty salaries: $1,500 per student per course
  29. 29. Program Director salary: $100,000
  30. 30. Budget allocated to Business Career Center for MBA class: $5,000 per student
  31. 31. Supplies, books: $3,000 per student
  32. 32. Administrative cost: $85,000 for current set up of 2 class rooms
  33. 33. Fixed marketing cost: $100,000</li></ul>Model description <br />We are taking data for the ongoing class of 2012 as the baseline data and building the model for the next ten years on top of this. <br />The decision variable is class size. We have considered 9 class sizes and have linked those with the number of class rooms needed. <br />Class SizeClassrooms required120215021803200321032404250427043004<br />Cost Structure:<br />Fixed CostsProgram Director$100,000 Administrative$85,000 Faculty Salaries$3,960,000 Marketing (Brochure/Manager/Misc)$100,000   Variable CostsSupplies/Books/Overheads/Misc$3,000 Scholarships$4,000 Marketing (Fairs/Info Sessions)$1,300 BCC$5,000<br />Revenue and diversity of the class:<br /> Domestic studentsInternational studentsTuition fee$69,000$75,000Yield rate for admissions 70%50%<br />Applicants pool data:<br />Annual increase due to Rankings2.5%Standard deviation10.0%Average selection rate 16%Desired placement rate90%Transformation function1.256<br />Here transformation function has been derived by correlating % of applicants offered to the placement rate. This way, this function takes care of the reputation of the program e.g. if the placement rate is more than expected this year, then the number of applicants due to reputation factor would be more next year than current year and vice versa. <br />Applications sources breakup:<br />Domestic %Reputation / Ranking35%Additional Awareness15%International Reputation / Rankings45%Additional awareness5%<br />We have taken normal distribution for estimating the number of applicants through reputation and awareness from domestic and international locations. While converting admissions offers to actual students, we have used binomial distribution. <br />Apart from this, we have used the following formulas<br />Revenue =Average Tuition*Class size<br />Costs = Fixed Cost + Variable Cost<br />Profit = Revenue – Costs<br />We have also taken in to account over capacity in our model. Preferred value for over capacity is zero since we would not like to return any students on the day of registration.<br /> <br />Modeling outcome<br />We have run the simulation over a period of ten years for 1000 times using YASAI and monitored two outcomes using simoutput: Profit and over capacity. <br />YASAI gives us the maximum profit for the class size 300, however the over capacity is 43. This level of over capacity is not acceptable and hence second best option is considered with class size of 270 which gives an over capacity of close to zero. <br />Business impact<br />Currently the profit from the MBA program has been estimated to be around $3M per year. If the class size is increased, this profit would go up to $6.7M per year over the next ten years. So, from the point of view of profit, class expansion seems to be the next logical step. <br />However, we should keep in mind some other aspects while taking the final decision. Queen’s is the number 1 business school in Canada and has been ranked in the top 2 spots in BusinessWeek rankings for many years. Students come to Queen’s due to its unique offering: small class size, personalized attention, integrated approach to learning and emphasis on fitness. The MBA office knows every student by name. The relationship between students and faculty has also been extremely close due to the small class size. The school may lose its uniqueness if it increases the class size from 120 to 270 in one go. Prospective students may not perceive Queen’s the same way they did before. This may actually impact the quality of the applicants in the coming years. Since the placement rate is directly correlated with the quality of the students, this in turn would get impacted negatively and hence the quality of the applicants would further decrease. Over a period of time, this may severely damage the brand which has been built over the years. <br />Analysis<br />Advantages and Benefits<br /><ul><li>The model gives us a very good starting point to consider some of the qualitative aspects discussed before.
  34. 34. The model takes in to account most of the quantitative aspects of the case.
  35. 35. The data collection process and analysis involved in the modeling exercises gives us an opportunity to think critically on the current situation and if some of aspects could be improved upon.
  36. 36. Some of the benefits related to the expansion have been analyzed: more diverse class, global reach, better job opportunities, stronger alumni base and stronger presence in the industry. </li></ul>Disadvantages and Limitations <br /><ul><li>The model doesn’t allow us to take in to account many qualitative factors which are equally important while assessing the current situation
  37. 37. How the prospective applicants would perceive the new class size?
  38. 38. How the recruiters and industry would see this change?
  39. 39. How would the alumni see this?
  40. 40. Would there be any compromises in terms of quality of education imparted?
  41. 41. Would there be any long term implications to the Queen’s brand due to this change?
  42. 42. How would the school attract the additional high quality applicants from other top ranked global business schools?
  43. 43. The model does not consider various aspects of diversity in current form
  44. 44. Experience levels
  45. 45. Professional backgrounds
  46. 46. Educational backgrounds
  47. 47. Gender diversity
  48. 48. We could not come up with a comprehensive cost structure due to confidentiality reasons.
  49. 49. The model does not incorporate various cyclical trends during the admission cycle: applications, offer rollout, offer acceptance etc.
  50. 50. The model does not incorporate the last minute no-shows after the acceptance of offer.</li></ul>Conclusion <br />After carefully assessing Queen’s strategic position against its competition and analyzing the tangible benefits from the modeling exercise, team T-412 recommends to the MBA office to be conservative while considering the class size expansion. Instead of expanding the class size from 120 to 270, we suggest MBA office to expand the class in a multi-phased manner in the next 3-5 years. This approach will allow MBA office to design and execute its branding strategies in a way to maintain Queen’s competitive advantage against other top ranked schools in North America and globally as well. <br />Future work<br />This modeling exercise was done to get a reasonable idea of the implications of the options at hand. Though the outcomes of this model can be used to make some initial estimates, there is a fair amount of scope to improve the model. We would like to work on some of the areas as described in the Analysis section to expand on the scope of this model and get more insights in to the decision making process. Here are some of those areas: <br /><ul><li>Quality of the incoming students and its impact on the reputation
  51. 51. Impact on the placements rates with the class size increase and its sensitivity on the class size
  52. 52. Diversity of the incoming class in a more holistic way
  53. 53. Convince stake holders (MBA office, Finance) to share more data with us to incorporate a better cost structure and come up with a more robust model to make decisions
  54. 54. Incorporate last minute no-shows in the model to get a more clear picture of the situation </li></ul>Appendix <br />