University System of Georgia. FORMAL PROPOSAL FOR A NEW DEGREE PROGRAM (Traditional/Face-to-Face Delivery)

Transcription

1 University System of Georgia FORMAL PROPOSAL FOR A NEW DEGREE PROGRAM (Traditional/Face-to-Face Delivery) Institution: Georgia State University Approval by President or Vice President for Academic Affairs: Risa Palm, October 23, 2013 Date: July 30, 2013 School/Division: J. Mack Robinson College of Business Department: Dean s Office Departmental Contact: Dr. Richard Phillips, Associate Dean Name of Proposed Program/Inscription: Master of Science in Analytics Degree: Master of Science in Analytics (MSA) Major: None CIP Code: Management Science and Quantitative Methods, Other Anticipated Implementation Date: Fall 2014 Approval by Chief Business Officer (or designee): Contact Information: Approval by Chief Facilities Officer or designee (if different from CBO): Contact Information:

2 1. Description of the Program s Fit with the Institutional Mission, Existing Degrees and Majors The mission of the Robinson College of Business is to ensure a diverse set of students emerges prepared to deliver value in business, government and non-profit organizations. (RCB Vision 2020 accepted by the faculty in 2012). Societies in general and businesses in particular now realize that Big Data transcends our current ability to both envision and define the destination of the journey collectively undertaken in the area of capturing, and learning from, the proliferation of digital information. The resulting pace of innovation impacting a variety of settings is highly rapid because the underlying technologies that enable the analysis of Big Data are mostly software and algorithms. Put simply: Big Data is big and the shift taking place not only impacts business, but also all sectors of the economy and world geographies. According to the Director of the National Science Foundation, Dr. Subra Suresh, "Data are motivating a profound transformation in the culture and conduct of scientific research in every field of science and engineering. He further suggests that American scientists must rise to the challenges and seize the opportunities afforded by this new, data-driven revolution. 1 We propose to offer a graduate program specifically designed to produce technically proficient graduates with the skills necessary to identify and leverage the business opportunities provided by Big Data across a range of application domains. The Master of Science in Analytics will develop competencies in the management and analysis of Big Data that can be used by business in a variety of domains. Doing so requires students to learn how to acquire, organize and model data in order to formulate business plans and guide decision-making in corporate and non-corporate settings. At present this program does not exist in the college, but the college s existing faculty are well-equipped to offer such a program for the benefit of Georgia s students, businesses, and the State economy. 2. Program Description and Goals The mission of the Master of Science in Analytics is to educate students how to acquire, organize, model, and analyze data sets in order to formulate the questions and develop answers that guide decision-making in corporate and non-corporate settings. 2.a Institutional Priority Development of this program is an institutional priority for at least four reasons. First, relatively few business and data analytics programs are currently available, but the demand for data scientists is growing rapidly. Graduates from this program will be ideal candidates for the range of technical data-driven positions in a variety of industries/businesses currently emerging such as data scientist, quantitative marketing analyst, credit risk analyst, predictive modeler, informatics and web analytics specialists. Second, employer demand for graduates in this area is spurring other universities in other states to launch business and data analytics master s programs. Relative to these offerings, the program we propose will be similar in purpose but will differentiate itself in several ways. As such, Robinson s MS in Analytics has the potential to develop into a nationally recognized program in the area of business analytics. Examples of other university programs include: o North Carolina State University

3 o o o o o Northwestern - New York University - University of San Francisco - Louisiana State University - Sciences/Pages/MS-Analytics Stevens Institute of Technology - As another example of potential student demand the higher education consulting firm Eduvantis published a report earlier this year entitled Big Data, Big Opportunity for Business Schools where they document the growth of these programs and characterize the elements that distinguish one program from another. 2 Third, the fastest growing segment of graduate business education today is specialized master s programs. According to the Graduate Management Admissions Council (GMAC), 160,500 GMAT score reports were forwarded to U.S. colleges and universities in support of applications to specialized master s programs in 2012 an increase of 15 percent from the prior year and up 86 percent over the past five years (GMAC 2012). Robinson has been and is well positioned to take advantage of these opportunities as the enrollment in our own specialized master s programs is up 45 percent in the past five years with our portfolio of programs attracting over 600 students in spring Continuing to grow graduate enrollment at this rate is an institutional priority for both the Robinson College of Business specifically and Georgia State University more generally. The final reason this program is important is because it is just one element of a portfolio of initiatives approved by the the president of Georgia State University designed to position the university as a leader in the application of technologies/modeling to Big Data in key problem domains. A number of GSU units will support and are already engaging efforts to create a broad interdisciplinary and trans-disciplinary research effort and the development of new and innovative academic programs. Several initiatives designed to realize this vision are already underway. For example, in spring 2013 the president of Georgia State University approved a set of proposals that seek to hire three senior faculty members with expertise in big data analytics as part of the university s Second Century Initiative. 3 The candidates will be appointed in relevant departments in either the Robinson College of Business or the College of Arts and Sciences. The search committees charged to identify and recruit qualified candidates were formed in summer 2013 and position descriptions are already written and about to be distributed. When these new senior faculty hires arrive they will have good company as earlier Second Century Initiative grants were approved in the methodologically related areas of Bioinformatics, Health Information Technology, and Evidence-based Policy Making. A related initiative is the goal to establish Robinson s Marketing Department as a center of excellence in marketing analytics research. The initiative began with the establishment of the Center for the Excellence in Brand and Customer Management and the appointment of its director Professor V. Kumar. Dr. Kumar, 2 A summary of the report where is online at 3 The Second Century Initiative is designed to attract 100 new high impact research scholars over a five year time period to coincide with the 100 th year since the founding of the university. Additional information about the initiative and the positive impact that it is already having on Georgia State s research environment is available online at 3

4 Regents Professor and the Richard and Susan Lenny Distinguished Chair Professor of Marketing, is known as one of the creators of Customer Lifetime Value an analytical marketing technique that he and his coauthors have developed over many years. He was recently ranked amongst the top 5 marketing scholars worldwide based on his research productivity as he has co-authored over 200 articles that appear in premier journals of marketing such as the Harvard Business Review, Journal of Marketing, Journal of Marketing Research, Marketing Science, and Operations Research. Since his arrival the Robinson College has added new junior faculty members with research interests and skills that extend and complement the work of the Dr. Kumar s center and, more generally, to build the reputation of the department. Recent new faculty hires come from well-regarded universities including the University of Texas at Austin, Cornell University, Columbia University, and Hong Kong University of Science and Technology among others. Our success attracting these faculty members, top candidates in the market in the years of their graduation, illustrate the recent leadership added to the college in the big data analytics space that we can draw upon with the launching of the M.S. in Analytics. As a result of these and other related efforts, the launching of the M.S. in Analytics is a natural programmatic extension of the research profile of both the college and the university. 2.b Brief description of the program and how it is to be delivered The program is designed as a three-semester, full-time, lock-step, cohorted offering. Students will complete 26 credit hours of required courses and six credit hours of approved elective course work. It will be delivered primarily in a face-to-face format with some online elements when doing so will serve the students well. Students will also have the opportunity to attend non-credit seminars for leadership, professional development, and career placement purposes. 2.c Goals/objectives of the Program Robinson s Master of Science in Analytics program will differentiate from similar programs in at least four important ways. First, the program will have a Dual-Core design where students will master both the programming skills and the analytical modeling tools necessary for application in business across a broad array of purposes. Second, the program will be technically rigorous but in business context. Many modeling-based programs provide students with advanced skills to needed to manage data and build models. Robinson s program will differentiate as it also emphasizes the need for graduates to understand how to formulate an executable business plan that will turn the model into value. Third, we will leverage Robinson s size and breadth of program offerings to provide students access to a unique set of application courses across a variety of important domains. Students will have access to unique course work in marketing analytics, finance, risk management, health information technology, and logistics and supply chain management. Finally, given that Big Data happens in the real world and it is in the hands of government and public and private companies, Robinson s deep connections to the business community will give the program we propose a fourth important differentiator. Robinson has built a network of public and private companies that will provide students the opportunity to demonstrate their ability to turn data in value before they graduate. 2.d Location of the program main campus or other approved site 4

5 The majority of the course work will be offered on Robinson s Buckhead Executive Education Center. Required and/or elective courses offered by departments in other colleges will be offered on Georgia State s main campus. 3. Curriculum 3.a Curriculum: List the entire course of study required and recommended to complete the degree program. Provide a sample program of study that would be followed by a representative student. Include Area F requirements (if applicable). Clearly differentiate which courses are existing and those that are newly developed courses. Include course titles as well as acronyms and credit hour requirements associated with each course. The MS in Analytics is an eleven-course 32 credit hour program. Nine courses are required and students must choose two electives. Six of the nine required courses were developed specifically for this program. Program of Study A maximum of 9 semester hours of transfer credit is possible in this 32-hour program. Each student's program must be planned in consultation with a faculty adviser and a copy of the program filed with the Office of Graduate Admissions and Student Services for review and approval. Progress toward the degree, including clearance for graduation, cannot be confirmed without an approved program of study. The program of study should be planned before the student takes a non-required course. Any changes in the program must be approved by the faculty adviser and a copy of the changes sent to the GASS. Foundation Requirements All M.S. in Analytics students will complete the Business Communication Skills Requirement. The following foundation courses are in addition to the 32 hours required for the M.S. in Analytics. They are assigned as part of the admissions process based on a review of each student's transcripts. They can be exempted if equivalent work has been previously completed with grades of C or higher. Accounting: Financial and managerial accounting principles (MBA 8025, or Acct 2101 and Acct 2102) Behavioral Science: Management principles (MBA 8165, or MGS 3400). Students may satisfy this requirement with either management (MGS 3400), sociology (Soci 1101), or psychology (Psyc 1101) principles. Economics: MBA 7035 Economics for Managers or both macroeconomic principles (Econ 2105) and microeconomic principles (Econ 2106). Mathematics: Students must have completed three semesters of advanced calculus (Math 2211, Math 2212, and Math 2215). Statistics: Students must have Econ 8710 or completed two semesters of undergraduate mathematical statistics (Math 4751, Math 4752). Required Courses (26 hours): MSA 8000 Consumer and Managerial Decision Making (3) (NEW) MRM 8000 Introduction to Analytical Programming and Numerical Methods (2) (NEW) CIS 8040 Database Management Systems (3) MSA 8050 Unstructured Data Management (3) (NEW) MSA 8100 Operations Research Models and Methods (3) (NEW) MGS 8040 Data Mining (3) ECON 9720 Econometrics II (3) MSA 8200 Econometric Modeling for Analytics (3) (NEW) MSA 8300 Value Through Analytics: Model Deployment and Life Cycle Management (3) (NEW) 5

6 Elective Courses (6 hours) Students will select at least two elective courses. These courses can be in an application area of interest or the student can select courses to deepen their technical skill development. Students electives choices must be approved in advance by the faculty adviser for M.S. in Analytics. Examples of possible electives include the following: CIS 8020 Systems Integration (3) CIS 8100 Management of Information Systems (3) CIS 8200 Information Systems Strategy (3) FI 8000 Valuation of Financial Assets (3) FI 8200 Financial Derivatives (3) FI 8260 Hedge Fund Strategies (3) FI 8320 Corporate Financial Strategy (3) HA 8160 Health Care System (3) HA 8550 Health Planning and Financial Management (3) HA 8620 Operations Management and Quality in Health Care (3) HA 8670 Health Information Systems (3) MK 8010 Marketing Metrics (3) MK 8705 Digital Marketing Analytics (3) MK 8715 Brand and Consumer Analytics (3) MK 8730 Marketing Engineering (3) MRM 8610 Financial Engineering (3) MRM 8620 Quantitative Financial Risk Models (3) MGS 8730 Project Management (3) MGS 8740 Operations Strategy (3) RMI 8050 Risk Management Modeling (3) RMI 8300 Predictive Risk Models (3) The sample program of study is shown on the following page. 3.b and 3.c Course descriptions See appendix. 3.d Provide documentation that the program and all courses in the proposed curriculum have been approved by all relevant campus curriculum governance bodies. The Robinson College faculty approved all courses and the associated degree requirements at the spring faculty meeting held on April 12, e Append materials available from national accrediting agencies or professional organizations as they relate to curriculum standards for the proposed program. See appendix. Summer I MS Analytics Course Sequence 6

7 Econ 8710 Statistical Foundations for Econometrics (if needed) MRM 8000 Intro to Analytical Programming and Numerical Methods Fall 1 CIS 8040 Database Management Systems MSA 8000 Consumer and Managerial Decision Making MSA 8100 Operations Research Models and Methods ECON 9720 Econometrics II Spring I MSA 8050 Unstructured Data Management MSA 8200 Econometric Modeling for Analytics MGS 8040 Data Mining Elective 1 Summer 2 Elective (optional) Internship Fall 2 MSA 8300 Value Through Analytics: Model Deployment and Life Cycle Management Elective 2 3.f Indicate ways in which the proposed program is consistent with nationally accepted trends and standards in the discipline. The proposed program is consistent with the accreditation standards of the Association to Advance Collegiate Schools of Business (AACSB), in particular Standard 9. The relevant requirements of Standard 9 are the General Skills Area and the Specialized Business Master s Degree Programs as follows: General Skills Areas Written and oral communication (able to communicate effectively orally and in writing) Ethical understanding and reasoning (able to identify ethical issues and address the issues in a socially responsible manner) Analytical thinking (able to analyze and frame problems) Information technology (able to use current technologies in business and management contexts) Interpersonal relations and teamwork (able to work effectively with others and in team environments) Diverse and multicultural work environments (able to work effectively in diverse environments) Reflective thinking (able to understand oneself in the context of society) Application of knowledge (able to translate knowledge of business and management into practice) Specialized Business Master s Degree Programs In addition to the general skill areas, specialized business master's degree programs would normally include learning experiences in the following areas Understanding the specified discipline from multiple perspectives Framing problems and developing creative solutions in the specialized discipline Applying specialized knowledge in a global context (for practice-oriented degrees) or Conducting high-quality research (for research-oriented degrees) 7

8 The program of study we propose will meet or exceed each of the standards listed above for researchoriented degrees. The program will be assessed according to learning objectives developed based on these AACSB standards. 3.g If internships or field experiences are required as part of the program, provide information documenting internship availability as well as how students will be assigned, supervised, and evaluated. The primary field experience for students in this program will be a practicum course that will serve as the capstone. The field experience will be conducted in partnership with numerous Atlanta-based firms and governmental agencies. These include partners in the field of public safety (Atlanta Police Foundation) and business partners such as Suntrust, Lexis-Nexus, Delta, GE and others. The college is well positioned to secure the assistance of these partners, given our strong relationships in the business community. The instructor for the capstone course will monitor the students completing these projects and will assure a valuable learning experience for these students. 3.h Indicate the adequacy of core offerings to support the new program. All core courses are available at the time when needed to promote students through the program according to the 15-month time to completion. 3.i Indicate the method of instructional delivery. Instruction will be primarily classroom-based delivery. Where relevant, individual faculty will be encouraged to hybridize course delivery to allow for more problem-based instruction in the classroom. 3. Admissions Criteria: Please include required minima scores on appropriate standardized tests and grade point average requirements. Applicants will hold an undergraduate degree from an accredited college or university. We will target students with degrees primarily coming from three groups: Group 1: Math, Engineering, Statistics, Computer Science, and similar degrees Group 2: Economics and Business degrees from quantitative-oriented schools (e.g., the Georgia Institute of Technology, Duke University, etc.); and Group 3: Although we believe most applicants will come from Group 1 or Group 2, we anticipate occasional applicants who hold Ph.D.s, coming from pre-med, biology, etc. An undergraduate GPA of 3.5 or higher is expected. Applicants will submit either a GMAT or a GRE score in order to seek admission to the program. We will seek highly talented students with GMAT/GRE Quantitative Percentiles greater than 75 percent and GMAT/GRE Verbal Percentiles greater than 65 percent. Candidates will also have to have a demonstrated interest in computers, technology, etc. Candidates will be chosen based on GPA and GMAT or GRE scores, other relevant materials and the results of an interview conducted by members of the admissions committee. Professional experience will not be required. 5. Availability of Assistantships 8

9 Any enrolled student will be eligible to seek a graduate assistantship once on campus. In addition, the Office of Graduate Recruiting will be allocated a small number of assistantships that it can award during the admissions process to help attract highly qualified students. 6. Evaluation and Assessment 6.a Provide the student learning outcomes and other associated outcomes of the proposed program. Through this Master of Science in Analytics program, we seek to develop professionals who: 1. Demonstrate a mastery of data analytics technologies, tools and methodologies 2. Demonstrate a mastery of general business concepts in the global environment 3. Demonstrate critical thinking and problem solving skills 4. Demonstrate well-developed communication skills 5. Demonstrate the ability to use appropriate technology in business situations 6. Demonstrate the ability to successfully work in diverse teams 7. Demonstrate the ability to recognize and critically reflect on ethical dilemmas and act accordingly See appendix for assessment of learning outcomes. 6.b Describe how the institution will monitor and ensure the quality of the degree program. Program quality will be monitored and assessed by an assessment committee made up of faculty members participating in the program and chaired by the faculty advisor to the program. 7. Administration of the Program 7.a Indicate where the program will be housed within the academic units of the institution. As an interdisciplinary program, the MSA program will be housed within the Dean s office in the J. Mack Robinson College of Business at Georgia State University. 7.b Describe the administration of the program inclusive of coordination and responsibility. Administration of the MSA program will be conducted by the student services team and the admissions team located in the Office of Graduate Students Recruiting & Student Services with oversight by the Assistant Dean for Graduate Recruiting & Student Services. The academic director will be assigned by the Associate Dean for Academic Initiatives and Innovation. 8. Waiver to Degree-Credit Hour: If the program exceeds the maximum credit hour requirement at a specific degree level, then provide an explanation supporting the increase of hours (NOTE: The maximum for bachelor s degrees is 120-semester credit hours and the maximum for master s degrees is 36-semester credit hours). Not Applicable 9. Accreditation: Describe the program s alignment with disciplinary accreditation requirements and provide a time line for pursuing accreditation. Indicate the source of institutional funding that will be used, if needed, for the accreditation process. The MSA program will be added to the portfolio of Robinson College programs, all currently accredited by the Association to Advance Collegiate Schools of Business, International (AACSB). The College goes through a maintenance of accreditation process every five years so the next cycle occurring in the 9

10 2014/2015 academic year will include the MSA program. As discussed above, the program s design is consistent with the relevant AACSB standards for specialized business master s programs. 10. External Reviews (This item only applies to doctoral level programs): Provide a list of five to eight reviewers, external to the System, from aspirational or comparable programs/institutions. This list should contain contact information for each reviewer, and include an explanation of why the reviewer was suggested. The list should not include individuals for whom the department or institution has consulted during the process of program proposal development. Not applicable. 11. Enrollment Projections and Monitoring 11.a Provide projected enrollment for the program during the first three years of implementation. (NOTE: These projections will be used to monitor enrollment following program implementation.) We anticipate matriculating approximately 25 students in the first year of the program. Early evidence from other universities offering similar programs indicates that after the first year, we would be able to grow enrollments to as much as 40 per year. A table summarizing our enrollment projection by year is below. Enrollment Projection Student Majors First Cohort Second Cohort Third Cohort Fourth Cohort Shifted from other programs Number of new students Total Majors Course Sections Previously Existing New Total Program Sections Credit Hours Previously Existing New Total Credit Hours 650 1,190 1,400 1, b Explain the specific methodology used to determine these projections and verify their accuracy, especially if new student enrollment will be needed to sustain funding for the program. Indicate whether enrollments will be cohort-based. Enrollment projections are based upon our experience attracting students to existing cohort-based MS programs. At this time the Robinson College of Business offers 15 cohort graduate programs (MS and MBA) of which several have been newly developed and successfully launched over the past several years. Given the growth of our own graduate programs and of similar business analytics programs at universities 10

11 in other states, we are confident that we can achieve the enrollment numbers set out in the budget table shown later in this proposal. 12. Provide the year when the program is expected to be reviewed in the institution s comprehensive program review process. The college s next AACSB accreditation review will be conducted in The program would be added to the University s Academic Program Review schedule and would be expected to be reviewed when the college s other college-wide graduate program (the MBA program) is scheduled to be reviewed. 13. Describe anticipated actions to be taken if enrollment does not meet projections. Based on our research and on the growing importance of Big Data for organizations in the State of Georgia as well as nationwide and worldwide, we have every reason to expect that enrollment will meet or exceed the projections. We have a number of actions we could take if enrollment does not meet these projections. For example, we could refocus our promotion and marketing of the program to better communicate its value to potential students. We could retool the course work to better appeal to students and employers. 14. Faculty Qualifications & Capacity 14.a Provide an inventory of faculty directly involved with the program. On the list below indicate which persons are existing faculty and which are new hires. For each faculty member, provide the following information. Faculty Name Richard Luger Satish Nargundkar Richard Phillips Rank Associate Professor of Risk Management and Insurance Clinical Associate Professor of Managerial Sciences C.V. Starr Professor of Risk Management and Insurance, and Associate Dean of Academic Initiatives and Innovation Highest Degree Ph.D. University of Montreal Ph.D. Clemson University Ph.D. University of Pennsylvania Degrees Earned Ph.D. M.A. B.Sc. Ph.D. B.Eng. Ph.D. M.A. B.S. Academic Discipline Economics Industrial Management Managerial Economics Area of Specialization Econometrics, Financial Econometrics, Computational Methods Data mining, Quantitative methods, Decision support systems Risk Management Finance Economics Current Workload 100% FTE 100% FTE 100% FTE 11

12 Balasubraman Ramesh Harley Ryan Subhashish Samaddar Board of Advisors Professor of Computer Information Systems Suntrust Associate Professor of Finance Professor of Managerial Sciences Ph.D. New York University Ph.D. Georgia State University Ph.D. Kent State University Ph.D. M. Phil. M.B.A. B.Eng, Ph.D M.B.A. B.S. Ph.D. M.B.A. B.Eng. CIS Finance Operations Research Software engineering Computer supported collaborative work Corporate Finance Contracting & Compensation Knowledge management, Information technology Decision strategy 100% FTE 100% FTE 100% FTE Senior Faculty Hire To be determined Clinical To be determined Professor/Instructor Note: In addition to the core faculty development team, MSA students will have the opportunity to take elective course work in a number of relevant areas within the college in courses we already offer. The primary elective courses are expected to come from the departments of Marketing, Risk Management and Insurance, Health Administration, Finance, and Managerial Sciences. The faculty members associated with these courses are existing faculty members. Further it is anticipated that the college will not need to offer any additional sections of these elective courses as we currently have excess seat capacity in these courses. Total Number of Faculty: 8 14.b If it will be necessary to add faculty to support the program, give the desired qualifications of the persons to be added, and a timetable for adding new faculty. We anticipate two faculty hires will be made who will support the launch of this new program. The first will be a senior faculty hire who will join the college as part of the university s Second Century Initiative. Minimum requirements for a qualified candidate will be an earned Ph.D. in a business-related analytical discipline, an outstanding research record and scholarly reputation, including evidence of external funding levels appropriate to the candidate s discipline, and a demonstrated ability of teaching. Ideal candidates will have significant academic experience, a deep understanding of the technologies and analytical methodologies relevant to Big Data, and demonstrate a coherent and high-impact research focus. The search committee charged to identify and recruit qualified candidates was formed in summer 2013 and a position description has already been written and is about to be distributed. The second position will be a non-tenure track faculty hire who will provide additional teaching capacity and who will be charged to work as a conduit from the students in the M.S. in Analytics program to the relevant professional communities. Making this hire will also provide degrees of freedom that we can use to move the appropriate faculty into the new course work that are part of the program and still cover existing course work using full time faculty members. The minimum requirements for a qualified candidate will be an earned Ph.D. either in managerial sciences, operations research, or in computer information systems where the ultimate choice of field may depend upon the senior faculty hire. The search committee charged to identify and recruit qualified candidates will be formed later in the academic year as progress is made on the senior faculty hire. 12

13 14.c If existing faculty will be used to deliver the new program, include a detailed faculty load analysis that explains how additional courses in the new program will be covered and what impact the new courses will have on faculty current workloads. (For example, if program faculty are currently teaching full loads, explain how the new course offerings will be accommodated.) The two new hires will provide teaching capacity for eight new sections per academic year. In year one we need to cover four sections of new course work and five sections of existing course work. Of these nine classes, excess capacity currently exists to accommodate the additional forecasted enrollment in two courses (MRM 8000 and the elective course). Thus, the new hires provide one course of excess teaching capacity in the first year. Years 2-4 of this program will require us offering 11 new courses of which three have excess capacity to absorb the new students (MRM 8000 and the two elective courses). Thus, in steady state, the new hires provide the necessary teaching capacity to launch the new program without cannibalizing existing programs. Furthermore, given the highly interdisciplinary nature of the program, we expect future hiring beyond the first year will likely lead to faculty members with skill sets relevant for this program. 15. Budget 15.a.1 Expenditures: Provide a description of institutional resources that will be required for the program (e.g., personnel, library, equipment, laboratories, supplies, and capital expenditures at program start-up and recurring). The primary physical resources required for this program are classrooms and computer laboratories where students can work. Specifically, we plan to offer the program at Robinson s Executive Education Center in Buckhead during day-time hours when the facility currently has excess classroom capacity. In addition, the college recently signed a lease for three additional floors in that building that will, in part, be used to provide the computer laboratory where students in this program and in other programs will work. The primary case to expand the Buckhead Facility is being made to ease the capacity shortage that currently exists for our programs targeted to working professionals taking classes in the evenings and on weekends. Thus, the capital expenditure associated with the expansion is not being charged to the M.S. in Analytics as this program will only absorb times when the facility has excess capacity. The amount of salary for the two new faculty hires included in the M.S. in Analytics budget was calculated assuming 80 percent (25 percent) of the clinical faculty member s (the senior faculty member s) effort will be allocated to the program. The amount of salary in the budget for the existing faculty members who will teach in the program was calculated by multiplying the average salary of a faculty members employed in the Robinson College of Business times 12.5 percent times the number of courses needed to offer the program beyond the capacity provided by the new hires (one in the first year and three for all remaining years). Beyond the two new faculty hires already discussed, we anticipate hiring two additional staff positions to support the launch and ongoing running of this program. These hires will become part of the Office of Graduate Recruiting and Students Services. No new research resources are required to launch this program as the library already subscribes to the requisite scholarly and professional journals relevant for this field. Likewise, the university already has 13

14 site licenses to the requisite software that includes MS Office, SAS, Matlab, and the statistical package R is available online as free software. 15.a.2 Expenditures: If the program involves reassigning existing faculty and/or staff, include the specific costs/expenses associated with reassigning faculty and staff to support the program (e.g. cost of part-time faculty to cover courses currently being taught by faculty being reassigned to the new program or portion of full-time faculty workload and salary allocated to the program). We do not expect to hire additional part-time instructors as a result of launching this program. In addition, no existing staff members will be reassigned to support this project as we plan to hire additional staff. 15.b.1 Revenue: If using existing funds, provide a specific and detailed plan indicating the following: 1) source of existing funds being reallocated; 2 how the existing resources will be reallocated to specific costs for the new program; and 3) the impact the redirection will have on units that lose funding. This program will rely upon a program fee that will cover tuition and other expenses of the program. No existing funds will be reallocated to support this new program. 15.b.2 Explain how the new tuition amounts are calculated. In developing our program fee proposal, we also benchmarked the price of this program relative to competing programs in other states. In addition, the fee we are proposing is consistent with the pricing model of the college uses for its existing portfolio of other premium priced specialized master s programs. The program fee will be set by the Board of Regents. 15.b.3 Explain the nature of any student fees listed (mandatory fees, program fees, etc.). The program fee includes mandatory university fees, a graduation fee, and will cover other expenses of the program including the cost of providing ipads to all students, expenses associated with the operating expenses of the Buckhead Facility, student meals and parking, etc. 15.b.4 If revenues from Other Grants are included, please identify each grant and indicate if it has been awarded. Not applicable. 15.b.5 If Other Revenue is included, identify the source(s) of this revenue and the amount of each source. Not applicable. 15.c.1 When Grand Total Revenue is not equal to Grand Total Costs, explain how the institution will make up the shortfall. In the short term, the Robinson College of Business is committed to make up any possible shortfall that may come from running this program by reallocating its budget to accommodate the shortfall. Like any premium-priced program, the college will re-evaluate its commitment to continue offering the program if the appropriate enrollment levels are not reached. 15.c.2 If the projected enrollment is not realized, provide an explanation for how the institution will cover the shortfall. 14

15 In the short term, the Robinson College of Business is committed to make up any possible shortfall that may come from running this program by reallocating its budget to accommodate the shortfall. Like any premium-priced program, the college will re-evaluate its commitment to continue offering the program if the appropriate enrollment levels are not reached. III. REVENUE SOURCES First Second Third Fourth FY Dollars FY Dollars FY Dollars FY Dollars Source of Funds Reallocation of existing funds (see 15 b.i) New student workload Number of students New Tuition (see 15 b.ii) (number of students x $39,000) $975,000 $1,560,000 $1,560,000 $1,560,000 Federal funds Other grants (see 15 b.iv) Student fees (see 15 b.iii) Other (see 15 b.v) New state allocation requested for budget hearing Nature of Funds Base budget One-time funds GRAND TOTAL REVENUES (see 15 c.i & c.ii) $975,000 $1,560,000 $1,560,000 $1,560,000 15

16 I. EXPENDITURES First Second Third Fourth FY Dollars FY Dollars FY Dollars FY Dollars Personnel reassigned or existing positions Faculty (see 15.a.ii) $18,750 $56,250 $56,250 $56,250 Part-time Faculty (see 15 a.ii) Graduate Assistants (see 15 a.ii) (3 GRAs) Administrators(see 15 a.ii) Support Staff (see 15 a.ii) Fringe Benefits $5,625 $16,875 $16,875 $16,875 Other Personnel Costs Total Existing Personnel Costs $24,375 $73,125 $73,125 $73,125 EXPENDITURES (Continued) Personnel new positions (see 15 a.i) Faculty $147,000 $147,000 $147,000 $147,000 Part-time Faculty Graduate Assistants $15,000 $15,000 $15,000 $15,000 Administrators $45,000 $45,000 $45,000 $45,000 Support Staff $30,000 $30,000 $30,000 $30,000 Fringe Benefits $46,385 $56,925 $56,925 $56,925 Other personnel costs $18,000 $18,000 $18,000 $18,000 Total New Personnel Costs $301,385 $311,925 $311,925 $311,925 Start-up Costs (one-time expenses) (see 15 a.i) Library/learning resources Equipment Other (Recruitment, advertising) $50,000 Physical Facilities: construction or renovation Total One-time Costs $50,000 Operating Costs (recurring costs base budget) (see 15 a.i) GSU Tuition (32 hours x $449 per hour) $359,200 $574,720 $574,720 $574,720 GSU Student Fees (students x number of semesters x $1064) $79,800 $127,680 $127,680 $127,680 GSU Graduation Fee (number of students * $50) $1,250 $2,000 $2,000 $2,000 Supplies/Expenses (Buckhead Center facility cost, office supplies, student parking, meals, etc.) $148,675 $237,880 $237,880 $237,880 Travel $1,000 $1,000 $1,000 $1,000 Equipment (I-Pads) $15,000 $24,000 $24,000 $24,000 Library/learning resources (Textbooks, research databases, student assessment tools, etc) $51,700 $82,720 $82,720 $82,720 Other (Student recruitment, advertising) $100,000 $100,000 $100,000 Total Recurring Costs $656,625 $1,150,000 $1,150,000 $1,150,000 GRAND TOTAL COSTS $1,032,385 $1,535,050 $1,535,050 $1,535,050 16

17 16. Facilities Complete the table below. Total GSF a. Indicate the floor area required for the program in gross square feet (gsf). When addressing space needs, please take into account the projected enrollment growth in the program over the next 10 years. b. Indicate if the new program will require new space or use existing space. (Place an x beside the appropriate selection.) Type of Space Comments i. Construction of new space is required ii. Existing space will require modification iii. If new construction or renovation of existing space is anticipated, provide the justification for the need. iv. Are there any accreditation standards or guidelines that will impact facilities/space needs in the future? If so, please describe what the impact will be. v. Will this program cause any impacts on the campus infrastructure, such as parking, power, HVAC, etc. If so, indicate the nature of the impact, estimated cost and source of funding. vi. Existing space will be used as is c. If new space is anticipated, provide information in space below. i. Estimated construction cost ii. iii. iv. Estimated total project budget cost Proposed source of funding Availability of funds v. When will the construction be completed and ready for occupancy? (Indicate semester and year). vi. How will the construction be funded for the new space/facility? vii. Indicate the status of the Project Concept Proposal submitted for consideration of project authorization to the Office of Facilities at the BOR. Has the project been authorized by the BOR or appropriate approving authority? d. If existing space will be used, provide information in space below. Provide the building name(s) and floor(s) that will house or support the program. Indicate the campus, if part of a multi-campus institution and not on the main campus. Please do not simply list all possible space that could be used for the program. We are interested in the actual space that will be used for the program and its availability for use. The Buckhead Executive Education Center will be the primary location for this program. 17

18 e. List the specific type(s) and number of spaces that will be utilized (e.g. classrooms, labs, offices, etc.) i. No. of Spaces Type of Space Number of Seats Assignable Square Feet (ASF) Classrooms Labs (dry) Labs (wet) Meeting/Seminar Rooms Offices Other (specify) Total Assignable Square Feet (ASF) ii. If the program will be housed at a temporary location, please provide the information above for both the temporary space and the permanent space. Include a time frame for having the program in its permanent location. Chief Business Officer or Chief Facilities Officer Name & Title Phone No. Address Signature Note: A Program Manager from the Office of Facilities at the System Office may contact you with further questions separate from the review of the new academic program. 18

19 APPENDIX FOR SECTION 3b Existing Course Descriptions ECON 8710 Introduction to Statistical Foundations for Analytics and Econometrics Prerequisites: Basic statistics, multivariate calculus This course provides probability and statistical tools necessary for studying analytics and econometrics at graduate level. Topics covered include basic techniques of probability theory, estimation, hypothesis testing, and estimation methods. Applications of these concepts to economic problems and illustrations from business and economics are emphasized. ECON 9720 Econometrics II This course covers econometric techniques with a focus on linear models. Subjects include the classic linear regression model, generalized least squares, instrumental variable methods, and generalized method of moments. An introduction to asymptotic distribution theory is provided. Emphasis is placed on inference and specification testing. Brief introductions to series techniques and binary choice models are included. CIS 8040 Database Management Systems Prerequisites: CIS 3210 or CIS 3260 This course emphasizes database concepts, development, use, and management in three main sections: database concepts, practice, and emerging trends. Relational database systems are the main focus, but other types, including object-oriented databases, are studied. Practical design of databases and developing database applications using modern software tools will be emphasized. This course will also cover the methods of extracting data from disparate databases and sources, the fundamentals of data warehousing, and how to transform data for effective integration into a warehouse. Topics include data capture, cleaning, representation, storage, queries, manipulation, data-warehouse concepts, real-time data management, big data management environments (e.g., Hadoop). Also included, as they apply to structured data environments are data security, governance, visualization. Students will get a hands-on experience identifying data needs and sources including interview techniques, defining variables, determining the time period from which to take sample data, handling missing data, etc. MGS 8040 Data Mining This course covers various analytical techniques to extract managerial information from large data warehouses. A number of well-defined data-mining tasks such as classification, estimation, prediction, affinity grouping and clustering, and data visualization are discussed. Design and implementation issues for corporate data warehousing are also covered. NEW Course Descriptions MSA 8000 Consumer and Managerial Decision Making Prerequisites: Econ 2105 and 2106 This course presents a microeconomic theory of how consumers and managers of companies make economic decisions. The course is organized into two main components. The first provides the model of 19

20 how consumers make individual choices about which products or services to purchase. Topics include preferences and utility theory, demand analysis, and impact uncertainty and incomplete information have on consumer decisions. The second part extends the economic theory of individual decision making to the application of these concepts to contemporary business situations for the purpose of corporate decisionmaking. Topics covered include risk and return analysis, cost of capital, project selection, and capital budgeting techniques. MRM 8000 Introduction to Analytical Programming and Numerical Methods This course is an introduction to analytical programming and numerical methods. The objective is to learn how to develop algorithms and computer code for scientific computing with a view towards the practical application of mathematical models in risk management, insurance, economics, finance, marketing analytics, and related fields. The course emphasizes the principles and numerical techniques used to turn algorithms into reliable and efficient computer programs. Note even though we make use of the R language, the principles and techniques apply to any programming language. MSA 8050 Unstructured Data Management Prerequisite: CIS 8040 Database Management Systems This course addresses the unstructured data management skills needed for modern data analysis including those salient to big data and real-time data environments. The focus is on unstructured data and its environment. Unstructured data includes web data (blogs, text), user generated content, social media, location-aware data, and digital media among others. Topics covered include extraction methods for real time audio and video data, data capture, cleaning, representation, storage, queries, manipulation, and realtime data management. Also included as they apply to unstructured data environment are data security, governance, and visualization. Students will learn natural language processing and geo-spatial analytical tools. MSA 8100 Operations Research Models and Methods Prerequisite: MSA 8010/ MRM 8000 (Introduction to Computer Programming and Numerical Methods) The focus of this course is operations research (OR) as a discipline of applying advanced analytical methods to help make better business decisions. It introduces formulation, solution techniques, and sensitivity analysis for optimization problems that include linear, integer, network flow, non-linear and dynamic programs such as traditional LP/ILP/MILP models, transportation and network models. Students are exposed to multidisciplinary applications from areas including but not limited to logistics, manufacturing, transportation, marketing, project management, health care, urban planning, and finance. Students use software packages to solve linear, integer, and network problems. MSA 8200 Econometric Modeling for Analytics This course introduces students to econometric methods used in business analytics with a focus on realworld applications and datasets. It starts off by discussing econometric methods for panel data, including how to account for basic heterogeneity effects. Subsequently, the course covers some of the most important models used for the analysis of time series, including estimation and inference methods for univariate and vector auto-regressive models. After discussing these models in the classical context, the course revisits them using Bayesian methods with a focus on issues of parameter and model uncertainty. The course closes with a discussion of state-space models and Kalman filtering. 20