CURRICULUM PROPOSAL

BUSINESS ADMINISTRATION: BUSINESS ANALYTICS, B.S.

Item #1 – Deactivate BS: Business Administration: Industrial Management.

Rationale: Significant changes to the program requirements and a change of name warrant deactivation of Industrial Management concentration.

Item #2 – Create a new concentration: “Business Administration: Business Analytics, B.S.”

Rationale: Business Analytics is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. Advances in information technology have enabled companies to collect vast amounts of data. Insightful use of this data to drive decision making and gain competitive advantage is vital for businesses to survive. Tim McGuire of the global business consulting firm McKinsey & Company says, “Analytics will define the difference between the losers and winners going forward.”1 Another McKinsey report states “The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.“2

There is huge regional and local demand for business analytics trained professionals. Chattanooga is one of the metropolitan areas with high potential for job growth in the information technology area. The GIG initiative of the city is expected to further increase the demand for analytics trained professionals. Area businesses such as BCBST, Unum, Volkswagen, and TVA have large and growing data analytic departments.

An important part of the mission of the College of Business is providing quality educational programs that produce academically-prepared and business-world ready men and women for a competitive global environment. This proposal for Business Analytics concentration is one of the steps to fulfill this mission.

1 http://www.mckinsey.com/insights/business_technology/making_data_analytics_work2 http://www.mckinsey.com/features/big_data

CURRICULUM PROPOSAL

BUSINESS ADMINISTRATION: BUSINESS ANALYTICS, B.S.

PROGRAM

General Education The same as all undergraduate Management majors

Program requirementsThe same as all undergraduate Management majors

Required courses: 24 hours includingMGT 3560 - Prescriptive Analytics (Revised course)MGT 3600 - Management Information SystemsMGT 3660 - Business ForecastingMGT 4260 - Introduction to Business Analytics (New course)MGT 4270 - Advanced Business Analytics (New course)MGT 4280 - Supply Chain Management (New course)MGT 4250 - Database and Data warehouse (New course)3 hours from:

MGT 4380 - International ManagementMKT 3180 - International MarketingFIN 4120 - International Finance

Electives: 9 hours chosen from:BUS 3900r - Internship (Only 3 hours)ACC 3050 - Managerial Cost AccountingMGT 3300 - Concepts in Organizational BehaviorMGT 3310 - Organizational Motivation and LeadershipMGT 3320 - Human Resource ManagementMGT 4140 - Managerial Decision-MakingMKT 4150 - Business to Business MarketingECON 4290 - Managerial EconomicsMGT 3760 - Business Simulation (New course)

New courses proposed:MGT 4260 - Introduction to Business AnalyticsMGT 4270 - Advanced Business AnalyticsMGT 4280 - Supply Chain ManagementMGT 4360 - Database and Data warehouseMGT 3760 - Business Simulation (Elective)

CATALOG DESCRIPTION OF PROPOSED NEW COURSES

MGT 3760 Business SimulationMonte Carlo and Discrete-event simulation modeling and analysis of business system. Applications from a variety of business disciplines including marketing, operations, finance, scheduling, and staffing will be discussed. Spring semester. Prerequisites: MGT 3110, junior standing or department head approval. Differential course fee will be assessed.

MGT 4250 Databases and Data WarehousesThis course covers an introduction to organizational databases, database management systems, data warehouses and queries and business reports. Students will become familiar with operational and analytical database systems and design and built simple databases, write queries, and prepare reports for better decision making. Fall semester. Prerequisite: MGT 3600, junior standing or department head approval. Differential Course Fee will be assessed.

MGT 4260 - Introduction to Business AnalyticsThis course will provide an introduction to business analytics. Students will learn how to prepare the data for analytics purposes and understand to use various predictive Analytics approaches. These techniques will be examined in the context of various business applications such as healthcare, marketing, finance, and retailing. Fall semester. Prerequisite: MGT 4250 (or concurrent enrollment), junior standing or department head approval. Differential Course Fee will be assessed.

MGT 4270 - Advanced Business AnalyticsThis course builds on the Introduction to Business Analytics course (MGT 4260) and will describing various methodologies for describing the structured data and applying analytics approaches to understanding unstructured data from disparate sources. Spring semester. Prerequisite: MGT 4250, MGT 4260, junior standing or department head approval. Differential Course Fee will be assessed.

MGT 4280 Supply Chain ManagementConcepts and techniques related to designing and managing supply chains. Topics include Master production scheduling, material requirements planning, capacity requirements planning, logistics, purchasing/sourcing, warehousing, and inventory management. Emphasis on analysis of the competitive environment, distribution network alternatives, and customer service aspects provide a background in each functional area to enable students to pursue their areas of interest. Fall semester. Prerequisites: MGT 3110, junior standing or department head approval. Differential course fee will be assessed.

Item #3: Proposed change of name and description

MGT 3560 Prescriptive Analytics (Current title: Management Science)Concepts and applications of quantitative techniques for business decision making under deterministic and stochastic conditions. The course will focus on model building, analysis, interpretation and decision making using linear programming, integer programming, goal programming, decision analysis, queuing systems, and dynamic programming. Fall semester. Prerequisites: MGT 1000 or CPSC 1000, MGT 2120, MATH 1130 or MATH 1710 with a minimum grade of C or MATH 1720 or MATH 1830 or MATH 1910 or Math ACT score of 26 or better, junior standing, or department head approval. Differential course fee will be assessed.

Current description:Concepts and applications of quantitative (mathematical) techniques, and computer analysis for business decision making under deterministic and stochastic conditions. Topics include mathematical model formulation, linear programming, integer programming, goal programming, transportation problems, assignment problems, network models, project scheduling, decision analysis, queuing, dynamic programming, and Markov processes. Fall semester. Prerequisites: MGT 1000 or CPSC 1000, MGT 2120, MATH 1130 or MATH 1710 with a minimum grade of C or MATH 1720 or MATH 1830 or MATH 1910 or Math ACT score of 26 or better, junior standing, or department head approval. Differential course fee will be assessed.

Goals of Business Analytics (BA) Concentration

The mission of the Business Analytics concentration is to prepare students for a career in Business Analytics. Students who successfully complete the program should be able to use a range of information technologies ranging from spreadsheet software to advanced statistical packages to analyze big data and develop business strategies. In short, a graduate of the BA concentration should possess the expertise to analyze data from multiple sources and help businesses make better decisions.

Students graduating from the BA concentration should demonstrate expertise in the following functional areas within BA:1. Data collection, organization, and preparation2. Static and dynamic data visualization3. Data mining including Cluster Analysis, RFM modeling and Market Basket analysis4. Predictive analytic techniques including Forecasting, Decision Tree, Regression, Logit

regression, and Neural Networks5. Prescriptive analytic techniques including applications such as linear and integer

optimization, nonlinear optimization, optimization models with uncertainty6. Text mining

Further, students graduating from the BA concentration should demonstrate the ability to effectively communicate ideas and concepts in oral presentations, interpersonal relations, and in written formats.

Faculty teaching the courses offered in the BA concentrationCurrent Faculty:Dr. Mohammad AhmadiDr. Beni AsllaniDr. Parthasarati DileepanDr. Ashish GuptaProf. John OsterhageProf. David Witt

New Faculty:One BA analytic faculty will be recruited in the approved line available from retirement.

Financial impact

The college already has the necessary hardware and software resources. Therefore, there will be no financial impact.

CLEAR PATH – Business Administration: Business Analytics, B.S.

Freshman Year Meet with Academic Advisor two times each semester. Go to every class. Contact your instructor if you are absent. Devote enough time to your studies and think about course materials and how they apply to your life. Become actively involved in at least one co-curricular activity.

Fall Semester: Hrs Spring Semester HrsENGL 1010 3 ENGL 1020 3MATH 1130 3 MATH 1830 3Fine Arts 3 Humanities or 2nd Fine Arts 3Cultures and Civilizations I 3 MGT 1000 3Elective Outside of Business 3 Cultures and Civilizations II 3Elective Outside of Business 1

16 15Sophomore Year Confirm your academic major choice and know the requirements and career fields related to your major. Using MyMocsDegree, create course plan for your remaining degree requirements. Involve yourself in learning opportunities that are challenging and relevant.

Fall Semester: Hrs Spring Semester HrsNatural Science with Lab 4 Natural Science non-Lab 3ANTH 1520 or PSY 1010 or SOC 1510 3 THSP 1090 3MGT 2110 3 MGT 2120 3ACC 2010 3 ACC 2020 3ECON 1010 3 ECON 1020 3

16 15Junior Year Participate in study abroad, leadership opportunities, service learning, civic engagement, internships, research

projects, and other learning opportunities. Develop your job or graduate school strategy. Update your graduation plan as necessary.

Fall Semester: Hrs Spring Semester HrsMGT 3560 3 MGT 3110 3MGT 3150 3 MKT 3600 3FIN 3020 3 MGT 3660 3MGT 3130 3 BUS 3350 3MGT 3100 or ENGL 2880 3 Concentration elective 3

15 15Senior Year Complete your Graduation Application with the Records Office.

Fall Semester: Hrs Spring Semester HrsMGT 4250 3 MGT 4400 3MGT 4260 3 MGT 4410 1MGT 4280 3 MGT 4380 3Concentration elective 3 MGT 4270 3

Concentration elective 33000/4000 Elective Outside Business 3

15 13

Item #4: Proposal for the new courses

Syllabi of proposed new courses follow

Department of Management

COURSE: MGT 3760TITLE: Business SimulationPREREQUISITES: MGT 3110CREDIT: 3 hoursFACULTY: Dr. Mo AhmadiTEXTS: 1. Simulation Modeling Using @RISK: Updated for Version 4, 1st

Edition, Wayne L. Winston Indiana University, Kelley School of Business (Emeritus), ISBN-10: 053438059X, ISBN-13: 9780534380595

2. Simulation Using ProModel, 3rd Edition, Charles  R. Harrell, ISBN-13 9780073401300

CATALOG DESCRIPTIONMonte Carlo and Discrete-event simulation modeling and analysis of business system. Applications from a variety of business disciplines including marketing, operations, finance, scheduling, and staffing will be discussed. Spring semester. Prerequisites: MGT 3110, junior standing or department head approval. Differential course fee will be assessed.

COURSE OBJECTIVESThis is a course in Monte Carlo and Discrete-event simulation for undergraduate students. The course will cover modeling, simulation, analysis of results, and use of simulation software such as ProModel and @Risk. Complete design, analysis, and mostly applications of Monte Carlo and Discrete-event simulation experiments will be emphasized. Applications will be taken mostly from manufacturing, healthcare, and service systems. The course will include the basic concepts of simulation as well as more advanced topics, which will make it possible for the students to simulate various systems and thoroughly understand how simulation can aid in better decision making processes. Topics include stochastic models for simulation, use of analytics for designing simulations and output analysis, and random variable and process generation. Other objectives of the course include:

Develop competency in mathematical model formulation. Use computer technologies for simulating various systems. Analyze data and convert data to useful information. Use the information to enhance critical thinking.

COURSE CONDUCTThe course will be conducted primarily in a lecture-discussion manner. Students will have access to computers in class. Therefore, in every meeting, students will work on a simulation project. Homework will be required. Students must have their assignments completed before each class meeting. Assignments that are turned in late (no later than one class period) will receive a maximum of 50% of the credit. It is expected that each student will be prepared for each meeting and will agree with the following policies.

1. Read the assigned chapters and textbook material before coming to class.2. Have the assignments ready to be turned in.3. Be prepared to complete an in-class assessment in every meeting.4. There will be no make-up for the missed daily assessments.5. Missed daily assignments will receive a grade of zero. Assignments that are turned in

late (no later than one class period) will receive a maximum of 50% of the credit.

GRADING SYSTEM

Grade Item Points Final gradeThree exams  300 90% and above = AHW Assignments 100 80% - 90% = BFinal project 50 70% - 80% = CTotal 450 60% - 70% = D

Below 60% = F

COMPUTER USAGEProModelTM and @Risk computer software will be used for simulation. Also, Excel will be used throughout the course. Students MUST HAVE THOROUGH KNOWLEDGE OF EXCEL.

OTHER COMMENTSa. During the semester, numerous handouts will be distributed or e-mailed to you via

Blackboard. If you miss a class or cannot download a file, you are responsible for obtaining handouts, assignments and other information from your classmates.

b. This is an elective upper division course. There will not be any tutor available for this course.

c. Upon registration, all UTC students become subject to the rules and regulations of the Honor Code (see the Student Handbook).

The Honor Code is fully enforced in my classes.The Honor Code is based upon the assumption that the student recognizes the fundamental importance of honesty in all dealings within the University community and that education is a cooperative enterprise between student and teacher and between student and student. Any act of dishonesty violates and weakens this relationship and lessens the value of the education that the student is pursuing.

d. College of Business faculty will be happy to share their knowledge and experience with you as you plan for your future. If you have any questions regarding career paths in this field or interest in applying to graduate school, please feel free to meet with me (or any faculty member.

ADA STATEMENT: Attention: If you are a student with a disability (e.g. physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Office for Students with Disabilities at 425-4006, come by the office - 102 Frist Hall or see http://www.utc.edu/OSD/

If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely affecting your successful progress at UTC, please contact the Counseling and Career Planning Center at 425-4438 or http://www.utc.edu/Administration/CounselingAndCareerPlanning/

SCHEDULE

DATE

ACTIVITY

Week 1 Course Overview – Monte Carlo Simulation using spreadsheet (Chapters 1, 2 and 3)

Week 2 Simulation with @Risk (Chapters 4 and 5)

Week 3 Business applications using @Risk (Selected chapters from 6 to 13)

Week 4 Business applications using @Risk (Selected chapters from 14 to 24)

Week 5 EXAM 1

Week 6 Introduction to discrete event simulation and ProModel (Chapters 1-4 and Labs 1-3)

Week 7 Data collection and Analysis (Chapter 5 and Labs 5)

Week 8 Model building and verification (Chapters 6 and 7, and Labs 4, 6, and 7)

Week 9 Simulation output analysis (Chapter 8 and Lab 8)

Week 10 EXAM 2

Week 11 Comparing systems (Chapter 9 and Lab 9)

Week 12 Simulation optimization (Chapter 10 and Lab 10)

Week 13 Modeling manufacturing systems (Chapters 11 & 12 and Labs 11 & 12)

Week 14 Modeling service systems (Chapter 13 and Lab 13)

Week 15 FINAL EXAM

Department of Management

COURSE: MGT 4250TITLE: Databases and Data WarehousesPREREQUISITES: MGT 3600CREDIT: 3 hoursFACULTY: Dr. Arben AsllaniTEXTBOOK: "Database Systems – Introduction to Databases and Data Warehouses",

Jukic, Vrbsky, Nestorov, 1st edition (2014), Publisher: PEARSON, ISBN: 9780132575676

CATALOG DESCRIPTIONThis course covers an introduction to organizational databases, database management systems, data warehouses and queries and business reports. Students will become familiar with operational and analytical database systems and design and built simple databases, write queries, and prepare reports for better decision making. Fall semester. Prerequisite: MGT 3600, junior standing or department head approval. Differential Course Fee will be assessed

GOALS AND OBJECTIVESThis is an undergraduate level course and as such students will be expected to gain knowledge about databases and data warehouses. Students in this course will learn how to design and use operational and analytical databases.

Skills and Competencies: Specifically, at the completion of this course, the student will understand the role of databases and their impact in the organization, represent a business description into an entity relationship diagram, create tables, queries, forms and reports using a selected database management system. In addition, students will be introduced to the concepts of data warehousing, star schemas, data marts, the extract-transform-load process, online analytical processing, and business intelligence.

GRADING SYSTEMGrade Item PointsGroup Project   20%Midterm   20%HW Assignments   30%Final Exam   30%Total 100%

Letter Grade From ToA 90% 100%B 80%   90%C 70%   80%D 60%   70%F 0%   60%

OTHER POLICIESPolicy on Late Submissions:Timely completion of all assignments is critical to student success. Instructors may grant limited extensions of time for unexpected business, health or personal emergencies beyond the student's control.  Student must make the request in advance of the due date and support the request by a compelling. Any such extension will be for a period not to exceed one week. For late submissions that have not been approved by the instructor (and for assignments submitted after an extension due date) the penalty will be a 20% reduction in the grade for that assignment for each day that the assignment is late. Please note that there can be no extensions for the assignments during the last week.

Policy on Academic Integrity and Plagiarism:The Honor Code is based upon the assumption that the student recognizes the fundamental importance of honesty in all dealings within the University community and that education is a cooperative enterprise between student and teacher and between student and student.  Any act of dishonesty violates and weakens this relationship and lessens the value of the education which the student is pursuing. The Honor Code and the Honor Court and its procedures are detailed in the UTC’s Student Handbook.

ADA STATEMENT: Attention: If you are a student with a disability (e.g., physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Disability Resource Center (DRC) at 423-425-4006 or come by the office, 102 Frist Hall. (See http://www.utc.edu/disability-resource-center/.)

If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely affecting your successful progress at UTC, please contact the Counseling and Career Planning Center at 425-4438 or visit:http://www.utc.edu/Administration/CounselingAndCareerPlanning/

TopicsClass Introduction, Course Syllabus Forms and Reports with AccessIntroduction to Databases Introduction to Data WarehousesConceptual Design Star SchemaLogical Design Online Analytical ProcessingPhysical Design Data MiningQueries with Access NOSQL Databases

Department of Management

COURSE: MGMT 4260TITLE: Introduction to Business AnalyticsPREREQUISITES: MGT 4360 (or concurrent enrollment), junior standing or department head

approvalCREDIT: 3 hoursFACULTY: Ashish Gupta, PhDTEXTS: Data Mining Techniques: For Marketing, Sales, and Customer

Relationship Management, 3rd Edition, Gordon S. Linoff, Michael J. A. Berry, 2011, ISBN: 978-0-470-65093-6

Course Description: This course will provide an introduction to Business Analytics. Students will learn how to prepare the data for analytics purposes and understand to use various predictive Analytics approaches. These techniques will be examined in the context of various business applications such as healthcare, marketing, finance, and retailing. Fall semester. Prerequisite: MGT 4250 (or concurrent enrollment), junior standing or department head approval. Differential Course Fee will be assessed.

Course Objectives: The purpose is to introduce students to a) Provide the theoretical and practical understanding of the key methods of data preparation methodologies using SAS Enterprise Guide. b) Provide theoretical and practical understanding of various Predictive Analytics Techniques using SAS Miner.

Mandatory TopicsIntroduction to Business AnalyticsData preparation (using Enterprise Guide)

RecodingConditioning

FormattingFilteringWorking with data from disparate sources: RDBMS and Data Warehouses

Predictive Analytics: (Using Enterprise Miner)Accessing and Assaying Prepared DataDecision TreesRegressionNeural Networks Ensemble

Software: SAS Enterprise Guide and SAS Enterprise Miner.

Course ConductThe class will meet at the scheduled times in our classroom. We will develop the framework through our class lectures, but also work on exercise, projects throughout the semester to give you a real life, hands-on experience in Business Intelligence and data mining. There will be lecture, software demonstrations, project updates, class discussion, etc. We will have a occasional invited lectures from outside speakers. The class time will typically be distributed with following proportion: 35% lecture, 45% hands-on training on tools, 20 % Discussion & Participation. This proportion I sonly estimate and will certainly deviate.

Grading PolicyGrade Item Points Final gradeClass Participation (in class and online forums) 10% 90% and above = AMidterm Exam I 20% 80% - 90% = BAssignments (Multiple) 50% 70% - 80% = CFinal Exam 20% 60% - 70% = DTotal 100% Below 60% = F

Exams: There will be two non-cumulative semester exams, including the final. These exams could be a combination of in-class exams or take home exams. Each exam will be worth 100 points. In all other cases, failure to take an exam on during scheduled time window will result in a score of zero (0) on the exam.

Case Studies and Assignments: Several assignments and case studies will be given over the duration of the course during the semester. Unless otherwise specified by the instructor, you will have one week to work on each assignment. You have to turn in your typed, well-organized write-up electronically on blackboard by 5:30 PM (before lecture begins) of the stated due date. The homework assignments are to be solved in groups unless otherwise stated. Assigned cases will involve a written component and classroom discussion.

Group Term Project: This will be a group project activity of 3-4 students. Online forum use is encouraged to participate in off-class discussions related to the projects. Projects will require the use of either SAS guide or SAS miner software to analyze publicly available datasets from various sources such as http://www.kdnuggets.com/datasets/ , http://archive.ics.uci.edu/ml/ . A student could also avail datasets through their own resources. Other additional software packages could be used as well. A proposal will be required to be submitted half way into the semester, followed by the complete report due near the semester end and one team presentation in the class. This project will provide the additional opportunity to the students to improve their business analytics skills. More details about the project, due dates, expectations, will be provided by the instructor later in the classroom. All projects will typically require teams to select their own project, define the problem they would like to study within the data sets, and a report of the findings along with major conclusions. Certain exceptions could be made with respect to software use, if the project is industry driven or is of high impact value or is innovative while being relevant to Analytics.

Class Participation- (Classroom interaction and Online Discussions): All students are expected to actively provide thoughtful and relevant comments to class discussions through online forum and within the classroom. A forum will be created where students will need to interact among themselves on varied topics related to the class and the current topic that is underway. Both types of participations are required: face-to-face and online. This is NOT a group activity and students will be awarded scores at the end of semester based on their meaningful, value-added contribution to the class and forum, finding and sharing new information, innovative news and technologies related to the ongoing topic in the class. This means that students also need to be reading and finding information from external sources proactively during the course. Students need to be aware that instructor will be keeping track of individual contributions and will be reading all the posts carefully. Please remember that quality and quantity are extremely important. A post just meant for the purpose of quantity will not serve any benefit. It should contribute towards either an ongoing discussion substantially or must start a new topic. Please do not post comments such as ‘I agree with the previous post’, etc. Classroom discussions will happen in multiple ways: case study discussions, reading articles, etc.

Your participation has to be consistent throughout the semester. All the messages relevant to the topic must be posted while the chapter is still ongoing according to the class schedule.

Readings: Students will be expected to read assigned material before coming to class so that they can be active participants in the learning experience. Reading throughout the semester will make the lectures more interesting, help students prepare for tests and quizzes, and will allow them to have more input in the direction of the course.

Late Work Policy: Late work is discouraged and will not be accepted. Prior arrangement needs to be made with the instructor.

Honor Code I understand that any work which I submit for course credit will imply that I have adhered to this Academic Honor Code: “I will neither give nor receive unauthorized aid and I will not tolerate an environment which condones the use of unauthorized aid.” All students are subject to the UTC’s policy on academic dishonesty and integrity in the Student Handbook. Students in violation of University policies will receive a failing course grade and appropriate administrative action will be taken for record.

You will need following technology-1. Fast speed internet access, UTC email access 2. Blackboard access https://bb4.utc.edu/3. SAS on Demand http://support.sas.com/ondemand/index.html#account

(Requires one time registration)4. SAS server Access http://support.sas.com/ctx3/sodareg/index.html

Disclosure: Please note that instructor reserves to make any changes in the course schedule and syllabus at any time during the semester. Students will be informed beforehand whenever such changes are made

ADA STATEMENT: Attention: If you are a student with a disability (e.g. physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Office for Students with Disabilities at 425-4006, come by the office - 102 Frist Hall or see http://www.utc.edu/OSD/

If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely affecting your successful progress at UTC, please contact the Counseling and Career Planning Center at 425-4438 or http://www.utc.edu/Administration/CounselingAndCareerPlanning/

Department of Management

COURSE: MGMT 4270TITLE: Advanced Business AnalyticsPREREQUISITES: MGT 4260, MGT 4360, junior standing or department head approval.CREDIT: 3 hoursFACULTY: Ashish Gupta, PhDTEXTS: Business Intelligence: A Managerial Perspective on Analytics, 3/E,

Ramesh Sharda and Dursun Delen. Efraim Turban, ISBN-10: 0133051056, ISBN-13: 9780133051056, 2014, Prentice Hall

Course Description: This course builds on the Introduction to Business Analytics course (MGT 4260) and will describing various methodologies for describing the structured data and applying analytics approaches to understanding unstructured data from disparate sources. Spring semester. Prerequisite: MGT 4250, MGT 4260, junior standing or department head approval. Differential Course Fee will be assessed. Course Objectives: The purpose is to introduce students to a) Provide practical understanding of various descriptive analytics techniques. b) Provide understanding of using text Analytics for processing unstructured data.

We will primarily use SAS Enterprise Miner, SAS Text Miner and Sentiment Analysis.

Topics covered:Mandatory TopicsCluster AnalysisMarket Basket AnalysisSegmentation AnalysisProfilingVisual AnalyticsText AnalyticsSentiment AnalysisMixed Model ApproachesIntroduction to Big Data and Hadoop methodologies

Software: Main program used will be SAS Enterprise Miner. Other SAS programs such as SAS content Analysis, SAS sentiment Analysis, SAS Text Miner may also be used depending upon time and availability.

Course Conduct

The class will meet at the scheduled times in our classroom. We will develop the framework through our class lectures, but also work on exercise, projects throughout the semester to give you a real life, hands-on experience in Business Intelligence and data mining. There will be lecture, software demonstrations, project updates, class discussion, etc. We will have a occasional invited lectures from outside speakers. The class time will typically be distributed with following proportion: 35% lecture, 45% hands-on training on tools, 20 % Discussion & Participation. This proportion I sonly estimate and will certainly deviate.

Grading PolicyGrade Item Points Final gradeClass Participation (in class and online forums) 10% 90% and above = AMidterm Exam I 20% 80% - 90% = BAssignments (Multiple) 50% 70% - 80% = CFinal Exam 20% 60% - 70% = DTotal 100% Below 60% = F

Exams: There will be one non-cumulative mid-term semester exam. The exam will be a take home exam. In all other cases, failure to take an exam on during scheduled time window will result in a score of zero (0) on the exam.

Case Studies and Assignments: Several assignments and case studies will be given over the duration of the course during the semester. Unless otherwise specified by the instructor, you will have one week to work on each assignment. You have to turn in your typed, well-organized write-up electronically on blackboard by the stated due date. The homework assignments are to be solved in groups unless otherwise stated. Assigned cases will involve a written component and classroom discussion.

Class Participation- (Classroom interaction and Online Discussions): All students are expected to actively provide thoughtful and relevant comments to class discussions through online forum and within the classroom. A forum will be created where students will need to interact among themselves on varied topics related to the class and the current topic that is underway. Both types of participations are required: face-to-face and online. This is NOT a group activity and students will be awarded scores at the end of semester based on their meaningful, value-added contribution to the class and forum, finding and sharing new information, innovative news and technologies related to the ongoing topic in the class. This means that students also need to be reading and finding information from external sources proactively during the course. Students need to be aware that instructor will be keeping track of individual contributions and will be reading all the posts carefully. Please remember that quality and quantity are extremely important. A post just meant for the purpose of quantity will not serve any benefit. It should contribute towards either an ongoing discussion substantially or must start a new topic. Please do not post comments such as ‘I agree with the previous post’, etc. Classroom discussions will happen in multiple ways: case study discussions, reading articles, etc.

Your participation has to be consistent throughout the semester. All the messages relevant to the topic must be posted while the chapter is still ongoing according to the class schedule.

Readings: Students will be expected to read assigned material before coming to class so that they can be active participants in the learning experience. Reading throughout the semester will make the lectures more interesting, help students prepare for tests and quizzes, and will allow them to have more input in the direction of the course.

Honor Code I understand that any work which I submit for course credit will imply that I have adhered to this Academic Honor Code: “I will neither give nor receive unauthorized aid and I will not tolerate an environment which condones the use of unauthorized aid.” All students are subject to the UTC’s policy on academic dishonesty and integrity in the Student Handbook. Students in violation of University policies will receive a failing course grade and appropriate administrative action will be taken for record.

You will need following technology-5. Fast speed internet access, UTC email access 6. Blackboard access https://bb4.utc.edu/7. SAS on Demand http://support.sas.com/ondemand/index.html#account

(Requires one time registration) optional. 8. SAS server Access http://support.sas.com/ctx3/sodareg/index.html

Disclosure: Please note that instructor reserves to make any changes in the course schedule and syllabus at any time during the semester. Students will be informed beforehand whenever such changes are made

ADA STATEMENT: Attention: If you are a student with a disability (e.g. physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Office for Students with Disabilities at 425-4006, come by the office - 102 Frist Hall or see http://www.utc.edu/OSD/

If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely affecting your successful progress at UTC, please contact the Counseling and Career Planning Center at 425-4438 or http://www.utc.edu/Administration/CounselingAndCareerPlanning/

Department of Management

COURSE: MGT 4280TITLE: Supply Chain ManagementPREREQUISITES: MGT 3110CREDIT: 3 hoursFACULTY: David WittTEXT: Manufacturing Planning and Control Systems for Supply Chain

Management, Sixth Edition, Vollmann, Berry, Whybark, & Jacobs (Irwin) 2010, ISBN 978-007-3377827, www.mhhe.com/jacobs-berry6e

CATALOG DESCRIPTIONConcepts and techniques related to designing and managing supply chains. Topics include Master production scheduling, material requirements planning, capacity requirements planning, logistics, purchasing/sourcing, warehousing, and inventory management. Emphasis on analysis of the competitive environment, distribution network alternatives, and customer service aspects provide a background in each functional area to enable students to pursue their areas of interest. Fall semester. Prerequisites: MGT 3110, junior standing or department head approval. Differential course fee will be assessed.

OBJECTIVESAchieve competency is designing and managing supply chains through fulfilling the following: Master demand forecasting and management techniques. Learn Master Production Schedule and capacity management techniques Learn to develop Material Requirements Plans, Capacity Requirements plans, and

Distribution Requirements plans Learn to manage supply chain logistics Achieve expertise in various inventory management and control methods

SKILLS AND COMPTENCIESWe will analyze data and expand proficiency in the use of data, recognize problems and opportunities and encourage critical thinking, develop expertise in an area related to career choice, communicate effectively in written form, and foster understanding of the impact of business decisions in supply chain management.

COURSE CONDUCTClass meetings will be devoted to lectures and discussion of the material from the texts and current issues from other sources. We will use the Socratic Method and students are expected to participate in active dialog regarding the topic at hand. You will need your book in order to review concepts and work on homework. Please make sure you bring your textbook to each and every class.

GRADING SYSTEMYour grade will be determined by and based on the following components and weights. None of the exams will be deliberately cumulative, although concepts developed in the earlier portion of the course have applications in the later portions. Eligible material for the exams includes all text and lecture material covered prior to the exam.

Exams and quizzes will be open book and open notes (including homework problems). The essay part of the exams will be closed book. Grades will be based on the following weights:

EXAM 1 100 points GradingEXAM 2 100 points 90% and above = AFINAL EXAM 100 points 80% - 90% = BHOMEWORK 60 points 70% - 80% = CQUIZZES 50 points 60% - 70% = DPARTICIPATION & ATTENDANCE 40 points Below 60% = FTotal 450 points

All grades will be earned based on quality, completeness, and technical proficiency. In order to complete the course all projects, assignments, exams, etc. must be completed.

Participation & Attendance (40 Points)Participation and attendance are both expected of all students for each class. Students must come to class prepared which means having fully read and analyzed the various readings and assignments. Participation points must be earned. Attendance is also vital so we may have a full intellectual discussion. If there is an emergency and you will not be able to attend class please notify me as soon as possible. Participation will be rewarded in part by being prepared to discuss homework assigned. Advance notice is required if a student is unable to make it to class.

Homework (60 Points)Homework will be assigned for each class. The cumulative homework will grade up to 60 points. It is expected that students will come prepared to discuss the problems and essays assigned and share their work with the class.

UTC Honor Code PledgeI pledge that I will neither give nor receive unauthorized aid on any test or assignment. I understand that plagiarism constitutes a serious instance of unauthorized aid. I further pledge

that I will exert every effort to insure that the Honor Code is upheld by others and that I will actively support the establishment and continuance of a campus-wide climate of honor and integrity.

ADA STATEMENT: Attention: If you are a student with a disability (e.g., physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Disability Resource Center (DRC) at 423-425-4006 or come by the office, 102 Frist Hall. (See http://www.utc.edu/disability-resource-center/.)

If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely affecting your successful progress at UTC, please contact the Counseling and Career Planning Center at 425-4438 or http://www.utc.edu/Administration/CounselingAndCareerPlanning/

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COURSE SCHEDULE

DATE ACTIVITY

Week 1 Course Overview – Chapter 1 (Manufacturing Planning & Control for Supply Chain Management)

Week 2 Chapter 4 and 4A – Sales and Operations Planning (SOP)

Week 3 Chapter 5 – Master Production Scheduling (MPS)

Week 4 Chapter 5 – Master Production Scheduling (MPS) … continued

Week 5 EXAM 1

Week 6 Chapter 6 – Materials Requirement Planning (MRP)

Week 7 Chapter 6A – Advanced Mat. Req. Planning (MRP)

Week 8 Chapter 7 – Capacity Planning & Management

Week 9 Chapter 9 – Just-in-Time

Week 10 EXAM 2

Week 11 Chapter 10 – Distribution Requirements Planning

Week 12 Chapter 10A – Management of Supply Chain Logistics

Week 13 Chapter 11 – Order Point Inventory Control Methods

Week 14 Chapter 12 – Strategy and Manufacturing Planning & Control (MPC) System Design

Week 15 FINAL EXAM