BASEL MBA PROGRAM

MBA-820: Information Technology for Decision Making

MADJID TAVANA, PH.D. Professor, Business Systems and Analytics

Lindback Distinguished Chair of Information Systems and Decision Sciences Editor-in-Chief, Decision Analytics

Editor-in-Chief, International Journal of Applied Decision Sciences Editor-in-Chief, International Journal of Management and Decision Making

Editor-in-Chief, International Journal of Strategic Decision Sciences Editor-in-Chief, International Journal of Enterprise Information Systems

Management Department ● La Salle University Philadelphia, Pennsylvania 19141 ● U.S.A.

Phone: (215) 951-1129 ● Fax: (267) 295-2854 ● Skype: madjidtavana Email: tavana@lasalle.edu ● Web: http://tavana.us

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1. PREREQUISITES: Completion of Foundation Courses 2. COURSE DESCRIPTION:

Managing Information Technology (IT) is no longer viewed as a back office, cost-dominated function. In many industries, IT has become a strategic requirement that consists of two related but competing activities: supporting the existing business and enabling new business. These two activities share a set of functional requirements, typically organized within the information systems (IS) department. But they also share a set of critical management issues, which transcend the IS function. This course is about the manager's responsibilities for problem solving and decision making, and those areas in which IT can be used to gain the insight needed to support selection of decision alternatives. The course focuses on data, information, and knowledge by utilizing a series of tools to develop Database Management Systems, Management Information Systems, Decision Support Systems, and expert System in support of the decision making and problem solving processes in a hands-on environment. 3. COURSE OBJECTIVES: Upon completion of prescribed work for this course, the student should be able to:

Understand the emerging technological issues facing managers. Understand the value of data, information, and knowledge to organizations. Distinguish among Database Management Systems, Management Information Systems,

Decision Support Systems, and expert System. Utilize IT to design competitive and efficient organizations. Describe the latest concepts, components, and applications of IT. Utilize IT tools to design operational, managerial, and strategic systems. Describe the leadership responsibilities and organizational impact of IT. Utilize a series of tools to design and develop Database Management Systems,

Management Information Systems, Decision Support Systems, and expert System in support of the decision making and problem solving processes.

Describe when and how Management Support Systems may be used to complement more analytic decision making frameworks.

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4. COURSE OVERVIEW: Computers are data, information, and knowledge processing machines. Billions of dollars are spent every year collecting, storing, processing, and retrieving data; whether it is for financial, marketing, or operational analysis and decision making. Data is a collection of bits, bytes, and characters. Raw data by itself has little or no use. No decision can be made without organizing and synthesizing data. Information is derived from organizing data and knowledge is extracted from synthesizing information. The evolution of data and its relationship with information and knowledge can be visualized as a pyramid of interdependent layers on the top of each other with data at the bottom, information in the middle, and knowledge on the top.

Computers are used to collect, store, and process (organize and synthesize) data, information, and knowledge. Data is collected by a Transactional Processing System (TPS) and stored in a Database Management System (DBMS). Data is organized into information by an Information System (IS) and used in a Decision Support System (DSS) for decision making. Information is organized, meaningful, and useful data. Information is synthesized into knowledge by a Knowledge Based system (KBS) and used in an Expert Systems (ES) for problem solving.

Consider the scenario depicted in the pyramid below where a retailer collects data on their revenues and expenses every time a purchase is made or every time an expense is paid. That data is then stored in the retailer’s DBMS. The accounting department can retrieve and organize this data into meaningful information by way of a report such as income statement. The

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operations department can use this information in a DSS to assess profitability. The finance department can synthesize this information in a KBS and make expansion or contraction decisions. This course focuses on data, information, and knowledge by utilizing a series of tools to develop Database Management Systems, Management Information Systems, Decision Support Systems, and expert System in support of the decision making and problem solving processes in a hands-on environment.

5. WEB RESOURCES: http://tavana.us/downloads/downloads.shtml username: tavana password: spacewalk 6. COURSE TOPICS AND REQUIREMENTS: The World of Information Systems and Decision Sciences

Decision Making in the Information Age

Transactional Processing Systems and Database Management

Database Management Systems (SA-DBM-H)

Building DBMS with ACCESS (SA-ACC-H)

Cases:

Happyville Casino, Explorer Healthcare, Great Times Summer Camp, and Jimmy “the Body Bag” Biggs

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Access Case Analysis OR Access Problem in Exam (15% of the Final Grade):

Access Case Report: A PowerPoint Presentation with Problem Description, Initial

Table, Split Tables, Relationships, and Query.

SAMPLE ACCESS CASE & DATABASE.

Decision Support Systems and Spreadsheets

Decision Support Systems and EXCEL (DS-EXL-H)

Cases:

American Appliances, Heinrich Company, Francois Stealth, Planters Nut Company, Titanic Cruise Company, Built-4-U, Golden Palace Casino, Impulse Shopping Network, and Rent-A-Wreck.

Excel Case Analysis OR Excel Problem in Exam (15% of the Final Grade):

Excel Case Report: A PowerPoint Presentation with Problem Description, Excel

Spreadsheet, Solver Formulation, and Optimal Solution.

SAMPLE EXCEL CASE & EXCEL FILE.

Decision Support Systems and Natural Language Programming (Visit D-code.us)

Natural Language Programming: D-code (DS-COL-H)

Building DSS with D-code (DS-COP-H)

Cases:

Keystone Corporation, Prolog Corporation, Starship Technologies, Dr. Warped, and Jungle Jim

D-code Case Analysis OR D-code Problem in Exam (15% of the Final Grade):

D-code Case Report: A PowerPoint Presentation with Problem Description,

Influence Diagram, Planners Lab Model, and Spreadsheet Solution.

SAMPLE D-CODE CASE & D-code FILE.

Decision Support Systems and Influence Diagramming (Visit D-cide.us)

Influence Diagramming and D-cide (DS-DCD-H)

Cases:

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Procom Corporation, Thrills R Us, Parrot Club, Southwest Airline, Pick Your Own, Jungle Jim

D-cide Case Analysis OR D-code Problem in Exam (15% of the Final Grade):

D-code Case report: A PowerPoint Presentation with Problem Description,

Influence Diagram Screenshot, and Spreadsheet Solution.

SAMPLE D-cide CASE & D-cide FILE.

Knowledge-Based Systems (Visit B-wise.us)

Knowledge Engineering with B-wise (DS-BWL-H)

Building Expert Systems with B-wise (DS-BWP-H)

Cases:

Check Cashing Problem, College Hill Tavern, Police Academy, Corleone Family, La Boutique, and Gateway Computers

B-wise Case Analysis OR B-wise Problem in Exam (15% of the Final Grade):

B-wise Case Report: A PowerPoint Presentation with Problem Description, A

listing of Factors and Choices, and Decision Tree Screenshot.

SAMPLE B-wise CASE & B-wise FILE.

Exam (Between 0% to 25% of the Final Grade)

A hands-on exam focusing on the systems described throughout the

course (Open Book and Open Notes).

Professionalism (5% of the Final Grade)

7. PROFESSIONALISM:

The majority of this class is engaged in full time employment or is seeking to enhance their employment opportunities. I would like to help you enhance your career by asking you to behave as you would in a professional setting. To do this, I suggest that you think of me as your manager, and our class sessions as regularly scheduled meetings. Following are some of the things that professionals would never do:

Miss a regularly scheduled meeting.

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Arrive late for a meeting without explaining the circumstances ahead of time. Leave early from a meeting, without explaining the circumstances ahead of time. Sleeping or being inattentive during a meeting. Being unprepared or being unwilling to participate in class and group discussions.

To encourage development of professional habits, there will be a penalty of 10 points (out of 100) for each class missed unless an excuse (not exceeding one class) is obtained from the instructor IN ADVANCE of the class. 8. CUSTOMIZING YOUR COURSE REQUIREMENTS:

You can choose to show your proficiency in each course topic through a case study or exam problem. A minimum of two case studies is required from each student to partially satisfy this requirement:

Course Component

Case Study

Exam

Access 15% OR 15%

Excel 15% OR 15%

D-code 15% OR 15%

D-cide 15% OR 15%

B-wise 15% OR 15%

Group Project 25%

Total 100%

9. GRADING POLICY: Cases should be submitted through the following online submission system:

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Grades are sent to each student through email using the following evaluation form:

Grading Criteria 0 1 2 3 4 5 6 7 8 9 10

Originality/Creativity

Presentation

Problem Description

Complexity

Solution

Overall score

The student earns points which will be calculated on a 100 point scale. There is no extra credit. The following are the cutoff points for each grade:

A Indicates the demonstration of a superior level of competency 93.0-100

A- Indicates the demonstration of a very good level of competence 90.0-92.9

B+ Indicates the demonstration of a good level of competency 87.0-89.9

B Indicates the demonstration of an average, satisfactory level of competency 83.0-86.9

B- Indicates the demonstration of a less than average level of competency 80.0-82.9

C Indicates a below average and marginally satisfactory level of competency 70.0-79.9

F Indicates failure to demonstrate a satisfactory level of competency 00.0-69.9

La Salle University is a community of shared academic values, foremost of which is a strong commitment to intellectual honesty, honorable conduct, and respect for others. In order to meet these values, students are expected to adhere to the highest standards of academic integrity. These standards are embodied in the La Salle University Academic Integrity Policy and are available online at: http://tavana.us/AIP.pdf

11. GROUP PROJECT:

Big Data and Decision Analytics

BANKING IN EMERGING ECONOMIES

The determinants for the internationalization of banking are based on country characteristics and market dynamics and bank-specific advantages. Primarily the country characteristics consist of barriers to entry

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to provide services, the type of activities allowed and the type of investment allowed, as well as, regulations on capital flows and taxation and repatriation of profits, or indeed, tax benefits offered by a government to attract foreign banks to invest directly to encourage spill-over effects in the industry. The size of the market for banking products and specifically the product markets that are targeted and the potential growth of these are other factors. In terms of the foreign financial market dynamics the potential performance and profitability depends on the interaction and rivalry among existing banks in the market, the number of these their nationality and their size distribution, that is whether it a concentrated oligopolistic market with a few large banks and some other smaller banks, or it is a highly fragmented market. Different product markets and customer segments, that is, individual or corporate customers, may have different levels of rivalry and margins and hence profitability is different for each type. The more a bank has distinctive competencies the more that they may be transferred abroad. By definition when they have distinctive there must be some competitive advantage for the bank. The decision to enter an emerging economy by a multinational bank is a very important one, as many factors need to be considered. We consider the following 30 countries in 4 continents: Africa (Angola, Ghana, Kenya, Namibia, Nigeria, South Africa, Uganda); Asia (Taiwan, Thailand, South Korea, Vietnam); Europe (Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, Turkey, Ukraine); and Latin America (Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Uruguay). PESTEL analysis (political, economic, social, technological, environmental, and legal analysis) is used to initially collect 500 factors grouped into the political, economic, social, technological, environmental, and legal categories. We then use FONDA to Filter, Organize, Normalize, Decide, and analyze the data. A minimum of 200 factors for the abovementioned 30 countries must be used in the final data set. More information is available at: http://tavana.us/project/

Click here to open and fill out your data sheet. Please return or email your completed data sheet to your instructor during the first week of classes.