OPIM 101 Introduction to the Computer as an Analysis Tool

1. OPIM 101 Introduction to the Computeras an Analysis Tool Spring 2000 Steven O. Kimbrough James D. Laing

2. Faculty Steven O. Kimbrough kimbrough@equity.wharton.upenn.edu James D. Laing laing@equity.wharton.upenn.edu Graduate assistants Patricia Grossi, Head TA pgrossi@opim.wharton.upenn.edu phone: 898-6806 Eric Zheng, Grader Undergraduate assistants Staff

3. Develop analytical, quantitative, and problem-solving skills for using computer to model, analyze, and solve management problems communicating analyses, conclusions, and recommendations for managerial action Master cutting-edge tools for other courses summer jobs professional career after college Gain insight on effective use of information and decision technology to solve problems the role of computers in modern organizations operations and information management Not “a course on how to use Excel”! Course Objectives

4. Required: Kimbrough and Laing (1998). Information and Decision Technology: An Introduction to Computer-Based Modeling and Analysis Walkenbach (1999). Excel 2000 Bible MOUS Essentials: Excel 97 Proficiency MOUS Essentials: Excel 97 Expert MOUS Essentials: Access 97 Jacobson (1999). Excel 2000 Visual Basic for Applications Course Pack #1 Recommended: PennNet Passport Texts

5. Classroom sessions Homework assignments Tutorials in Excel and Access Reading materials Homework Exercises (not graded) Semester Grade Points Based on: Case 1 – Internet (5% of total points) Three Lab Proficiency Exams (each @ 10%) Midterm Exam (25%) Case 2 – Integrating Excel and Access using Visual Basic for Applications (15%) Final Examination (25%) Grades curved per Wharton core-course guidelines - approximately 25% As 40% Bs 30% Cs 5% Ds and Fs Course Requirements

6. Last day to add classes: Jan. 28 Case 1 due by 10:00am Jan. 31 Lab Exam 1: Feb. 3 or 4* *Note: All Three Lab Exams by Appointment Lab Exam 2: Feb. 17 or 18* Last day to drop classes: Feb. 18 Midterm Exam: 6:00-8:00pm March 2 Spring Break: March 10-20 Lab Exam 3: March 23 or 24* Case 2 due by 10:00am April 24 Last Day of Class: April 28 Final Exam: 1:30-3:30pm May 4 Important Dates(“chiseled in stone”)

7. Learning is not a spectator sport! Hands-on essential to learning Do assigned work on time Do assignments and attend class Catching up in OPIM 101 is difficult Case and tutorials take time -- plan ahead Get help when you need it RTFM: read the manual online help (e.g. Office Assistant) opim101 newsgroup for questions of general interest (check frequently) e-mail: opim101@opim.wharton.upenn.edu office hours (TAs, Graders, Faculty) for info re private tutor for any Wharton course, contact Anita Henderson (898-7608) Check course newsgroup and homepage regularly Tips

8. OPIM 101 is demanding for the staff also, so please be thoughtful. All questions about the grading of the case should be directed to the grader for the case, not the TAs. Please prepare before coming to office hours to use TAs’ efficiently If your questions will require access to your file, please upload it to your Futures account for downloading during office hours. Use the newsgroup Pose your question there if the answer might help other students. Check it regularly TAs will try to respond within 24 hours. Maintain high standards of civility. Working with the Staff; Etiquette

9. We strongly endorse the University of Pennsylvania’s Academic Code of Integrity, and will report any violation for official action. Each student must work independently on Case 1: Internet. (Groups may cooperate for Case 2.) Do not discuss the contents of any lab exam with others until everyone has taken it. Otherwise, we encourage you to: discuss with other students the course materials – readings, tutorials, and homework exercises create an effective study group form a project group for Case 2 Academic Integrity

10. Students rate OPIM 101 very high on amount of work difficulty of course amount learned OPIM 101 empowers students to use computers effectively for solving business problems. The large investment required to develop this analytic power pays significant dividends in subsequent coursework entry into the job market sustained professional growth Cautions, Encouragements

11. Recognize the problem Develop a concept for representing and solving the problem Spreadsheet modeling, LP, decision analysis, programming, database, IR, simulation How shall we think of solving the problem? What is our solution concept? Implement the solution (usually in software) How can we actually solve the problem by gaining effective access to the data, models, documents, etc. needed to implement our solution concept? Analyze, interpret, and communicate the solution results How good is our solution? What exactly does it mean? Are the findings stable or do they rest on precarious assumptions? &c. Problem-Solving/ Decision-Making Life Cycle

12. Internet (and the WWW) Spreadsheet modeling Visual Basic for Applications Linear programming Database Decision analysis Course’s Main Topics

13. Monte Carlo simulation Discrete event simulation Machine learning Genetic algorithms Neural nets Behavioral decision making Information retrieval Additional Topics

14. Skills e.g., Excel, Access, Visual Basic, Internet Plus.... Applications in the context of the basic problem solving/decision making life cycle Basic Strategy

15. Recognition of a problematic situation The problem: find documents(here, Web pages) relevant to an information-based task at hand. Problem representation or model Solution concept: Use search engines to find relevant information Solution implementation Implementation: Use search engines available on the Internet, using key word searching techniques, to find relevant information Solution interpretation Interpretation: Explore cyberspace, looking for what you are after. How effective is your search technique? Example: InformationRetrieval

16. Recognition of a problematic situation The problem: to decide whether to accept an investment opportunity. Problem representation or model Solution concept: Think of the cash inflows and outflows as time-dependent, and make them time-equivalent by taking NPVs. Solution implementation Implementation: in Excel. Lay out the cash flows in a well-organized spreadsheet and use available functions to make the calculations needed to implement the solution concept. Solution interpretation Interpretation: perform sensitivity analysis, plot results and reflect upon them. Example: InvestmentAnalysis

17. Recognition of a problematic situation The problem: to decide on a course of action in the face of considerable risk and economically significant outcomes Problem representation or model Solution concept: Think of the problem as a decision analysis problem, so that decision trees can be applied. Solution implementation Implementation: in Excel. Lay out the outcomes, chance events, and possible decisions in a well-organized, maintainable spreadsheet. Use Excel to make the calculations needed to determine expected value, EVSI, etc. Solution interpretation Interpretation: use standard sensitivity analysis techniques (e.g., Data Tables, charts, goal seeking) to examine and interpret the reports produced by the spreadsheet calculations. Example: Decisionsunder Risk (Decision Analysis)

18. Recognition of a problematic situation The problem: to decide how to allocate scarce resources in order to maximize economic benefit Problem representation or model Solution concept: Think of the problem as a constrained optimization problem, linear in form so that LP can be applied. Solution implementation Implementation: in Excel. Lay out the objectives and constrains in a well-organized spreadsheet and use the solver to make the calculations needed to implement the solution concept. Solution interpretation Interpretation: examine and interpret the sensitivity analysis reports produced by the LP solver. Example: ResourceAllocation (LP, linear programming)

19. Recognition of a problematic situation The problem: to decide how to allocate scarce resources in order to maximize economic benefit (again) Problem representation or model Solution concept: Think of the problem as a constrained optimization problem, integer or nonlinear in form so that LP cannot be applied. Solution implementation Implementation: in Visual Basic. Lay out the objectives and constrains in a well-organized spreadsheet and use the Visual Basic code to make the calculations needed to implement the solution concept. Solution interpretation Interpretation: examine and interpret the results produced by the Basic code. Example: Model-BasedDecision Making

20. Recognition of problem The problem: to understand what is actually going on in a business and to take actions that improve the profitability of the firm Problem representation or model Solution concept: The records of the firm’s business transactions contain a great deal of useful information on how and how well the firm is conducting its business. Explore those records. Solution implementation Implementation: in Access. Organize the transaction records in a well-designed relational database. Use the database query facilities, especially SQL and QBE, to make the calculations needed to reveal the essential business patterns needed to understand what is going on. Solution interpretation Interpretation: Use the query facilities to explore beyond a fixed set of reports. Perform what-if queries, plot data, etc. Example: Data Inter-pretation

21. Uniform Resource Locators Internet addressing scheme See materials from Wharton Computing Basic format: scheme:path Schemes, aka: access methods, protocols http: hypertext transfer protocol ftp: file transfer protocol gopher: precursor to the World Wide Web Example: http://www.upenn.edu/index.html www.upenn.edu - a computer index.html - a file (the Web default) or http://www.upenn.edu/ URLs

22. Wharton home page http://www.wharton.upenn.edu Netscape manual http://home.netscape.com/newsref/manual Virtual fly shop http://www.flyshop.com/ A Beginner’s Guide to HTML http://www.ncsa.uiuc.edu/General/Internet/WWW/HTMLPrimerAll.html OPIM 101 home page http://opim.wharton.upenn.edu/~opim101/spring00/ OPIM 101 Syllabus http://opim.wharton.upenn.edu/~opim101/spring00/dopim101s00syllabus.html (Some) Useful URLs

23. Netscape Current standard for graphical interface Web browsing On Macintosh, Microsoft Windows, & Unix machines Internet Explorer From Microsoft Roughly equivalent to Netscape Mosaic The first “killer ap” for the Internet Precursor to Netscape Lynx Character-based interface for Web browsing Available on Unix machines at Wharton Fast, but no graphics Good for dialing in from home Browsing the Web(and viewing the Syllabus)