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

2 Staff Faculty –Steven O. Kimbrough –James D. Laing Graduate assistants –Patricia Grossi, Head TA phone: –Eric Zheng, Grader Undergraduate assistants

3 Course Objectives 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”!

4 Texts 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

5 Course Requirements 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 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

6 Important Dates (“chiseled in stone”) 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 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

7 Tips 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) – –office hours (TAs, Graders, Faculty) –for info re private tutor for any Wharton course, contact Anita Henderson ( ) Check course newsgroup and homepage regularly

8 Working with the Staff; Etiquette 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.

9 Academic Integrity 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

10 Cautions, Encouragements 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

11 Problem-Solving/ Decision-Making Life Cycle 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.

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

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

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

15 Example: Information Retrieval 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?

16 Example: Investment Analysis 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.

17 Example: Decisions under Risk (Decision Analysis) 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.

18 Example: Resource Allocation (LP, linear programming) 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.

19 Example: Model-Based Decision Making 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.

20 Example: Data Inter- pretation 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.

21 URLs 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: a computer index.html - a file (the Web default) or

22 (Some) Useful URLs Wharton home page Netscape manual Virtual fly shop A Beginner’s Guide to HTML W/HTMLPrimerAll.html OPIM 101 home page OPIM 101 Syllabus g00/dopim101s00syllabus.html

23 Browsing the Web (and viewing the Syllabus) 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