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OPIM 101 Introduction to the Computer

as an Analysis Tool

Spring 2000

Steven O. Kimbrough

James D. Laing

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Staff

• 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

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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”!

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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

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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 (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

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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 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

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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)– 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

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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.

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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

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Cautions, Encouragement

s• 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

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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.

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Course’s Main Topics

• Internet (and the WWW)

• Spreadsheet modeling

• Visual Basic for Applications

• Linear programming

• Database

• Decision analysis

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Additional Topics

• Monte Carlo simulation

• Discrete event simulation

• Machine learning– Genetic algorithms

– Neural nets

• Behavioral decision making

• Information retrieval

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Basic Strategy

• Skills– e.g., Excel, Access, Visual Basic, Internet

Plus....

• Applications– in the context of the basic problem

solving/decision making life cycle

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Example: InformationRetrieval

• 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?

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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.

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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.

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Example: ResourceAllocation

(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.

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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.

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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.

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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:http://www.upenn.edu/index.html

www.upenn.edu - a computer

index.html - a file (the Web default)

or

http://www.upenn.edu/

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(Some) Useful URLs

• Wharton home pagehttp://www.wharton.upenn.edu

• Netscape manualhttp://home.netscape.com/newsref/manual

• Virtual fly shophttp://www.flyshop.com/

• A Beginner’s Guide to HTMLhttp://www.ncsa.uiuc.edu/General/Internet/

WWW/HTMLPrimerAll.html

• OPIM 101 home pagehttp://opim.wharton.upenn.edu/~opim101/spring00/

• OPIM 101 Syllabushttp://opim.wharton.upenn.edu/~opim101/

spring00/dopim101s00syllabus.html

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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