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OPIM 101 Introduction to the Computer as an Analysis Tool

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Title: OPIM 101 Overview Subject: decision technology Author: Steven O. Kimbrough Last modified by: James D. Laing Created Date: 1/14/1996 1:55:07 PM – PowerPoint PPT presentation

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Title: OPIM 101 Introduction to the Computer as an Analysis Tool


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
  • kimbrough_at_equity.wharton.upenn.edu
  • James D. Laing
  • laing_at_equity.wharton.upenn.edu
  • Graduate assistants
  • Patricia Grossi, Head TA
  • pgrossi_at_opim.wharton.upenn.edu
  • phone 898-6806
  • 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 (each _at_ 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 1000am 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 600-800pm March 2
  • Spring Break March 10-20
  • Lab Exam 3 March 23 or 24
  • Case 2 due by 1000am April 24
  • Last Day of Class April 28
  • Final Exam 130-330pm 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)
  • e-mail opim101_at_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

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
    Pennsylvanias 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
Courses 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 firms
    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
  • schemepath
  • 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/

22
(Some) Useful URLs
  • Wharton home page
  • http//www.wharton.upenn.edu
  • Netscape manual
  • http//home.netscape.com/newsref/manual
  • Virtual fly shop
  • http//www.flyshop.com/
  • A Beginners Guide to HTML
  • http//www.ncsa.uiuc.edu/General/Internet/WWW/HTML
    PrimerAll.html
  • OPIM 101 home page
  • http//opim.wharton.upenn.edu/opim101/spring00/
  • OPIM 101 Syllabus
  • http//opim.wharton.upenn.edu/opim101/spring00/do
    pim101s00syllabus.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
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