OPIM 101 Overview

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Transcript OPIM 101 Overview

Introduction to the Computer as an Analysis Tool OPIM 101

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Overview

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Staff Syllabus and organization of the course Problem solving with computers ToDo 2

Staff

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Instructors

Jan W. Buzydlowski (Sections 01 & 02)

Panos Markopoulos (Sections 03 & 04) Course Coordinator

Steven O. Kimbrough Head Teaching Assistant

Karthik Balasubramaniam

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Teaching Assistants (TAs)

Undergraduate Assistants Graders

Ph.D. Students 3

Texts

Free:

Kimbrough (2003). Information and Decision Technology: An

Introduction to Computer-Based Modeling and Analysis

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“IDT Book” On-line in PDF from course homepage

Non-Programmers Tutorial for Python by Josh Cogliati.

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“EasyTut” On-line at Course Homepage

Course Pack

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available on-line from the course homepage 4

Texts

Not free:

Moore, Weatherford, et al (2000). Decision Modeling with Microsoft Excel

MOUS Essentials: Excel 2000

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PIN Codes 5

Course Requirements

Graded:

Cases

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Internet: 5% Excel: 10% Database: 15%

Exams

Multiple choice and short answer

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Mid-term: 30% Final: 30%

MOUS Exam

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Excel: 10% 6

Grading Policies

Grades curved per Wharton core-course guidelines - approximately

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25% As 45% Bs 30% Cs Ds and Fs (if earned…) 7

Tips

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Learning is not a spectator sport!

Hands-on essential to learning Do assigned work on time

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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

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online help (e.g. Office Assistant) e-mail: [email protected]

office hours (TAs, Graders, Faculty) for info re private tutor for any Wharton course, contact Anita Henderson (215.898.7608)

Check course homepage regularly!!!

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Working with the Staff; Etiquette

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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.

Maintain high standards of civility / protocol. 9

Academic Integrity

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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. Work in groups of 2-3 for Case 2 & Case 3.

Otherwise, we encourage you to:

discuss with other students the course materials – readings, tutorials, and homework exercises

create an effective study group

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form a project group for Cases 2 & 3 (now!) 10

Course Objectives

1. Develop analytical, quantitative, & problem solving skills for:

using computer to model, analyze, and solve management problems

communicating analyses, conclusions, and recommendations for managerial action 2. Useful for:

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other courses summer jobs professional career after college 11

Management Problem Solving

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Develop a concept (model) for representing and solving the problem (Abstraction)

How shall we think of solving the problem? What is our solution concept?

Spreadsheet modeling, LP, decision analysis, etc. Model the solution

How can we actually solve the problem by gaining effective access to the data, models, documents, etc. needed to implement our solution concept?

Programming, database Analyze, interpret, and communicate the solution results

How good is our solution? Metrics? What exactly does it mean? Are the findings stable or do they rest on precarious assumptions?

Sensitivity Analysis 12

THE MODELING PROCESS

Model Symbolic World Real World Management Situation Analysis Intuition Results Decisions 13

Example

The problem: to understand what is actually going on in a business and competing companies and to take actions that improve the profitability of the firm.

Problem representation or model

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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

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Implementation: in Access. Gather data from the Web. 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

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Interpretation: Use the query facilities to explore beyond a fixed set of reports. Perform what-if queries, plot data, etc.

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Course’s Main Topics

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Modeling with Excel Deterministic Models Probabilistic Models Scripting Database Management Systems Internet "To be able to implement a well-built and organized model in Excel and to populate the model with required data extracted from a variety of sources" 15

Course’s Homepage

http://opim-sun.wharton.upenn.edu/~opim101/spring03/ 16

ToDo

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Read

IDT book

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Chapter 1: "Introduction and Overview"

MW book

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Chapter 1: "Introduction to Modeling" Download Today's Lecture 17