1. MGS3100_01.ppt/Aug 25, 2015/Page 1 Georgia State University - Confidential MGS 3100 Business Analysis Introduction - Why Business Analysis Aug 25 and 26, 2015

2. MGS3100_01.ppt/Aug 25, 2015/Page 2 Georgia State University - Confidential Agenda Business Analysis - Models The Modeling Process Introduction to Decision Sciences

3. MGS3100_01.ppt/Aug 25, 2015/Page 3 Georgia State University - Confidential What is Decision Sciences Grocery Industry Kroger Travel Industry Delta SkyMiles Marriott Rewards Gambling Industry MGM Mirage Players Club The Mirage Treasure Island Bellagio New York New York MGM Grand Retail Business Best Buy Circuit City Macy

4. MGS3100_01.ppt/Aug 25, 2015/Page 4 Georgia State University - Confidential Agenda Business Analysis - Models The Modeling Process Introduction to Decision Sciences

5. MGS3100_01.ppt/Aug 25, 2015/Page 5 Georgia State University - Confidential MGS 3100 Business Analysis Course Overview

6. MGS3100_01.ppt/Aug 25, 2015/Page 6 Georgia State University - Confidential Deterministic Models vs. Probabilistic (Stochastic) Models Deterministic Models are models in which all relevant data are assumed to be known with certainty. can handle complex situations with many decisions and constraints are very useful when there are few uncontrolled model inputs that are uncertain. are useful for a variety of management problems. are easy to incorporate constraints on variables. software is available to optimize constrained models. allows for managerial interpretation of results. constrained optimization provides useful way to frame situations. will help develop your ability to formulate models in general.

7. MGS3100_01.ppt/Aug 25, 2015/Page 7 Georgia State University - Confidential Deterministic Models vs. Probabilistic (Stochastic) Models Probabilistic (Stochastic) Models are models in which some inputs to the model are not known with certainty. uncertainty is incorporated via probabilities on these “random” variables. very useful when there are only a few uncertain model inputs and few or no constraints. often used for strategic decision making involving an organization’s relationship to its environment.

8. MGS3100_01.ppt/Aug 25, 2015/Page 8 Georgia State University - Confidential Classification of Models By problem type Forecasting Decision Analysis Constrained Optimization Monte Carlo Simulation By data type Time series Exponential smoothing Moving average Cross sectional Multiple linear regression By causality Causal: causal variable Non-causal: surrogate variable Methodologies 1. Qualitative Delphi Methods 2. Quantitative - Non- statistical Using “comparables” 3. Quantitative - Statistical Time-series Regression

9. MGS3100_01.ppt/Aug 25, 2015/Page 9 Georgia State University - Confidential Reasons for Using Models Models force you to: Be explicit about your objectives Identify and record the decisions that influence those objectives Identify and record interactions and trade-offs among those decisions Think carefully about variables to include and their definitions in terms that are quantifiable Consider what data are pertinent for quantification of those variables and determining their interactions Recognize constraints (limitations) on the values that those quantified variables may assume Allow communication of your ideas and understanding to facilitate teamwork

10. MGS3100_01.ppt/Aug 25, 2015/Page 10 Georgia State University - Confidential Agenda Business Analysis - Models The Modeling Process Introduction to Decision Sciences

11. MGS3100_01.ppt/Aug 25, 2015/Page 11 Georgia State University - Confidential The Modeling Process Quantitative - Statistical Variables and Attributes Objective Hierarchies Influence Diagrams Mathematical Representation Testing and Validation Implementation and use Describe Problem / opportunity Identify Overall Objective Organize Sub-Objectives into a hierarchy Identify Model’s Objective Determine all variables and their attributes Decide on Measurement / Data Collection Graphically depict relationships among variables Distinguish between Decision and outcome variables Determine mathematical relationships among variables Develop mathematical model(s) Evaluate reliability and validity Understand limitations Implement models in DSSs Clarify assumptions, inputs, and outputs

12. MGS3100_01.ppt/Aug 25, 2015/Page 12 Georgia State University - Confidential The Modeling Process Quantitative – Non-Statistical Managerial Approach to Decision Making Manager analyzes situation (alternatives) Makes decision to resolve conflict Decisions are implemented Consequences of decision These steps Use Spreadsheet Modeling

13. MGS3100_01.ppt/Aug 25, 2015/Page 13 Georgia State University - Confidential The Modeling Process Management Situation Decisions Model Analysis Results Intuition Abstraction Interpretation Real World Symbolic World As applied to the first two stages of decision making

14. MGS3100_01.ppt/Aug 25, 2015/Page 14 Georgia State University - Confidential The Modeling Process Management Situation Decisions Model Analysis Results Intuition Abstraction Interpretation Real World Symbolic World Managerial Judgment The Role of Managerial Judgment in the Modeling Process:

15. MGS3100_01.ppt/Aug 25, 2015/Page 15 Georgia State University - Confidential Building Models To model a situation, you first have to frame it (i.e. develop an organized way of thinking about the situation). A problem statement involves possible decisions and a method for measuring their effectiveness. Steps in modeling: 1.Study the Environment to Frame the Managerial Situation 2.Formulate a selective representation 3.Construct a symbolic (quantitative) model

16. MGS3100_01.ppt/Aug 25, 2015/Page 16 Georgia State University - Confidential Building Models 1.Studying the Environment Select those aspects of reality relevant to the situation at hand. 2.Formulation Specific assumptions and simplifications are made. Decisions and objectives must be explicitly identified and defined. Identify the model’s major conceptual ingredients using “Black Box” approach. Performance Measure(s) Decisions (Controllable) Parameters (Uncontrollable) Exogenous Variables Model Consequence Variables Endogenous Variables The “Black Box” View of a Model

17. MGS3100_01.ppt/Aug 25, 2015/Page 17 Georgia State University - Confidential Building Models 3.Study the Environment to Frame the Managerial Situation The next step is to construct a symbolic model. Mathematical relationships are developed. Graphing the variables may help define the relationship. To do this, use “Modeling with Data” technique. Var. X Var. Y Cost A Cost B A + B

18. MGS3100_01.ppt/Aug 25, 2015/Page 18 Georgia State University - Confidential Iterative Model Building DEDUCTIVE MODELING INFERENTIAL MODELING PROBABILISTIC MODELS DETERMINISTIC MODELS Model Building Process Models Decision Modeling (‘What If?’ Projections, Decision Analysis, Decision Trees, Queuing) Decision Modeling (‘What If?’ Projections, Optimization) Data Analysis (Forecasting, Simulation Analysis, Statistical Analysis, Parameter Estimation) Data Analysis (Data Base Query, Parameter Evaluation

19. MGS3100_01.ppt/Aug 25, 2015/Page 19 Georgia State University - Confidential Modeling and Real World Decision Making Four Stages of applying modeling to real world decision making: Stage 1: Study the environment, formulate the model and construct the model. Stage 2: Analyze the model to generate results. Stage 3: Interpret and validate model results. Stage 4: Implement validated knowledge.

20. MGS3100_01.ppt/Aug 25, 2015/Page 20 Georgia State University - Confidential Modeling and Real World Decision Making Modeling Term Management Lingo Formal DefinitionExample Decision Variable Lever Controllable Exogenous Investment Input Quantity Amount Parameter Gauge Uncontrollable Exogenous Interest Rate Input Quantity Consequence Outcome Endogenous Output Commissions Variable Variable Paid Performance Yardstick Endogenous Variable Return on Measure Used for Evaluation Investment (Objective Function Value)