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INTRODUCTION TO MODELING Modeling Approach to Decision Making: Uses spreadsheet software such as Excel® This approach is easy for managers to use, Results.

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Presentation on theme: "INTRODUCTION TO MODELING Modeling Approach to Decision Making: Uses spreadsheet software such as Excel® This approach is easy for managers to use, Results."— Presentation transcript:

1 INTRODUCTION TO MODELING Modeling Approach to Decision Making: Uses spreadsheet software such as Excel® This approach is easy for managers to use, Results in better management decisions, Provides important insights into problem. Involves spreadsheet based management models

2 THE MODELING PROCESS 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

3 Operations Research / Management Science Origin: Military services early in World War 2. Urgent need to allocate scarce resources to the various military operations and to the activities within war operation in an effective manner Research teams called upon to apply a scientific approach to this and other strategic and tactical problems This scientific approach is transferred and, and is used extensively in the industrial part of business, as well as in a lot of other areas such as government, engineering, economics, natural and social sciences Definition. The use of modern science, with a special weight on numerical techniques, on complex problems concerning management of people, machines, raw materials and money, in business, industry, the public sector and military services. The goal of OR is to help the management to make strategical and tactical decisions on a more scientific basis. Mathematical programming Roughly speaking, the part of OR that focuses primarily on deterministic problems where probability theory is not needed Approach: to construct a mathematical model to represent the problem of interest, identifying decisions to be made and constraints on the decisions. An algorithm is then used to solve for an optimal solution

4 Why learn Management Science? You will learn different techniques that may give public organizations and private firms and farms a more solid foundation for decision-making You will develop your modeling skills in general --> developing your abilities for logical thinking You will sharpen your quantitative skills You will develop your intuition by studying many different types of models

5 Management Situation Decisions Model Analysis Results Intuition Abstraction Interpretation Real World Symbolic World as applied to the first two stages of decision making. THE MODELING PROCESS

6 Management Situation Decisions Model Analysis Results Intuition Abstraction Interpretation Real World Symbolic World The Role of Managerial Judgment in the Modeling Process: Managerial Judgment THE MODELING PROCESS

7 Decision Support Models force you to be explicit about your objectives. 1. identify and record the types of decisions that influence those objectives. 2. identify and record interactions and trade-offs among those decisions. 3. think carefully about which variables to include. 4. consider what data are pertinent and their interactions. 5. recognize constraints or limitations on the values. 6. Models allow communication of your ideas and understanding to facilitate teamwork. 7. Models allow us to use the analytical power of spreadsheets hand in hand with the data storage and computational speed of computers. THE MODELING PROCESS

8 MORE ON MODELS A model is a carefully selected abstraction of reality. Symbolic models 1. always simplify reality. 2. incorporate enough detail so that the result meets your needs, it is consistent with the data you have available, it can be quickly analyzed. Decision models are symbolic models in which some of the variables represent decisions that must or could be made. Decision variables are variables whose values you can control, change or set.

9 MORE ON DECISION MODELS Decision models typically include an explicit performance measure that gauges the attainment of that objective. In summary, decision models For example, the objective may be to maximize profit or minimize cost in relation to a performance measure (such as sales revenue, interest income, etc). 1. selectively describe the managerial situation. 2. designate decision variables. 3. designate performance measure(s) that reflect objective(s).

10 BUILDING MODELS 1. Study the Environment to Frame the Managerial Situation A problem statement involves possible decisions and a method for measuring their effectiveness. To model a situation, you first have to frame it (i.e., develop an organized way of thinking about the situation). Steps in modeling: 2. Formulate a selective representation 3. Construct a symbolic (quantitative) model

11 1. Studying the Environment 2. Formulation Select those aspects of reality relevant to the situation at hand. 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. BUILDING MODELS

12 Performance Measure(s) Decisions (Controllable) Parameters (Uncontrollable) Exogenous Variables Model Consequence Variables Endogenous Variables The “Black Box” View of a Model BUILDING MODELS

13 3. Model Construction The next step is to construct a symbolic model. Mathematical relationships are developed. Graphing the variables may help define the relationship. Var. X Var. Y Cost A Cost B A + B To do this, use “Modeling with Data” technique. BUILDING MODELS

14 MODELING WITH DATA Consider the following data. Graphs are created to view any relationship(s) between the variables. This is the first step in formulating the equations in the model.

15 DETERMINISTIC AND PROBABILISTIC 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.

16 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.

17 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)


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