# Introduction to Management Science, Modeling, and Excel Spreadsheets

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Introduction to Management Science, Modeling, and Excel Spreadsheets
Chapter 1 Introduction to Management Science, Modeling, and Excel Spreadsheets

Learning Objectives After completing this chapter, you should be able to: Describe the importance of management science. Describe the advantages of a quantitative approach to problem solving. List some of the applications and use of management science models. Discuss the types of models most useful in management science. Demonstrate the basic building blocks and components of Excel. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Learning Objectives (cont’d)
After completing this chapter, you should be able to: Describe the basic nature and usefulness of break-even analysis. List and briefly explain each of the components of break-even analysis. Solve typical break-even problems manually and with Excel. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

The Importance of Management Science
The discipline of applying advanced analytical methods to help make better decisions. Devoted to solving managerial-type problems using quantitative models Applications of management science Forecasting, capital budgeting, portfolio analysis, capacity planning, scheduling, marketing, inventory management, project management, and production planning. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Table 1–2 Successful Applications of Management Science

Table 1–2 Successful Applications of Management Science (cont’d)

Problem Solving Approaches
Managers tend to use a qualitative approach to problem solving when The problem is fairly simple. The problem is familiar. The costs involved are not great. Managers tend to use a quantitative approach when The problem is complex. The problem is not familiar. The costs involved are substantial. Enough time is available to analyze the problem. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Directs attention to the essence of an analysis: to solve a specific problem. Improves planning which helps prevent future problems Results in more objective decisions than purely qualitative analysis. Incorporates advances in computational technologies to managerial problem-solving. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Models A Model Symbolic models Mathematical models
An abstraction of reality. It is a simplified, and often idealized, representation of reality. Examples : an equation, an outline, a diagram, and a map By its very nature a model is incomplete. Provides an alternative to working with reality Symbolic models Use numbers and algebraic symbols Mathematical models Decision variables Uncontrollable variables Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Deterministic versus Probabilistic Models
Deterministic models Used for problems in which information is known with a high degree of certainty. Used to determine an optimal solution to the problem. Probabilistic models Used when it cannot be determined precisely what values (requiring probabilities) will occur (usually in the future). Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Figure 1–1 The Management Science Approach

Figure 1–2 DSS Framework Source: E. Turban, Jay Aronson, and Ting-Peng Liang, Decision Support Systems and Intelligence Systems, 7th ed. (Upper Saddle River, NJ: Prentice Hall, 2005), p. 109. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Exhibit 1-2 Functions Screen

Breakeven Analysis Breakeven analysis (cost-volume analysis)
Is concerned with the interrelationship of costs, volume (quantity of output or sales), and profit. The Break-Even Point (BEP) The volume for which total revenue and total cost are equal. The dividing line between profit and loss; sales higher than the break-even point will result in a profit, while sales that is lower than the break-even point will result in a loss. Where you get “out of the red.” Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Breakeven Analysis Breakeven analysis (cost-volume analysis)
Is concerned with the interrelationship of costs, volume (quantity of output or sales), and profit. Components of Break-Even Analysis Volume: the level of output of a machine, department, or organization, or the quantity of sales. Revenue: the income generated by the sale of a product. Total revenue = revenue per unit (selling price per unit) multiplied by units (volume) sold. Costs: costs that must be taken into account Fixed costs are not related to the volume of output. Variable costs increase and decrease with output. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Assumptions of Break-Even Analysis
The revenue per unit is the same for all volumes. The variable cost per unit is the same for all volumes. Fixed cost is the same for all levels of volume. Only one product is involved. All output is sold. All relevant costs are accounted for, and correctly assigned to either the fixed cost category or the variable cost category. Copyright © 2007 The McGraw-Hill Companies. All rights reserved.

Figure 1–3 Total Revenue Increases Linearly as Volume Increases

Figure 1–5 Total Variable Cost

Figure 1–7 Profit and the Break-Even Point

Exhibit 1–4 Break-Even Analysis

Exhibit 1–5 Goal Seek Input Screen

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