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Quantitative analysis is a scientific approach to managerial decision making that involves defining problems, acquiring data, developing models, testing solutions, analyzing results, and implementing solutions. It uses mathematical tools to process raw data into meaningful information. Potential problems include conflicting viewpoints, outdated solutions, difficulties acquiring and understanding models, and resistance to change. Implementation is critical to success but challenging to achieve.
![How To Develop a Quantitative Analysis Model
Expenses can be represented as the sum of fixed and
variable costs and variable costs are the product of
unit costs times the number of units
Profit = Revenue – (Fixed cost + Variable cost)
Profit = (Selling price per unit)(number of units
sold) – [Fixed cost + (Variable costs per
unit)(Number of units sold)]
Profit = sX – [f + vX]
Profit = sX – f – vX
where
s = selling price per unit v = variable cost per unit
f = fixed cost X = number of units sold](https://image.slidesharecdn.com/render01edited-121120194704-phpapp02-171115213835/85/Render01edited-121120194704-phpapp02-18-320.jpg)
![How To Develop a Quantitative Analysis Model
Expenses can be represented as the sum of fixed and
variable costs and variable costs are the product of
unit costs times the number of units
Profit = Revenue – (Fixed cost + Variable cost)
Profit = (Selling price per unit)(number of units
sold) – [Fixed cost + (Variable costs per
unit)(Number of units sold)]
Profit = sX – [f + vX]
Profit = sX – f – vX
where
s = selling price per unit v = variable cost per unit
f = fixed cost X = number of units sold
The parameters of this model
are f, v, and s as these are the
inputs inherent in the model
The decision variable of
interest is X](https://image.slidesharecdn.com/render01edited-121120194704-phpapp02-171115213835/85/Render01edited-121120194704-phpapp02-19-320.jpg)
![Pritchett’s Precious Time Pieces
Profits = sX – f – vX
The company buys, sells, and repairs old clocks.
Rebuilt springs sell for $10 per unit. Fixed cost of
equipment to build springs is $1,000. Variable cost
for spring material is $5 per unit.
s = 10 f = 1,000 v = 5
Number of spring sets sold = X
If sales = 0, profits = ––$1,000$1,000
If sales = 1,000, profits = [(10)(1,000) – 1,000 – (5)(1,000)]
= $4,000](https://image.slidesharecdn.com/render01edited-121120194704-phpapp02-171115213835/85/Render01edited-121120194704-phpapp02-20-320.jpg)
Render01edited 121120194704-phpapp02
- 1. Introduction to Quantitative Analysis Chapter 1 To accompany Quantitative Analysis for Management, Tenth Edition, by Render, Stair, and Hanna Power Point slides created by Jeff Heyl © 2009 Prentice-Hall, Inc.
- 2. Chapter Outline 1.1 Introduction 1.2 What Is Quantitative Analysis? 1.3 The Quantitative Analysis Approach 1.4 How to Develop a Quantitative Analysis Model 1.5 Possible Problems in the Quantitative Analysis Approach 1.6 Implementation — Not Just the Final Step
- 3. Introduction • Mathematical tools have been used for thousands of years • Quantitative analysis can be applied to a wide variety of problems • It’s not enough to just know the mathematics of a technique • One must understand the specific applicability of the technique, its limitations, and its assumptions
- 4. Examples of Quantitative Analyses • Taco Bell saved over $150 million using forecasting and scheduling quantitative analysis models • NBC television increased revenues by over $200 million by using quantitative analysis to develop better sales plans • Continental Airlines saved over $40 million using quantitative analysis models to quickly recover from weather delays and other disruptions
- 5. Meaningful Information What is Quantitative Analysis? Quantitative analysisQuantitative analysis is a scientific approach to managerial decision making whereby raw data are processed and manipulated resulting in meaningful information Raw Data
- 6. What is Quantitative Analysis? Quantitative factorsQuantitative factors might be different investment alternatives, interest rates, inventory levels, demand, or labor cost Qualitative factorsQualitative factors such as the weather, state and federal legislation, and technology breakthroughs should also be considered – Information may be difficult to quantify but can affect the decision-making process
- 7. Implementing the Results Analyzing the Results Testing the Solution Developing a Solution Acquiring Input Data Developing a Model The Quantitative Analysis Approach Defining the Problem Figure 1.1
- 8. Defining the Problem Need to develop a clear and concise statement that gives direction and meaning to the following steps – This may be the most important and difficult step – It is essential to go beyond symptoms and identify true causes – May be necessary to concentrate on only a few of the problems – selecting the right problems is very important – Specific and measurable objectives may have to be developed
- 9. Developing a Model Quantitative analysis models are realistic, solvable, and understandable mathematical representations of a situation There are different types of models $ Advertising $Sales Y = b0 + b1 X Schematic models Scale models
- 10. Developing a Model • Models generally contain variables (controllable and uncontrollable) and parameters • Controllable variables are generally the decision variables and are generally unknown • Parameters are known quantities that are a part of the problem
- 11. Acquiring Input Data Input data must be accurate – GIGO rule Data may come from a variety of sources such as company reports, company documents, interviews, on-site direct measurement, or statistical sampling Garbage In Process Garbage Out
- 12. Developing a Solution • The best (optimal) solution to a problem is found by manipulating the model variables until a solution is found that is practical and can be implemented • Common techniques are – SolvingSolving equations – Trial and errorTrial and error – trying various approaches and picking the best result – Complete enumerationComplete enumeration – trying all possible values – Using an algorithmalgorithm – a series of repeating steps to reach a solution
- 13. Testing the Solution Both input data and the model should be tested for accuracy before analysis and implementation – New data can be collected to test the model – Results should be logical, consistent, and represent the real situation
- 14. Analyzing the Results Determine the implications of the solution – Implementing results often requires change in an organization – The impact of actions or changes needs to be studied and understood before implementation Sensitivity analysisSensitivity analysis determines how much the results of the analysis will change if the model or input data changes Sensitive models should be very thoroughly tested
- 15. Implementing the Results Implementation incorporates the solution into the company – Implementation can be very difficult – People can resist changes – Many quantitative analysis efforts have failed because a good, workable solution was not properly implemented Changes occur over time, so even successful implementations must be monitored to determine if modifications are necessary
- 16. Modeling in the Real World Quantitative analysis models are used extensively by real organizations to solve real problems – In the real world, quantitative analysis models can be complex, expensive, and difficult to sell – Following the steps in the process is an important component of success
- 17. How To Develop a Quantitative Analysis Model An important part of the quantitative analysis approach Let’s look at a simple mathematical model of profit Profit = Revenue – Expenses
- 18. How To Develop a Quantitative Analysis Model Expenses can be represented as the sum of fixed and variable costs and variable costs are the product of unit costs times the number of units Profit = Revenue – (Fixed cost + Variable cost) Profit = (Selling price per unit)(number of units sold) – [Fixed cost + (Variable costs per unit)(Number of units sold)] Profit = sX – [f + vX] Profit = sX – f – vX where s = selling price per unit v = variable cost per unit f = fixed cost X = number of units sold
- 19. How To Develop a Quantitative Analysis Model Expenses can be represented as the sum of fixed and variable costs and variable costs are the product of unit costs times the number of units Profit = Revenue – (Fixed cost + Variable cost) Profit = (Selling price per unit)(number of units sold) – [Fixed cost + (Variable costs per unit)(Number of units sold)] Profit = sX – [f + vX] Profit = sX – f – vX where s = selling price per unit v = variable cost per unit f = fixed cost X = number of units sold The parameters of this model are f, v, and s as these are the inputs inherent in the model The decision variable of interest is X
- 20. Pritchett’s Precious Time Pieces Profits = sX – f – vX The company buys, sells, and repairs old clocks. Rebuilt springs sell for $10 per unit. Fixed cost of equipment to build springs is $1,000. Variable cost for spring material is $5 per unit. s = 10 f = 1,000 v = 5 Number of spring sets sold = X If sales = 0, profits = ––$1,000$1,000 If sales = 1,000, profits = [(10)(1,000) – 1,000 – (5)(1,000)] = $4,000
- 21. Pritchett’s Precious Time Pieces 0 = sX – f – vX, or 0 = (s – v)X – f Companies are often interested in their break-evenbreak-even pointpoint (BEP). The BEP is the number of units sold that will result in $0 profit. Solving for X, we have f = (s – v)X X = f s – v BEP = Fixed cost (Selling price per unit) – (Variable cost per unit)
- 22. Pritchett’s Precious Time Pieces 0 = sX – f – vX, or 0 = (s – v)X – f Companies are often interested in their break-evenbreak-even pointpoint (BEP). The BEP is the number of units sold that will result in $0 profit. Solving for X, we have f = (s – v)X X = f s – v BEP = Fixed cost (Selling price per unit) – (Variable cost per unit) BEP for Pritchett’s Precious Time Pieces BEP = $1,000/($10 – $5) = 200 units Sales of less than 200 units of rebuilt springs will result in a loss Sales of over 200 units of rebuilt springs will result in a profit
- 23. Advantages of Mathematical Modeling 1. Models can accurately represent reality 2. Models can help a decision maker formulate problems 3. Models can give us insight and information 4. Models can save time and money in decision making and problem solving 5. A model may be the only way to solve large or complex problems in a timely fashion 6. A model can be used to communicate problems and solutions to others
- 24. Models Categorized by Risk • Mathematical models that do not involve risk are called deterministic models – We know all the values used in the model with complete certainty • Mathematical models that involve risk, chance, or uncertainty are called probabilistic models – Values used in the model are estimates based on probabilities
- 25. Possible Problems in the Quantitative Analysis Approach Defining the problem – Problems are not easily identified – Conflicting viewpoints – Impact on other departments – Beginning assumptions – Solution outdated Developing a model – Fitting the textbook models – Understanding the model
- 26. Possible Problems in the Quantitative Analysis Approach Acquiring input data – Using accounting data – Validity of data Developing a solution – Hard-to-understand mathematics – Only one answer is limiting Testing the solution Analyzing the results
- 27. Implementation – Not Just the Final Step Lack of commitment and resistance to change – Management may fear the use of formal analysis processes will reduce their decision-making power – Action-oriented managers may want “quick and dirty” techniques – Management support and user involvement are important
- 28. Implementation – Not Just the Final Step Lack of commitment by quantitative analysts – An analysts should be involved with the problem and care about the solution – Analysts should work with users and take their feelings into account
- 29. Summary • Quantitative analysis is a scientific approach to decision making • The approach includes – Defining the problem – Acquiring input data – Developing a solution – Testing the solution – Analyzing the results – Implementing the results
- 30. Summary • Potential problems include – Conflicting viewpoints – The impact on other departments – Beginning assumptions – Outdated solutions – Fitting textbook models – Understanding the model – Acquiring good input data – Hard-to-understand mathematics – Obtaining only one answer – Testing the solution – Analyzing the results