Project Break even analysis

  

1. Ellaborate and research about the project2. Provide two examples of break even analysis and do it in excel sheetAny examples of break even approach3. conclusion
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“Break – even Analysis”
[Please follow this format to write “one page” proposal for your term project]
Name: Pradeep Reddy Poreddy
Course: CMP 684 Management Decision Modeling
Semester: Spring 2016
Management Decision Modeling Project: Break even Analysis
Introduction:
In this project I would mainly describes the break-even analysis in Quantitative approach
and define the process in steps. Break-even analysis is a technique widely used by
production management and management accountants. It is based on categorizing
production costs between those which are “variable” (costs that change when the
production output changes) and those that are “fixed” (costs not directly related to the
volume of production). Where Breakeven analysis is used to determine when your
business will be able to cover all its expenses and begin to make a profit. It is important to
identify your startup costs, which will help you determine your sales revenue needed to
pay ongoing business expenses.
Subtitles:







Defining the Problem
Developing a model
Acquiring Input Data
Developing a Solution
Testing the Solution
Analyzing the Results
Conclusions
References:
Quantitative Analysis for Management, 12th Edition Moodle textbook
https://en.wikipedia.org/wiki/Break-even
The Quantitative Analysis Approach
Defining the problem
Developing a Model
Acquiring Input Data
Developing a Solution
Testing a Solution
Analyzing the results
Implementing the Results
First step: Defining the problem
 The problem must be clearly and concisely defined.
 Must identify the “right” problem.
 May be the most difficult step.
 May require specific, measurable objectives.
 Improperly defining a problem can easily result in no solution or an inappropriate solution.
Second step: Developing a model
 Model is a representation of a situation.
 Models may be: iconic (look-alike the real entity), analog (explains a phenomenon by
reference to some other occurrence) e.g. thermometer, schematic (drawing and pictures)
e.g. map and mathematical (mathematical relationship).
 Models contain variables (controllable or uncontrollable) and parameters.
 Controllable variables are called decision variables.
Good model characteristics should be solvable, realistic, easy to understand and easy to
modify.
 A QA model is an abstract representation of an existing problem in the form of graph or
chart but most frequently in mathematical relationships.
Third step: Acquiring input data
 Obtain the data that are used in the model (input data).
 Obtaining accurate data for the model is essential; even if the model is a perfect
representation of reality, improper data will result in misleading results.
 Data may come from: company reports, company documents, interviews, on-site direct
measurement, and statistical sampling.
Fourth step: Developing a solution
 Involves manipulating the model to arrive at the best (optimal) solution to the problem.
 Solution must be practical and implementable.
 Various methods:
o solution of equation(s)
o trial and error
o complete enumeration
o implementation of algorithm
 A QA solution technique usually applies to a specific type of model.
Fifth step: Testing the solution
 Before a solution can be analyzed and implemented, it needs to be tested completely.
Because the solution depends on the input data and the model, both require testing.
 Determine accuracy and completeness of input data: collect data from a different source
and compare.
Sixth step: Analyzing the result
 Analyzing the results starts with determining the implications of the solution.
 Sensitivity analysis determines how the solutions will change with a different model or input
data.
Final step: Implementing the results
 Implement the results.
 This is the process of incorporating the solution into the company.

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