Sensitivity Analysis The variables used to develop the table‚ including sales price‚ variable costs‚ unit sales‚ and the unit growth rate‚ are all most likely‚ or base-case‚ values‚ and the resulting $25‚517 NPV shown in Part 5 is called the base-case NPV. Now we ask a series of "what if" questions: "What if unit sales falls 30 percent below the most likely level?" In our sensitivity analysis we hold the other variables at their base case levels and then examine the situation when the key variables
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SENSITIVITY ANALYSIS The solution obtained by simplex or graphical method of LP is based on deterministic assumptions i.e. we assume complete certainty in the data and the relationships of a problem namely prices are fixed‚ resources known‚ time needed to produce a unit exactly etc. However in the real world‚ conditions are seldom static i.e. they are dynamic. How can such discrepancy be handled? For example if a firm realizes that profit per unit is not Rs 5 as estimated but instead closer
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What is...? series Supported by sanofi-aventis New title Health economics What is sensitivity analysis? Matthew Taylor PhD MSc Senior Consultant‚ York Health Economics Consortium‚ University of York G While economic models are a useful tool to aid decision-making in healthcare‚ there remain several types of uncertainty associated with this method of analysis. G One-way sensitivity analysis allows a reviewer to assess the impact that changes in a certain parameter will have on the model’s
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Sensitivity analysis is a technique that indicates exactly how much a project’s profitability (NPV or IRR) will change in response to a given change in a single input variable‚ other things held constant. Sensitivity analysis begins with a base case developed using expected values (in the statistical sense) for all uncertain variables. Then‚ each uncertain variable is usually changed by a fixed percentage amount above and below its expected value‚ holding all other variables constant at their expected
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Linear Programming Notes VII Sensitivity Analysis 1 Introduction When you use a mathematical model to describe reality you must make approximations. The world is more complicated than the kinds of optimization problems that we are able to solve. Linearity assumptions usually are significant approximations. Another important approximation comes because you cannot be sure of the data that you put into the model. Your knowledge of the relevant technology may be imprecise‚ forcing you to approximate
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Sensitivity Analysis Source: Introduction to Management Science 10 e‚ Anderson Sweeney Williams Example 1 Max s.t. 5x1 + 7x2 x1 < 6 2x1 + 3x2 < 19 x1 + x2 < 8 x1‚ x2 > 0 x2 8 7 6 5 4 3 2 1 x1 + x2 < 8 Max 5x1 + 7x2 x1 < 6 Optimal: x1 = 5‚ x2 = 3‚ z = 46 2x1 + 3x2 < 19 x1 1 2 3 4 5 6 7 8 9 10 x2 8 7 6 5 4 3 2 1 5 5 Feasible Region 1 1 1 2 3 4 4 4 3 3 2 2 5 6 7 8 9 10 x1 Example 1 • Range of Optimality for c1 The slope of the objective
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Scenario Analysis of Thailand IBMS403/404 0810937 Chenchen Chen 0810992 Yuan Cui 0823155 Cherry Liu 1 Content Table & Figure ............................................................................................................................................ 5 Chapter 1 business idea............................................................................................................................3 Step 1 Deciding on the company’s competitive advantage...........
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need for Spellman to wade through the draft documents? (224 words) There is definitely the need for Richard Spellman to go through the draft documents. He needs to ensure that the employment deal that he had discussed with Walt Sawyer was in fact what the contract spelled out and that all information that has been exchanged informally‚ has been taken into consideration on the formal agreement.. In the “Open Items” email sent by Spellman to Sawyer‚ the only topic that wasn’t explained in further
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Sensitivity analysis‚ what-if analysis‚ and goal seeking analysis are used for same purpose to analyze complex relationships among millions of data items to discover business patterns‚ trends. All of them are part of Decision support systems (DSS) analysis techniques. It helps managers to explore possible alternatives. What-If Analysis: In what-if analysis‚ an end user makes changes to variables‚ or relationships among variables‚ and observes the resulting changes in the values of
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needed. The team also believed that the customer base that had already tried the fresh pasta would have higher awareness of the pizza product. The Cucina Fresca project‚ introducing fresh pasta had been successful‚ however there are certain differences between the pasta and pizza project: In the fresh whole grain pasta market‚ the company had the first mover advantage. Pasta required TruEarth to upgrade its manufacturing facility‚ thereby requiring more initial investment. Another competitor had
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