Qt Primer

LAUNCH PAD-2011

Pre-Orientation Primer No.11

Quantitative Techniques by Dr. Gaurav Chaudhari

INTRODUCTION

? It is the application of quantitative techniques to the managerial problems. ?

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? Quantitative techniques do not make decisions, rather these assists in decision-making process. ?

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? While over reliance on the quantitative methods may be harmful so is the failure to make good use of them ?

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? Mathematical tools have been used for thousands of years ?

? Quantitative analysis can be applied to a wide variety of problem ?

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? It's not enough to just know the mathematics of a technique ?

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? One must understand the specific applicability of the technique, its limitations, and its assumptions ?

There are different types of models

? Schematic models ?

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? Scale models ?

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? Mathematical models ?

Quantitative techniques models are realistic, solvable, and understandable mathematical representations of a situation

? 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 ?

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? Mathematical models that do not involve risk are called deterministic models ?

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? We know all the values used in the model with complete certainty ?

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? Mathematical models that involve risk, chance, or uncertainty are called probabilistic models ?

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? Values used in the model are estimates based on probabilities ?

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Data may come from a variety of sources such as company reports, company documents, interviews, on-site direct measurement, or statistical sampling.

Input data must be accurate – GIGO rule

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:

? Solving equations ?

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? Trial and error – trying various approaches and picking the best result ?

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? Complete enumeration – trying all possible values ?

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? Using an algorithm – a series of repeating steps to reach a 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 ?

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? Results should be logical, consistent, and represent the real situation ?

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? Determine the implications of the solution ?

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? Implementing results often requires change in an organization ?

? The impact of actions or changes needs to be studied and understood before implementation ?

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1. Sensitivity analysis determines how much the results of the analysis will change if the model or input data changes

2. Sensitive models should be very thoroughly tested

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Advantages of quantitative techniques

? Provides logical and systematic