The Importance Of Quantitative Analysis

Introduction

The understanding, knowledge and use of quantitative approach or tools and methodologies for running an effective analysis are highly important in today’s world. Each business, despite its size or industry, has its specific needs and goals, so in order to reach these goals effectively it is important to use such tools and techniques, for example: decision making, linear programming, forecasting, optimization, inventory, simulation and many more. The use of such techniques can help to cut down costs, allocate resources more effectively, and plan production or ordering schedule by analyzing current data. Many businesses are using data analysis for future forecasting and inventory, for example, this tool is highly implemented within

These approaches will be applied and demonstrated on using the example of the small business, precisely bakery with its production and retail.

To be able to understand the results of the analysis better, it would be important to understand the meaning, role and complexity of each of these techniques, as well as their limitations and advantages. With a theoretical understanding and demonstrated example it would be easier to understand why data analysis is so important, what it mean towards reaching set goals and also, why it is almost impossible to run proper analysis using just one technique.

Before implementing any of the mentioned above techniques it is essential to structure the problem (using a 5 step approach of decision making) and analyze the problem. For analyzing the problem quantitative and qualitative approaches can be used, but, as mentioned above, the quantitative approach will be demonstrated. To be able to start, constrains, objective functions, and uncontrollable inputs should be

This approach is known as a mathematical technique for evaluating an optimal and best use of an organization’s recourses and has a three stage process: problem formulation, problem solution and solution interpretation and implementation. In order to do so usually two or more variables are used with the direct and precise relationship in between them. With the bakery example linear programming is demonstrated in order to evaluate an optimal production capacity and its optimization. To conduct effectively linear programming it is important to evaluate an objective that should be achieved, alternative course of action, make sure that resources are limited and that there is a possibility to express the objectives and limitations as mathematical equations or inequalities, as for a successful implementation of this method it should be linear. To be able to run this method it is important to correctly formulate your problem, constraints should affect feasible region otherwise it’s a redundant constraint and should be removed from the problem ( sometimes redundant constrains are hardly recognized until the problem is solved). Linear programming is one of the most popular quantitative methods due to its simplicity in understanding and implementation, provides better quality of decision making, it enables users to solve diverse combination problems and is very adaptive and flexible in terms of analysis, however