Process of Quantitative Analysis

According to Anderson et al. (2015), quantitative analysis is the critical examination of a situation or occurrence in a significant financial environment using sophisticated statistical and mathematical modeling. It advocates the investigation of all relevant aspects in the specific fiscal situation and is a crucial part of business research.

Defining the current problem is the first step in a quantitative analysis. An event description is carried out initially before examining the effect of a specific component on the entire business or research environment. This stage describes how much the issue affects the players and how it could impair the setup's functionality. The next step is the formulation of a hypothesis and the selection of variables.

The development of a solution begins with the isolation of its key components into analyzable functions. After the variables are separated, their relationship is evaluated. A hypothesis is created based on how the variables associate and how they can be manipulated to develop a different, more desirable outcome (Anderson et al., 2015). Additional data is collected and a sample created. Test theories are subsequently tested on the sample groups and all possible outcomes are noted. The final part of the process entails the organization and presentation of the findings as well as its discussion with key stakeholders or relevant audiences.

Categories of Business Problems Solved through Quantitative Analysis

Quantitative analysis offers a researcher or business establishment the opportunity study a given trend and postulate expected outcomes. It offers the business a rare glimpse into a possible future (Anderson et al., 2015). As such, the establishment can react in time to avert any negative operational or financial situation. Some of the challenges that can be remedied through quantitative analysis include transitional problems such as unfamiliar market dynamics, negative cash flow, rapidly declining market share, loss of investor confidence, and product quality issues.

Solving Business Problems with Appropriate Quantitative Decision-Making Models

According to Anderson et al. (2015), transitional challenges can often be solved by the assumption of progressive decision making models such as the decision trees and simulations. A decision tree presents a plethora of alternative decisions and potential consequences from a single base choice. The base decision often needs to be made at the moment. Some of these may include the hiring of new specialized staff, the purchase of additional equipment and marketing. Simulations may come in handy as they provide insight into a possible future should certain key decisions be made. Challenges such as rapid market share decline and negative cash flow can also be analyzed by the decision tree, which would project the potential impact of any sudden corrective measures taken.

References

Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2015). An introduction to management science: quantitative approaches to decision making. Cengage learning.