Quantitative data includes all information that is presented in a numeric form. Quantitative data is mainly gathered through the use of questionnaires. Several steps are involved in the analysis of quantitative data. The steps involved include cleaning, coding, presentation, interpretation, and finally the discussion of the data as asserted by Bryman and Bell (2015). The cleaning process is aimed at removing elements that are ambiguous from the data. During a quantitative research, the process of content analysis is employed to acquire information from questions that are open-ended. The next step, data coding is the process where numeral and symbols are assigned to responses so that they can fit into a limited amount of categories. The coding process is important because the collected values are changed into values that can be entered into a computer and can then be analyzed statistically. The coding procedure ensures that variables are made so that the analysis process is simplified. The function of the variables is to reduce and summarize data hence ensuring that only essential information is represented. The data coding process can be enabled using applications such as Excel and spreadsheets.
The next step in the data analysis process is the data presentation. It involves the depiction of the coded data in a way that is meaningful to the consumers. Tables and figures are the most commonly used to this effect. When using the computer applications, there are provided functions that can be used to present the data in tables and figures. Data must be adequately summarized so that to ensure that the process of presentation is successful. The presentation of the data may employ descriptive statistics that include percentages, frequencies, means, variations, and standard deviations. Preferential statistics can also be used in the presentation of the data as asserted by Bryman and Bell (2015). This includes the utilization of methods such as Analysis of Variance, t-tests, and regression among others. The final step in the analysis is the interpretation and discussion of the data. Interpretation is done by giving various comments and reactions based on the investigation. Interpretation is made according to the significant findings from the study undertaken. The success of the interpretation process is dependent on the proper understanding of the issues and literature that are under investigation. This enhances depth during interpretation and the subsequent discussions. During the process of interpretation, it is vital to avoid skewing of the objective set. Vested interests should also be avoided to protect the credibility of the report.
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Business Problems That Can Be Solved Through Quantitative Analysis
The first category of a business problem that can be solved by the application of quantitative analysis is quantitative trading. It consists of quantitative analysis as the basis for developing trading strategies ( Waller & Fawcett, 2013). The strategies depend on mathematical calculations and number crunching to acquire trading opportunities. The quantitative trading method is largely applied by large financial institutions where transactions involve the use of a large amount of money. Individual investors are commonly using this method to a greater effect. The second category of business problems that take advantage of the quantitative analysis method is the High-Frequency Trading. This is a trading method that utilizes computers with powerful capabilities to transact many orders at a fast speed. It also employs complex statistical algorithms to analyze markets and make orders depending on the condition of the market.
Banking and insurance problems can effectively be solved using quantitative problems. In banking, the quantitative analysis can be used to calculate the interests accrued on loans and the changes in interest rates. Quantitative methods can also be used to assess the growth of the company with regards to the profits margin. In the insurance sector, the actuaries apply the quantitative analysis methods to assess the amount of money a given entity is supposed to be compensated over a specified period.
Another category of business problem that can be solved using the quantitative analysis method is the algorithmic trading. According to Waller and Fawcett (2013), it is a system that employs mathematical methods that are complex and formulas to come up with quick transactions and decision as regards financial markets. It also uses computers that have a high speed which can clean, code, and present the information at a faster rate.
Solving Business Problems Using Appropriate Decision-Making Models
The first decision-making model is the use of decision trees. They are used to select the best decisions among an array of alternatives. The tree is designed in such a way that the problem is recorded graphically at the root of the diagram, and the branches of the trees represent the alternative solutions. According to Anderson et al . (2015), if the solution requires more decisions, then more branches are added near the base of the tree. Also, the cost, probability, and value of each possible scenario are taken down. The second quantitative model for decision-making that can be used is the network analysis. This model focuses on representing or depicting the association between tasks and events. Project activities are presented as a path beginning from the start of the project to where it ends.
Another model that can be used is referred to as the payback analysis used in case a manager or a business owner wants to buy equipment. The owner of the business will apply quantitative analysis to analyze factors such as warranty period, the life of the equipment, insurance cost, and other expenses. The manager or the business owner will hence apply the payback analysis to determine the strategy of buying that will ensure that they achieve the fastest payback in relation to the initial cost.
In conclusion, quantitative analysis is an important exercise for any business organization. It is a multi-step process that can provide a model for solving many business problems. It can also be used in solving the business problem using appropriate decision making models. Therefore, for a business to achieve its set goals, quantitative analysis must be emphasized because it is the only way a business can assess itself and determine if it utilizing its full potential.
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.
Bryman, A., & Bell, E. (2015). Business research methods . Oxford University Press, USA.
Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. Journal of Business Logistics , 34 (2), 77-84.
