I realized how important business analytics is through the rise and fall of my cousins company. My cousin established an outdoor product brand three years ago, but he struggled to choose the location for the retail store. He opened the first retail store in a busy shopping mall in Shanghai. Although the shopping mall had a strong exposure, customers of the mall preferred luxuries much more than outdoor products, and the stores earnings hardly offset the rent. Then, my cousin moved the stores location to a less crowded merchandise street, but it turned out that only professional outdoor enthusiasts would consume. It was after many time-consuming and unprofitable trials, he finally found an appropriate location for the store. I saw the reason why business analytics matters through this incident because I could imagine that with the help of statistical and financial analysis, factors that affected the performance of retail stores could be quantified and evaluated to support and also adjust decision-making prior to the implementation of business plans. Although I understand that trial and error is a crucial and sometimes inevitable method to the success of a business, the process of business analytics not only can minimize the cost of trials by recognizing the optimum choice among different paths of business plans and decreasing the number of failing trials but also help administrators of firms to gain the perc
eption of the markets big picture from a technical perspective.
As a student of Financial Mathematics, I have equipped myself with statistical and financial models that can promote strategic marketing and operational decisions of businesses. For example, I have learned how to apply multilinear regression analysis by EViews in one of my econometric courses. In a project of this course, I was assigned to carry out a regression analysis based on 300 random samples for evaluating the relationship between US salary and its related factors such as gender, race, and work experience. Through my exploration of EViews and regression models, I was able to find important statistical values, including T-value, P-value, and R-squared, for those variables, and built a reasonable regression model that was in accord with my initial assumption for the coefficient of the regression equation. This project triggered my interest in business analytics because it was fascinating to know that real-life factors that seem uncorrelated to salary, such as religion and political tendency, actually can be incorporated into a quantitative pattern, which made me eager to know how this mode can be applied to business. Since technological proficiency is an important idiosyncrasy for a career in business analytics, which fits with my enthusiasm and educational background, thus I believe that business analytics is the right career path for me.