A Decision of Uncertainty - Research Paper Example

A Decision of Uncertainty To Diversify the Range of Products or Open a New Branch The last financial year was a rather successful time for the enterprise I work for part time. It is a new business enterprise that has been in existence for three years. It deals with service of coffee and coffee products. It started on a slow pace and showed stunted growth and little chances of success for the first six months. In fact, the proprietor thought of closing it down during its seventh month of existence.

That was the moment I appeared in the scene and was assigned the duty of marketing the coffee shop. Within a period of two months, changes became apparent. I lured classmates and more clients streamed in. By the end of my summer vacation, the proprietor reported supernormal profits. It is for this reason that the business owner honored me with the task to decide the future of the business. Following its success over the past two years, it has accumulated enough savings to either open a new branch or diversify its range of products on the single business unit he currently owns.

Over the prosperous period of time, the business’ profits margin increased steadily from 23% to 32%, then 53%, 109% and finally 86% after periods of 5 months. Having reached its break even period, the business has accumulated enough money to diversify the range of products on offer in the same premises or to acquire other premises and have another branch of the same product range offered presently. Research Making this decision was an uphill task. The future of the enterprise depended on me and I was determined to prove my worth and give a viable solution.

I had to do extensive research on market trends of the locality. This information was available in the local federal offices that harbored a collection of businesses that had failed and those that had prospered. In addition, I was obliged to conduct a reliable survey on the brand name of the business. Having a successfully operating branch elsewhere depended upon how well known the enterprise had become. It was also of essence that I investigate the possibility of the current clientele base gaining interest in the kind of would-be newly introduced products.

The research that included collection of data from various stakeholders took two months. At the end of the 3 months, I had all the statistical data I needed to analyze and come up with an amicable solution. Given the complexity of data analysis involved, it was not practical to use a single statistical data analysis approach. First, I used Bayes’ Theorem to evaluate the probability of a business enterprise that operates in the locality thriving in other locations. The same theorem was used in determining whether or not an enterprise that expands its operations within the same locality would thrive or not.

This statistical analysis relied on data collected from federal business registrars. Bayes’ theorem emulates the method of logical deduction by determining the extent of confidence in probable conclusions on the foundation of available facts (Winkler, 2009, p. 59). The proof is most excellently stated in accordance with subjective probability. Subjective probability assigns probability after considering the outcomes of information and evaluation of the gathered data. Bayer’s theorem can, therefore, be employed in identifying confidence levels for determination of the underlying dilemma.

My research found out that: 60.13% of businesses that start other branches elsewhere thrive 59.95% of businesses that expand locally thrive I then set up variables of thriving probabilities as: T1= Probability of a business thriving locally T2= Probability of a branch thriving elsewhere Therefore, the probability of a business not thriving is P(T’1)=0.3987 and P(T’2) = 0.4005 Probability according to Bayes’ shows that: (Spanos 200, 49) The probability that the business idea will thrive, whichever way, is 0.57. Event Prior Probability P(Ti) Conditional Probability P(B|Ti) Joint Probability P(Ai and B) Posterior Probability P(Ai|B) 0.3987 0.6013 0.

3562 03562 / .1875 = 0.43 0.4005 0.5995 0.4392 0.4392/ .1875 = 0.57 P(B) = .1875 = 1.00 Upon application of binomial distribution formula: (Walker, 2013, p. 345) I found out that the possibility of the business thriving better with a branch elsewhere was 0.45 against 0.37 of the business surviving in the same place with an increased range of products. This was after a discerning analysis of several possibilities including competition and clientele reaction. Decision The statistical analysis expressed above provided me with a means of avoiding the riskier situation of the two available ones.

Whereas there were errors involved in the acquisition and calculation of data, the results obtained provided a subtle solution to the issue at stake. I reached the decision to advise the proprietor to start another branch of the same enterprise elsewhere. This would be followed by intense marketing. Convincing masses would be easier than before since there was an established branch to refer to. References Spanos, A. (2000). Probability theory and statistical inference: Econometric modeling with observational data.

Cambridge [u.a.]: Cambridge Univ. Press. Walker, J. T., & Maddan, S. (2013). Statistics in criminology and criminal justice: Analysis and interpretation. Burlington, Mass: Jones & Bartlett Learning. Winkler, O. W. (2009). Interpreting economic and social data: A foundation of descriptive statistics. Dordrecht: Springer.