Essay Sample on Business Drivers and Analysis of Effectiveness

Introduction

For a business to survive there has to be a proper understanding of the market. Essential inputs and activities that bring about financial gain must be understood and enhanced to help improve the overall business position (Krichene et al., 2017). Ranking the activities and giving more attention to those that yield more profits is an essential step in ensuring sustainability and profits of the operation. In the paper, an analysis of crucial business drivers and their effectiveness is done; more focus is paid to sports genre.

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Types of Correlations

Positive correlation; in positive correlation, there is a direct link between two variables where an increase in one variable causes an increase in the other variable. The decrease in the first variable also causes a decrease in the second variable. For instance, there is a positive correlation between the hours spent practicing and the level of expertise that a player has. If one practice more, the better player they become (Knudson & Lindsey, 2014).

Negative correlation; in negative correlation, there is an inverse relation between two variables, an increase in one variable causes a decrease in the other variable, and vice versa. For instance, an increase in the number of hours worked per day causes a decrease in the number of hours spends resting. The decrease in the number of hours worked increases the time spent resting (Knudson & Lindsey, 2014).

Minimal correlation; A change in variable A causes little or no change in variable B. therefore; there is a minimal correlation between the two. For instance, the number of personal vehicles owned by an individual and the liters of fuel spends per month. There will be little change as the person can only use one vehicle at a time (Knudson & Lindsey, 2014).

Deductions From the Correlations

In the first scenario, the number of indoor basketball leagues and the number of basketball teams in the area has a positive correlation. From the data, it is evident that there are both short term and long term implications for sports equipment sellers. In the short term, they may establish their brand as the best in the market. Focus on building market reputation should be given immediate priority (Bailey et al., 2018). In the long run, they may aim for financing one of the teams or even adding their team to the list of the current teams.

The high number of youths in an area and the lack of indoor sporting facilities have a minimal correlation. The company can focus on outdoor activities and still make sales in the market. On the other hand, the high number of indoor sporting facilities and the extreme warmth in an area has a positive correlation. The seller can focus on indoor sporting items and clothing's since there is a high possibility that more will be built.

The rural geographic setting and the high-income area have a positive correlation. As you move to rural areas, the lesser the income of the people there. On the other hand, urban areas promise more income and thus there is a positive correlation between urban areas and income (Bailey et al., 2018; Krichene et al., 2017). The seller should focus more on urban areas since there is more income and therefore a bigger market.

Implications to Big Data Regarding Their Client's Outdoor Sporting Goods

Big D focuses on selling of outdoor sporting equipment's; in this case, the market that they desire to enter has a higher focus on indoor games. This is evident from the positive correlations and the one instance of minimal correlation between the variables. In this case, Big D will report a low level of sales. There will also be a hard time moving the goods thus a low turnover. Additionally, Big D will not hit the target profit in the target area (Krichene et al., 2017).

Implications of Penetrating the Indoor Sporting Goods

There are both short term and long term implications of the penetration. In the short term, there will be reduced profits, the high cost of operation and customer relation issues. This is because big D client is focused on the outdoor market and thus there has to be an adjustment to meet the local needs. On the other hand, the company will have an expanded market in the long term. As more people get to know about their products, the sales will gradually increase (Schober et al., 2018). Furthermore, the number of returning clients is also likely to go high.

How to Use Correlation Tools to Identify Variables and Help Expand the Business

To identify the variables using correlation, the business can identify the factors that affect its operation in a given location. In this case, the income of the people, the number of basketball teams, the weather and population demographics. From this, identification of how the noted factors relate with others is done. Big D can then identify the factors that have a negative or positive correlation and label them as variables affecting the business operations.

Conclusion

Identification of correlation is essential for Big D as it will culminate in the eventual success of the clients business. Based on the variables identified and the correlation between them, Big D can utilize them to ensure that it can predict future patterns. Furthermore, it is evident that the variables will help measure performance and determine the direction of change, therefore ensure the overall success of big D.

References

Bailey, D. H., Duncan, G. J., Watts, T., Clements, D. H., & Sarama, J. (2018). Risky business: Correlation and causation in longitudinal studies of skill development. American Psychologist, 73(1), 81.

Knudson, D. V., & Lindsey, C. (2014). Type I and Type II errors in correlations of various sample sizes. Comprehensive Psychology, 3, 03-CP.

Krichene, H., Chakraborty, A., Inoue, H., & Fujiwara, Y. (2017). Business cycles' correlation and systemic risk of the Japanese supplier-customer network. PloS one, 12(10), e0186467.

Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients: appropriate use and interpretation. Anesthesia & Analgesia, 126(5), 1763-1768.