Business essay

Business essay
Introduction

The importance of statistics for business purposes can hardly be overestimated. First of all, the statistical measurements are used to present data in standardized and meaningful format (Cowan, 1998). Secondly, statistical data may be used to study the state of affairs in a certain area, forecast future results and improve existing tendencies in business. In human resource management, statistical values may give the clues to employees’ performance, motivation and indicate the fulfillment of organization’s goals and mission. One of important issues for statistical analysis is job satisfaction; this factor is related with many key figures such as workplace productivity, motivation, number of sick days per worker and overall company’s efficiency (Glenberg, 1996). For the American Intellectual Union studying job satisfaction and factors influencing it will allow to implement positive changes in workforce dynamics and develop a strategy for increasing job satisfaction among certain groups of employees.

In order to receive data for statistical analysis, surveys are generally used. The aim of this paper is to present the results of statistical analysis of a survey containing answers by 25 respondents related to their job satisfaction. The purpose of this analysis is to identify current tendencies and probabilities concerning workforce and job motivation within the American Intellectual Union, and provide recommendations basing on this analysis.

Description of methods

For analyzing the dataset, standard procedures of using central tendency measures were used; the mean was selected as the measure of central tendency for quantitative variables, and the mode was used as the measure of central tendency for qualitative variables. Also, probabilities (in other words, forecasts for a randomly selected employee (Cooper & Weekes, 1983)) were made for the whole employee population, basing on the assumption that dataset is unbiased and is presenting a statistically valid result for the whole population (Cowan, 1998). Probabilities were counted as the number of occurrences of a given event divided by the total number of trials in this sample (N=25), and expressed as percentage.

Analysis of data by 1 and 2 categories was performed using conditional functions built into Microsoft Excel software, and via applying proper filters to the dataset. Mean value of extrinsic job satisfaction for each gender was obtained by separating the whole dataset by gender characteristic and calculating the sum of extrinsic job motivation for each gender separately (and then dividing it by total number of respondents N=25). Correlation analysis means of MS Excel were used to determine correlation between quantitative variables.

Results

The main relationships studied in this analysis were: the distribution of individuals by gender and departments; the distribution of overall tenure with company by gender characteristic and mean values of extrinsic job motivation (also separate for each gender). Table 1 presents the results of analysis expressed in numeric and percentage forms; the latter figures also represent a probability that an individual randomly selected from the same population would have the described characteristics (Cooper & Weekes, 1983).

Also, several possibilities for a randomly selected workforce individual were calculated which reflect the major trends in the dataset: the probability that this individual will fall into the age category between 16 and 21 years old, the probability that this individual’s job satisfaction will be 5.2 and lower, the probability that this person is a female working in HR, and the probability that this employee is the salaried one with intrinsic job satisfaction value 5 or more.

Business essay

Business essay

Interpretation of results

Concerning the overall population, it is possible to notice such tendencies:

- Women are prevalent in the organization (56% of women against 44% of men, i.e. the difference by 12% is witnessed)
- Men are more likely to stay longer within the company (percentage of tenure between 2 and 5 years, and tenure more than 5 years for men is higher, in gender comparison)
- There are many women who are newcomers (almost twice, in percentage, compared to men, in category “tenure less than 2 years”)
- The vast majority of survey respondents work in the IT department, and the AD department is the smallest in the company (64% of respondents from IT department compared to 8% of respondents from AD department)
- For women, extrinsic job motivation estimate showed to be a little higher than for men; however, this difference was not significant
It should be indicated that this survey may contain sampling errors concerning the distribution of employees between departments, since 64% of respondents relate to IT department. In order to check the reliability of the results of the survey and its objectiveness, it is recommended to compare the overall number of employees in the departments, and the results of the survey.

It is notable that correlation analysis has shown the negative correlation value of -0.71 between estimate of benefits and extrinsic motivation. This may be the indicator either of wrong choice of benefits for motivating workforce, or of significant difference of opinions between those respondents who have high extrinsic motivation ad those who value benefits highly.

Conclusion

Statistical analysis allows to make conclusions about this current state of affairs, prepare forecasts and identify tendencies which might be used as basis for developing business strategies. This statement is true for any business area, and in the case of considered dataset it can be applied to studying and increasing job motivation.

For the American Intellectual Union analysis of workforce has shown prevalence of women over men, and employees of IT department over other departments. Also, it was witnessed that there are many women with tenure less than 2 years. Together with the larger number of women, this may be the indicator of high employee turnover, which may take place due to gender issues. This factor should be carefully analyzed, and appropriate strategy has to be developed.
Also, the significant by module but negative correlation value between estimate of benefits and extrinsic motivation appeared to be an unexpected result; more attention should be paid to increasing extrinsic motivation, and the system of benefits has to be reconsidered in order to add to extrinsic motivation, but not to decrease it.

Thus, results of the analysis might be used to develop a strategy for improving the efficiency of working, ensuring higher job satisfaction and overall business efficiency of the American Intellectual Union.

References

Cowan, Glen. (1998). Statistical data analysis. Oxford University Press.
Cooper, Ron A. & Weekes, Tony J. (1983). Data, models, and statistical analysis. Rowman & Littlefield.
Glenberg, Arthur M. (1996). Learning from data: an introduction to statistical reasoning. Routledge

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