Sales And Customer Care: New Assessment Answer

Discuss about the Contemporary issues in Accounting for the year 2016.

Introduction

Penny Geni –U$ is an Inland Revenue Department registered Tax Agent. They mainly serve the citizens of New Zealand and provide services to thousand of clients across New Zealand (Kristoufek, 2014). Penny Geni –U$ Limited was established in 18^th June 2013 and had been operating as a Tax Agent until then. Currently they are running their business for over three years and their business is recorded as NZ Limited Company (Broumi & Smarandache, 2013).

Penny Geni –U$ Limited has various departments in their business. Two such departments out of them are sales department and customer care department (Yu et al., 2012). In this assignment the workforce of Penny Geni –U$ Limited would be explored and their employees in the sales department and call centre department compared in context of various factors. Comparisons would be made between the turnover rate of the employees of these two departments of Penny Geni –U$ Limited and the reasons behind the turnover would be identified (Mukaka, 2012). Various statistical methods would be used for the analysis after collecting the required data. Graphs and charts would be  drawn to support the analysis.

Problem statement

The problem statement is to identify the reason of huge staff turnover in Sales department of Penny Geni –U$ Limited compared to the Customer Care department.

Research aim

The aim of the research is to identify the reason of huge staff turnover in Sales department of Penny Geni –U$ Limited compared to the Customer Care department.

Research objective

The objective of the research is as follows:

• To identify the difference in the turnover in the sales department and customer care department of Penny Geni –U$ Limited
• To identify the relationship between various factors of sales department and customer care department of Penny Geni –U$ Limited
• To identify the reasons behind the differences in the turnover rates of sales department and customer care department of Penny Geni –U$ Limited

Research questions

The research questions are as follows:

• What is the difference in the turnover rates in the sales department and customer care department of Penny Geni –U$ Limited?
• What is the relationship between various factors of sales department and customer care department of Penny Geni –U$ Li
  
  mited?
• What is the reason behind the differences in the turnover rates of sales department and customer care department of Penny Geni –U$ Limited?

Literature review

Penny Geni –U$ Limited is one of the leading Tax agent in New Zealand. They help their customers to pay proper amount of tax to the government of New Zealand and claim the refund for the last five years (Zhang et al., 2013). Taxes paid to the government of New Zealand are revised every year and people have to pay the amount accordingly. Sometimes, the citizens of New Zealand over pay their taxes, which they do not have any count. At the end of the financial, when the tax payers calculate the amount of tax to be paid to the government, they find that the tax they had paid was over the taxable amount (McHugh, 2013). They need to file a refund in that case.

As per the viewpoint of Siedenberg et al. (2013), it was found that filing for refund of tax involves many procedures. The taxpayer had to go through lots of steps that begin with logging into Inland Revenue Department and register on their website. Then the taxpayer has to check on his or her income by clicking on the “Salary and Waged” button. The taxpayer has to calculate his or her return on going to the personal tax summary calculation page (Zhang et al., 2013). After clicking the start button, the taxpayer has to complete his or her details. The last page of the calculation would give an idea about the deficit or excess of the tax payed by the customer.

The idea about the deficit or excess of the payable tax would help the taxpayer to know the amount of tax he or she would get or have to pay to meet his tax for the financial year. In order to pay the tax, the taxpayer needs to go to the “My Overview” page and click for “Request a PTS” (Carrasco et al., 2013). The taxpayer needs to provide all his information and submit it to Inland Revenue Department. It takes about two months for delivering PTS via post. Crosschecking of calculation is required after receiving PTS and if the taxpayer had miscalculated his tax, the taxpayer had to pay the amount by 7^th of February of every month (Dobbin & Ionan, 2015).

As per the viewpoint of Gilmour et al. (2013), it was seen that if there is a refund and it is below $ 200, then the taxpayer does not have to do anything. On providing the bank account number, the Inland Revenue Department would deposit the money in the bank account of the taxpayer. Otherwise, the Inland Revenue Department would send him a cheque via post. Thus, the process of filing of tax and providing information regarding the taxpayer is a lengthy and complicated process (Aron et al., 2013). The taxpayer had to go through tiring process and sometimes they cannot understand the steps of filing of taxes.

Penny Geni –U$ Limited helps the citizens of New Zealand to go through this process. They help the taxpayers to save their time and energy to calculate the tax to be paid or refund required at the end of the financial year. As per the viewpoint of Kohtamäki et al. (2013), it was seen that the taxpayers are working personals who usually remain busy in their work life and personal life. They hardly get any time to invest in filing their taxes. Sometimes, they remain so busy that they could not fill up the forms of tax properly (Zebende et al., 2013). In addition, various things are included in tax paying while there are various things that are excluded from paying of tax. The common people do not know these and they might file their tax incorrectly. This will land them into trouble and they might have to overpay during the payment of the tax.

As per the viewpoint of Zhu et al. (2013), it was seen that there were many situations where the common people had landed into legal trouble due to wrong filling of the forms to file their taxes. The taxpayers had to go through various legal process and they had to face various problems in future. In order to avoid these mishaps, Penny Geni –U$ Limited, a registered Tax agent helps the common people to file their taxes properly and help them not to fall into legal trouble (Shevlyakov & Smirnov, 2016).

Penny Geni –U$ Limited have various departments in their company (Tian et al., 2013). This includes sales departments and customer care departments as well. It was seen that these departments have various roles to play and they help the customers to file their taxes accordingly (Schumacker & Tomek, 2013). It was seen that the staffs of these departments are recently facing various problems and there was high rate of turnover for these two departments (Rawson et al., 2013). The turnover rate was high for sales department than the customer care department. The reason behind this difference in turnover rate is to be indentified and it would be presented in the research.

Methodology

Data collection

Primary data would be collected for this survey. The data would be collected from the records of Penny Geni –U$ Limited of New Zealand. Data would be collected for the last twelve months of the company. Quantitative data would be collected for this purpose and the management of Penny Geni –U$ Limited would provide the required data for the research. Data would be collected for the salary of the employees for the past twelve months for both sales and customer care department of Penny Geni –U$ Limited (Geith et al., 2015). Data would also be collected for facilities provided to both sales and customer care department, working hours of staffs for both sales and customer care department, number of employees leaving the organisation every month for the last twelve years and total number of employees present every month. Penny Geni –U$ Limited would be asked to provide information regarding the reasons of leaving the organisations for the employees of both the departments (Ye, 2013).

Data analysis

The primary data collected from the management of the company was analysed using correlation and chi square tests.

Correlations
		Reasons_of_leaving_in_sales	Salary_for_employees_in_sales	working_hours_in_sales	Facilities_in_sales	experience_of_the_employees_in_sales
Pearson Correlation	Reasons_of_leaving_in_sales	1.000	.384	.093	.329	-.271
	Salary_for_employees_in_sales	.384	1.000	.284	-.433	-.053
	working_hours_in_sales	.093	.284	1.000	-.278	.566
	Facilities_in_sales	.329	-.433	-.278	1.000	-.138
	experience_of_the_employees_in_sales	-.271	-.053	.566	-.138	1.000
Sig. (1-tailed)	Reasons_of_leaving_in_sales	.	.109	.387	.148	.197
	Salary_for_employees_in_sales	.109	.	.186	.080	.436
	working_hours_in_sales	.387	.186	.	.191	.028
	Facilities_in_sales	.148	.080	.191	.	.334
	experience_of_the_employees_in_sales	.197	.436	.028	.334	.
N	Reasons_of_leaving_in_sales	12	12	12	12	12
	Salary_for_employees_in_sales	12	12	12	12	12
	working_hours_in_sales	12	12	12	12	12
	Facilities_in_sales	12	12	12	12	12
	experience_of_the_employees_in_sales	12	12	12	12	12

Table 1: Correlation between the variables of sales

(Source: created by author)

From the table it was seen that there was negative correlation coefficient between facilities provided to the employees to the experience of the employees of sales. It can be interpreted that people with higher experience did not get their deserved facilities, which might have resulted, into resigning their job. It was also seen that with the increase in the working hours of the employees, the facilities provided to the staffs of sales also decreases. It was seen that with the increase in salaries of the employees, the facilities provided to the employees also decreases. These decrease the employees’ satisfaction, as they were not treated properly for the jobs and performances they were doing. The employees of sales department were highly dissatisfied with the way their company was treating them. This had lead to resignation of the employees of the sales department.

Correlations
		Reasons_of_leaving_in_customer_care	Salary_for_employees_in_customer_care	Working_hours_in_customer_care	Facilities_in_customer_care	Experience_of_the_employees_in_customer_care
Pearson Correlation	Reasons_of_leaving_in_customer_care	1.000	-.489	-.411	-.123	-.255
	Salary_for_employees_in_customer_care	-.489	1.000	-.115	-.144	-.173
	Working_hours_in_customer_care	-.411	-.115	1.000	.135	.233
	Facilities_in_customer_care	-.123	-.144	.135	1.000	.314
	Experience_of_the_employees_in_customer_care	-.255	-.173	.233	.314	1.000
Sig. (1-tailed)	Reasons_of_leaving_in_customer_care	.	.053	.092	.352	.212
	Salary_for_employees_in_customer_care	.053	.	.361	.328	.296
	Working_hours_in_customer_care	.092	.361	.	.338	.233
	Facilities_in_customer_care	.352	.328	.338	.	.160
	Experience_of_the_employees_in_customer_care	.212	.296	.233	.160	.
N	Reasons_of_leaving_in_customer_care	12	12	12	12	12
	Salary_for_employees_in_customer_care	12	12	12	12	12
	Working_hours_in_customer_care	12	12	12	12	12
	Facilities_in_customer_care	12	12	12	12	12
	Experience_of_the_employees_in_customer_care	12	12	12	12	12

Table 2: correlation coefficient of the variables of customer care

(Source: created by author)

From the table it could be seen that with the increase in salary of the employees, the facilities provided to the employees of customer care department had decreased over the time. It was also seen that with the increase in experience of the employees, the salary used to decrease. In addition, it was seen that the resignation of the employees decreased with the increase in facilities given to the employees of customer care and vice versa.

However, it was seen from the correlation coefficient that the employee satisfaction of the employees of customer care was higher than the employees’ satisfaction of the sales department. It was seen that the facilities given to the employees of sales department was less than the employees of the customer care department were. The correlation coefficient of the facilities provided to the employees of sales department was negative with all the other variables. Considering the employees of the customer care department, it was seen that the correlation coefficient of the facilities provided to the employees with the other variables were less negative than that of the sales department. Thus, it could be concluded that the employees of sales department were had higher rate of dissatisfaction than the employees of customer care department. This is the reason that the employees of sales department resigned from their jobs more than the employees of the customer care department are.          

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	5.220a	6	.516
Likelihood Ratio	6.994	6	.321
Linear-by-Linear Association	.808	1	.369
N of Valid Cases	12
a. 12 cells (100.0%) have expected count less than 5. The minimum expected count is .25.

Table 3: table of chi square between reasons of leaving in sales and experience of the employees in sales

(Source: created by author)

It was seen that the significant value of the test was 0.516. This can be interpreted that there was relationship between the two variables and with the increase in experience of the employees, the turnover of the employees had increased.

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	90.000a	81	.231
Likelihood Ratio	48.547	81	.998
Linear-by-Linear Association	.008	1	.928
N of Valid Cases	12
a. 100 cells (100.0%) have expected count less than 5. The minimum expected count is .08.

Table 4: chi square test between number of employees in sales and salary of the people in sales

(Source: created by author)

From the table it can be seen that the p value of the chi square test is 0.231. It can be interpreted that there was relationship between the number of employees in sales and salary of the people in sales. Decrease in the salary of the employees would result in resignation of the employees of this department.

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	30.000a	27	.314
Likelihood Ratio	28.634	27	.379
Linear-by-Linear Association	2.439	1	.118
N of Valid Cases	12
a. 40 cells (100.0%) have expected count less than 5. The minimum expected count is .17.

Table 5: chi square test of number of employees in sales and working hours in sales

(Source: created by author)

The table shows that the significant value of the test is 0.314. It can be interpreted that the relationship between number of employees in sales and working hours in sales department exists. It can be said that the increase in working hours would result to increase in resignation of the employees. This is because no employees likes to over work and extend their working hours.

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	18.600a	18	.417
Likelihood Ratio	20.316	18	.315
Linear-by-Linear Association	2.321	1	.128
N of Valid Cases	12
a. 30 cells (100.0%) have expected count less than 5. The minimum expected count is .25.

Table 6: Chi square test between number of people in sales and facilities in sales

(Source: created by author)

The significant value of the test is 0.417, which shows that there exists a relationship between these two variables. The change in one variable would affect the other variable. Thus, the decrease in facilities to the employees of the sales department results to increase in the resignation of the employees.

Conclusion

It can be concluded that there was difference between the salaries of the employees of sales department of Penny Geni –U$ Limited and the employees of customer care department of Penny Geni –U$ Limited. The satisfaction level of the employees would be less for the employees of sales department than the employees of customer care department. This is due to the more number of negative correlations between the variables of sales department than the variables of customer care department. This had resulted to increase in number of resignations for the employees of sales department than the employees of customer care department of Penny Geni –U$ Limited.

Recommendation

It is recommended that the company, Penny Geni –U$ Limited, must provide the same opportunities to the employees of sales department as they provide to the employees of customer care department. The company must reduce the working hours of their employees and provide them with better facilities. The company must also increase the salary of the employees of sales department and they must look carefully into the employees’ satisfaction level of the sales department. The company must treat the employees of sales department and customer care department equally, which would result in less resignation of the employees of sales department.

References

Aron, A., Coups, E., & Aron, E. N. (2013). Statistics for The Behavioral and Social Sciences: Pearson New International Edition: A Brief Course. Pearson Higher Ed.

Broumi, S., & Smarandache, F. (2013). Correlation coefficient of interval neutrosophic set. In Applied Mechanics and Materials (Vol. 436, pp. 511-517). Trans Tech Publications.

Carrasco, J. L., Phillips, B. R., Puig-Martinez, J., King, T. S., & Chinchilli, V. M. (2013). Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Computer Methods and Programs in Biomedicine, 109(3), 293-304.

Dobbin, K. K., & Ionan, A. C. (2015). Sample size methods for constructing confidence intervals for the intra-class correlation coefficient. Computational Statistics & Data Analysis, 85, 67-83.

Geith, T., Biffar, A., Schmidt, G., Sourbron, S., Dietrich, O., Reiser, M., & Baur-Melnyk, A. (2015). Physiological Background of Differences in Quantitative Diffusion-Weighted Magnetic Resonance Imaging Between Acute Malignant and Benign Vertebral Body Fractures: Correlation of Apparent Diffusion Coefficient With Quantitative Perfusion Magnetic Resonance Imaging Using the 2-Compartment Exchange Model. Journal of Computer Assisted Tomography, 39(5), 643-648.

Gilmour, P., Borg, G., Duffy, P. A., Johnston, N. D., Limbek, B. E., & Shaw, M. R. (2013). Customer service: differentiating by market segment.International Journal of Physical Distribution & Materials Management.

Kohtamäki, M., Partanen, J., Parida, V., & Wincent, J. (2013). Non-linear relationship between industrial service offering and sales growth: The moderating role of network capabilities. Industrial Marketing Management,42(8), 1374-1385.

Kristoufek, L. (2014). Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series.Physica A: Statistical Mechanics and its Applications, 406, 169-175.

McHugh, M. L. (2013). The chi-square test of independence. Biochemia Medica, 23(2), 143-149.

Mukaka, M. M. (2012). A guide to appropriate use of Correlation coefficient in medical research. Malawi Medical Journal, 24(3), 69-71.

Rawson, A., Duncan, E., & Jones, C. (2013). The truth about customer experience. Harvard Business Review, 91(9), 90-98.

Schumacker, R., & Tomek, S. (2013). Chi-square test. In Understanding Statistics Using R (pp. 169-175). Springer New York.

Shevlyakov, G., & Smirnov, P. (2016). Robust estimation of the correlation coefficient: an attempt of survey. Austrian Journal of Statistics, 40(1&2), 147-156.

Siedenberg, R., Goodin, D. S., Aminoff, M. J., & Rowley, H. A. (2013, November). Localizing Dipoles: The Correlation Coefficient and the Goodness. In Biomag 96: Volume 1/Volume 2 Proceedings of the Tenth International Conference on Biomagnetism (p. 342). Springer Science & Business Media.

Tian, J., Yu, D., Yu, B., & Ma, S. (2013). A fuzzy TOPSIS model via chi-square test for information source selection. Knowledge-Based Systems, 37, 515-527.

Ye, J. (2013). Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. International Journal of General Systems, 42(4), 386-394.

Yu, S., Zhou, W., Jia, W., Guo, S., Xiang, Y., & Tang, F. (2012). Discriminating DDoS attacks from flash crowds using flow correlation coefficient. IEEE Transactions on Parallel and Distributed Systems, 23(6), 1073-1080.

Zebende, G. F., Da Silva, M. F., & Machado Filho, A. (2013). DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches.Physica A: Statistical Mechanics and its Applications, 392(8), 1756-1761.

Zhang, S., Glazunov, A. A., Ying, Z., & He, S. (2013). Reduction of the envelope correlation coefficient with improved total efficiency for mobile LTE MIMO antenna arrays: mutual scattering mode. IEEE transactions on antennas and propagation, 61(6), 3280-3291.

Zhu, Z., Nakata, C., Sivakumar, K., & Grewal, D. (2013). Fix it or leave it? Customer recovery from self-service technology failures. Journal of Retailing, 89(1), 15-29.