GSBS6002: Foundations of Business Analysis Case Study Assessment

Business Analysis Case Study

Case Scenario/ Task

1. Does the current level of customer satisfaction differ from management’s goal of 7 out of 10?

2. Is there any difference between the satisfaction of male and female customers with the level of communication with staff and management at Computers R Us?

3. Are there any differences in the overall customer satisfaction across the following age groups: 1, 2, 3, 4 and 5?

4. Is there any difference in customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’?

5. Do any of the initiatives of ‘decreasing response times in the CompleteCare division’, ‘the level of advice CompleteCare staff provide on Computers R Us products and services’, ‘the level of communication with staff and management’ and ‘new loyalty rewards program’ influence the overall satisfaction of Computers R Us customers?

Computers R Us which is a manufacturer and retailer dealing with computers is facing certain issues that need to be addressed immediately to control the situation. The organization is facing problems with respect to customer satisfaction. A research analysis is executed to identify the present level of client contentment and what are the factors that can contribute effectively in improving it. Different statistical tests such as t-test, Anova, correlation and regression analysis is done to complete the objectives of this problem. The findings suggest that the organization lacks in meeting the standard objective of customer satisfaction (7) and therefore, it should take immediate steps to cover the gap. For this, a regression analysis is done which suggests that the overall satisfaction can be improved by improving Response Time Satisfaction, Advice Satisfaction and Communication Satisfaction. Out of these three attributes, Response Time Satisfaction contributes the most followed by Advice Satisfaction and Communication Satisfaction. The findings suggest that with each unit increase in Loyality Reward Satisfied, the Overall Satisfaction decreases with .1239 units. Therefore the company should focus on reducing the response time to as minimum as possible.

Introduction

Computers R Us which is a manufacturer as well as retailer of computers has lately started a service & repair department, Complete Care, to deal with its laptop and notebook systems. The aim of their newly launched service is to offer a fast reply to client’s technical queries & service contract issues. However, the company is facing some issues with respect to shortage of resources. And as a result, many complaints from the customers are being recorded and are continuously increasing. To solve this issue in an effective manner, the organization decided to conduct a thorough analysis of the problem. A survey form is developed covering all the issues and recommendations that can help the organization to improve. A random sample of 500 users is selected to provide their feedback and responses. The data is collected in an excel format and then different statistical tests such as Independent t-test, correlation and regression are executed on the dataset. These tests are explained in more detail in the later section of this report. The objective of this analysis is to improve the customer satisfaction. The analysis will help in identifying the present level of the client satisfaction & how it can be improved. The respondents are also asked to rate the recommendations they would like to experience from the organization and these set of recommendation will help in improving the customer satisfaction and hence the objective of the research work will be achieved.

An effective communication and timely response of the user’s query is very important to provide a high level of customer satisfaction. The suggestions given by the staff members to the users in response to their queries also act as a good point to ponder for improving the customer satisfaction. All these points are covered in the analysis section of this report.

Research Design

An online survey method is used for data collection for this research work. As the online survey is used for this study, the links have been shared through social media. The respondents are requested to provide their honest opinion as they were not asked to provide any of their personal information including their name, email-id, address in the questionnaire. Their responses were captured anonymously without revealing their identity. An online survey form was created and shared with the participants for this research purpose. Over the previous decade, the utilization of online techniques for statistical surveying has soared. Due to continually expanding innovative developments, it has become easy to perform the research analysis without needed much help from outside, direct & investigate the studies and that too utilizing lesser expenses and reduced timelines. Because of lower overhead, gathering information does not cost a huge number of dollars (Konstantinos E. Farsalinos, 2014).

Respondents enter the data on their own, & it is consequently get through electronically. Such Analysis is simple and can be easily rationalized. The online surveys are accessible quickly without using any efforts. The quick sending and getting back the responses is conceivable through online overviews that can't be possible through conventional techniques. The respondents provide the answers at their own time, comfortability, and speed. They can even start it responding, then pause it for some time and again continue it later. All this flexibility is provided by the online surveys. Respondents might be all excited and honest to provide their responses as they know that nobody will get to know who provided this information (Wright, 2006).

A simple random sampling is used for this analysis purpose (Lones Smith, 2013). A sample space of 500 users is chosen. Out of these 500 users, only 420 users responded successfully.

Analysis

Different statistical tests such as t-test, Anova, correlation and regression analysis is done to complete the objectives of this problem. The tests are conducted through the help of excel data analysis pack. The data for these tests is collected through the responses generated through online survey. The responses are collected in the Microsoft excel. A random sampling is used for selecting the population for this analysis so that any chances of biasness can be reduced. The findings suggest that the organization lacks in meeting the standard objective of customer satisfaction (7) and obtained only the value 5.89. Therefore, it should take immediate steps to cover the gap.

For this, a regression analysis is done which suggests that the overall satisfaction can be improved by improving Response Time Satisfaction, Advice Satisfaction and Communication Satisfaction. Out of these three attributes, Response Time Satisfaction contributes the most followed by Advice Satisfaction and Communication Satisfaction. The findings suggest that with each unit increase in Loyality Reward Satisfied, the Overall Satisfaction decreases with .1239 units. Therefore the company should focus on reducing the response time to as minimum as possible.

Conclusion

Statistical tests are very important to identify a problem, understand the root cause of a given problem, and identifying factors that can help in resolving the problem. The issues encountered by Computers R Us are diagnosed with the help of statistical tests such as independent t –test, two sample t-tets, Anova, correlation and regression analysis. This analysis concludes that Computers R Us lacks in meeting the standard objective of customer satisfaction (7) and obtained only the value 5.89. Therefore, it should take immediate steps to cover the gap. Also the analysis helped in identifying the most contributing factor to achieve the objective of improving customer satisfaction. The findings conclude that reducing the response time will help in improving the customer satisfaction. A set of recommendations is proposed in the following section of this report. These recommendations will help in overall improvement in the customer satisfaction of Computers R Us.

Recommendations

The response time contributes the most in improving the overall satisfaction.

The response time can be further reduced by implementing high technology while dealing with the customers. Alarms can be triggered whenever the user posts a query. The query should be automatically assigned to the concerned employee who can provide the appropriate solution. An auto response to the users that their problem is acknowledged and assigned to the concerned person should be sent. Also, the time taken to resolve the issue should be intimated.

The other factors are Advice Satisfaction and Communication Satisfaction. This can be improved by providing the necessary training to the staff so that they known all the technical workarounds and solution of the common problems. Also, a soft skills training should be provided to the employees so that they can understand how to effectively deal with the users and how to manage the different problems at work.

Appendix

What is the present level of customer satisfaction? Does it vary from 7 that is the management’s?

Appendix 1: Average customer satisfaction

H0: The average customer satisfaction does not differ from management’s goal of 7.

HA: The average customer satisfaction differs from management’s goal and is not equal to 7.

A one-sample t-test is used for this analysis. This test is the suitable one when one needs to compare the difference of one variable space with the pre-determined mean (Zikmund, Babin, Carr, & Griffin, 2012, p. 520). This criterion meets with the problem given in this analysis. The output of this one-sample t-test is as shown below:

Table 1: One-sample t-test for difference in customer satisfaction

From Table 1, it is evident that we can reject that null hypothesis that the average customer satisfaction complies with management’s goal of 7 (p-value 4.82617E-36). As the average customer satisfaction is less than 7 (5.89). The organization needs to improve its customer satisfaction to reach to its expected value of 7. The p value is less than .05 and hence it shows that there is a statistically significant difference in the actual average from the expected average customer satisfaction.

Does the satisfaction of customers vary with the gender with respect to the communication level of staff and management?

Appendix 2: Satisfaction of male and female customers with the level of communication with staff and management

H0: There is no difference between the satisfaction of male and female customers with the level of communication with staff and management.

HA: There is difference between the satisfaction of male and female customers with the level of communication with staff and management.

A Two-sample t-test is used for this analysis. This test is the appropriate one when one needs to compare the difference between the two independent groups (Winter, 2013). In this scenario, these two groups are ratings from males and females. The scenario requirements are completely met by the two sample t test. The output of this two-sample t-test is as shown below:

Table 2: Two-sample t-test for difference in customer satisfaction

A two-tail test is executed for this analysis. Here the value of t Stat (7.602980515)> t Critical two-tail (1.965738512), we reject the null hypothesis. Therefore the observed difference between the sample means (7.131147541 and 5.624472574) is persuasive sufficient to say that the satisfaction of male and female customers with the level of communication with staff and management.

Does the overall satisfaction very with the age groups?

Appendix 3: overall customer satisfaction across the following age groups: 1, 2, 3, 4 and 5

H0: There is no difference between the overall customer satisfactions across the following age groups: 1, 2, 3, 4 and 5

HA: There is difference between the overall customer satisfaction across the following age groups: 1, 2, 3, 4 and 5.

A single factor Anova analysis is used for this analysis. This test is the appropriate one when one needs to compare the difference between the different independent groups (Winter, 2013).

In this scenario, these different populations is the age groups 1, 2, 3, 4,& 5. The scenario requirements are completely met by the single factor Anova analysis. The output of this A single factor Anova analysis is as shown below:

Table 3: Single factor Anova analysis for difference in customer satisfaction

In this table, we will check for the values of F and F crit. if F > F crit, we reject the null hypothesis. But, this is not the case that means 1.866531434 < 2.393438223. Hence, we cannot reject the null hypothesis. Or in other words we can say that the means of the three populations are all equal. There is no difference between the overall customer satisfactions across the following age groups: 1, 2, 3, 4 and 5.

Is there any difference in customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’?

Appendix 4: customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’

H0: There is no difference between the customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’.

HA: There is difference between the customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’.

A correlation is used for this analysis. This test is the appropriate one when one needs to see if there is any relationship between the two variables. In this scenario we need to compare if there is difference between the customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’. The output of the correlation analysis is as shown below:

Table 4: Correlation in customer satisfaction considering Response Time and Loyality reward

Table 5: Correlation in customer satisfaction considering Response Time and Loyality reward and Overall Satisfied

The table 4 shows that there is a negative correlation between the customer satisfaction among responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’. The value of the correlation is -0.74228444 which indicates a high negative correlation. The value of this correlation coefficient lies between -1 and 1.

Therefore, it can be said that there is difference between the customer satisfaction between responses to the initiatives of ‘decreasing response times in the CompleteCare division’ and ‘the loyalty rewards program at Computers R Us’.

The same correlation test was executed considering the third variable “Overall Satisfaction”, as shown in Table 5. The output shows that there is a positive correlation between “Overall Satisfaction” and “Reduced Response Time”.

Do any of the initiatives of ‘decreasing response times in the CompleteCare division’, ‘the level of advice CompleteCare staff provide on Computers R Us products and services’, ‘the level of communication with staff and management’ and ‘new loyalty rewards program’ influence the overall satisfaction of Computers R Us customers?

Appendix 5: Impact of ‘decreasing response times in the CompleteCare division’, ‘the

level of advice CompleteCare staff provide on Computers R Us products and services’, ‘the level of communication with staff and management’ and ‘new loyalty rewards program’ on the overall satisfaction of Computers R Us customers.

H0: There is no Impact of ‘decreasing response times in the CompleteCare division’, ‘the

level of advice CompleteCare staff provide on Computers R Us products and services’, ‘the level of communication with staff and management’ and ‘new loyalty rewards program’ on the overall satisfaction of Computers R Us customers.

HA: There is an effect of ‘decreasing response times in the CompleteCare division’, ‘the

level of advice CompleteCare staff provide on Computers R Us products and services’, ‘the level of communication with staff and management’ and ‘new loyalty rewards program’ on the overall satisfaction of Computers R Us customers.

A regression analysis is used for this purpose. This test is the appropriate one when one needs to find the impact of variables on a variable. The scenario requirements are completely met by the regression analysis. The output of this two-sample t-test is as shown below:

Table 6: Regression Analysis for difference in customer satisfaction

The value of R Square is 0.66 which is a good fit but not very good. If the value is close to 1 then it indicates a better fit of the data. The significance value (1.03881E-95) is less than .05. The regression equation becomes:

Overall Satisfaction= 3.245667568 + 0.282964112 (Response Time Satisfied) + 0.11585157 (Advice Satisfied) + 0.111640816 (Communication Satisfied) + (-0.12399199) (Loyality Reward Satisfied).

For each unit increase in Loyality Reward Satisfied, Overall Satisfaction decreases with .1239units. For each unit increase in Response Time Satisfaction, Overall Satisfaction increases with .2829 units. For each unit increase in Advice Satisfaction, Overall Satisfaction increases with .1158 units. For each unit increase in Communication Satisfaction, Overall Satisfaction increases with .1116 units.