Data Analysis Case

1 EXECUTIVE SUMMARY

This report conducts data analysis to inform the Head of AllRepairs on time efficiency and customer satisfaction in the department that provide repair services for farms and businesses. Data from the department was analyzed using excel for inferential and descriptive statistics. Descriptive statistics were analyzed and results identify commendable time efficiency but lower than expected level of customer satisfaction. Test of hypothesis identify significance of job efficiency but this is an external factor. The report recommends the need to improve customers’ utility level and the need for an independent research on factors affecting customers’ satisfaction for appropriate policies towards improving customer satisfaction.

2 INTRODUCTION

Background information

Data analysis plays an important role in informing decisions and in forecasting activities in an enterprise. Its monitoring and evaluation aspects also help in quality assessment for ensuring customers’ utility for retained market control. Such analyses by the Business Analytics Department have the potential to sustain AllRepairs’ market command and profitability and to expand these aspects. As a quality control strategy, there is need to understand how efficiently and effectively staffs perform in terms of speed and subject to their experience. The need to retain customers through good relations also requires an understanding of customers’ utility from offered services and analysis to the effect is necessary. This paper, based on an assignment by the Head of AllRepairs and with emphasis on mechanics’ time efficiencies and customers’ satisfaction, analyzes data from repair of refrigeration units’ department and makes recommendations to the management for sustainability decisions.

Definition of terms

Descriptive statistics: Descriptive statistics are mathematical quantities that summarize features of a data’s distribution and offer a basis for interpreting the data. Examples of descriptive statistics are mean, mode, median, and standard deviation.

Frequency distribution: Frequency distribution is a mathematical function that related levels of a variable and the number of occurrence at each level. It is important in preference determination that relies on density distributions.

Regression analysis: Regression analysis defines application of regression to determine a relationship between two or more variables for forecasting purposes. It relies on developed coefficients to make inferences.

Correlation: Correlation defines interdependence between quantitative variables. It is measured through correlation coefficient that determines the strength and nature of a relationship.

Methods

The report based on a non-experimental study design