QSCA Management Analysis

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QSCA Management Analysis

Introduction

The problem of holding debt has been increasing since the last decade where people usually make their dues higher and higher and then do not pay them back. This is where the problem starts for the agencies where they should plan on how to recover those debts from the customers. One of the agencies who are involved in collecting such debts is QSCA (Sherri, 2011).

The purpose of QSCA is to provide services for the collection of due bills from the debtors. The data is collected from the main source and then decide a plan of colleting those debts from the people. It is specialized in very profitable small accounts and moreover they avoid risky collections. The Profitability in QSCA depends upon the number of days been taken to collect back the payment and also on quick recovery, discount rates are offered. The predictive analysis helps QSCA to optimize the allocation of collection resources by adopting the most legal and effective collection strategies that certainly reduce their costs (Sherri, 2011). A random sample of 96 customers has been taken in which their data of dues and the number of days they take to collect that money from the defaulters has been recorded. The customers are also categorized as residential or commercial customers. The discounts are so high that a debt of $50 may be purchased for even $10. The criterion for the company to be successful is that they collect the greatest amount of payments in a shortest possible time.

A statistical analysis is planned to be applied on the data to find out if there exist any relationship or correlation between the number of days agency takes in recovering the due and the amount of due on any customer. The descriptive statistics plays an important role in finding the mean number of days and average bill due on each customer and standard deviations can optimize the result range as well. A regression analysis will also be applied to find out the trend of the customers in returning the dues in any particular amount of time (Lyman, 2010).

Data Analysis for QSCA

The data for the assignment has been retrieved from the e-book which contains the number of days that QSCA takes to recover dues from a customer and different amount bills due on the customer. The descriptive statistics is now being used to analyze the average bills and days required to recover the dues (Lyman, 2010).

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Variance

DAYS

96

5

99

49.78

23.619

557.857

BILL

96

46

311

174.27

77.824

6.057E3

Valid N (list wise)

96

The results showing that almost an average of 50 days are required to recover dues from one customer and average overbill dues per person is $174.27. The data being normally distributed showing that 68.5% of the data lies between 50±24 days i.e. most of the recoveries take 26 to 74 days. Similarly, 68.5% of the bill's data lies between $174.27±77.824 i.e. most of the bills are in the range of $96.446 to $252.094. The average 50 days are quite acceptable for QSCA to recover ...