University Supply Chain Analytics: Customer Complaint Analysis Report

This report analyzes customer complaints received by an electronic supply company. The analysis, based on data from the company's ERP system, examines 719 complaints, categorizing them by type (delivery, wrong quantity, etc.) and product family. The study found that delivery issues were the most frequent complaint and that complaints originated from various product families, with "PF12" having the highest number. A chi-square test revealed no significant association between complaint type and product family. The report identifies human error, faulty equipment, and inadequate warehouse supervision as primary problems. The report suggests staff training, updated equipment, and improved customer service to address these issues and improve customer satisfaction. References to relevant literature are included to support the analysis.

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Student Number…..
Supply Chain Analytics
Value chain engineering system
Name
University
26th August 2017
August 26, 2017

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Supply Chain Analytics
Table of Contents
Executive summary.........................................................................................................................2
Introduction......................................................................................................................................2
Data analysis....................................................................................................................................3
i) Complaint types....................................................................................................................3
ii) Product family......................................................................................................................4
iii) Association between complaint type and product family.....................................................5
Problem definition...........................................................................................................................7
Solutions and suggestions................................................................................................................7
References........................................................................................................................................8
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Supply Chain Analytics
Executive summary
This paper sought to understand the complaint types raised by the customers of an electronic
supplying company. A total of 719 complaints were scrutinized where majority of complaints
identified were to do with delivery. Most of these complaints came from a product family
“PF12”. Results showed that there is no significant association between product family and the
complaint type. Many of the complaints were however identified to be as a result of human error
while others might have arose due to failed machines and equipment.
Introduction
Recently an electronic company has been receiving numerous customer complaints which make
sales and customer service representative (CSR) department sick of hearing angry customers’
voice. The marketing/sales manager requested for analysis of the customer complaints data to
find out problems and come up with solutions.
In this paper therefore we attempt to discuss customer complaints, product family, and types of
customers. In business arena, customers are regarded as the “Kings” and “Queens” who deserve
to be listened to. The handling of customer complaints is therefore a critical component aimed at
providing superior customer performance. According to Albrecht (1995), there are three key
aspects of handling customer complaints. The aspects are; acknowledging customer complaints,
identifying customer complaints, and handling customer complaints.
Data analysis
The data in the spreadsheet is pulled out from Enterprise Resource Planning (ERP) system of the
company which is active in the electronic industry. The ERP systems takes note of the date when
the complaint was initiated, date when the response was received, name of the customer, type of
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Supply Chain Analytics
the complaint, family in which the product under complaint belongs to among other variables. A
total of 719 complaints were received and this makes the basis of the analysis for this report.
For efficient analysis and internalization, the data is broken down into various variable-specifics
as below:
i) Complaint types
Table 1 below gives the total complaint types. As can be seen, majority of complaints
(n = 233, 32.4%) reported by customers was related to delivery followed by wrong
quantity (n = 136, 18.9%). The least type of complaints recorded was other
(unspecified) type of complaints (n =3, 0.4%)
Table 1: Total complaint types
Row Labels Count of Complaint Type
Delivery 233
Wrong Quantity 136
Lost In Transit 127
Wrong Product 118
Packaging 36
Poor Response 33
Damaged 18
Quality of workmanship 8
Invoice Error 7
Other 3
(blank)
Grand Total 719
The chart below illustrates the above information.
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Supply Chain Analytics
Delivery
Wrong Quantity
Lost In Transit
Wrong Product
Packaging
Poor Response
Damaged
Quality of workmanship
Invoice Error
Other
(blank)
0
50
100
150
200
250
233
136 127 118
36 33 18 8 7 3
Total complaint types
ii) Product family
Next, we looked at the frequency distribution of the various product families. The complaints
received were found to come from 15 different product families. Majority of the complaints (n =
60, 8.34%) belonged to the product family “PF12”. The product family “PF6” had the lowest
number of complaints recorded (n = 41, 5.70%).
Row Labels Count of Product Family Percent
PF12 60 8.34%
PF10 55 7.65%
PF2 54 7.51%
PF8 49 6.82%
PF14 48 6.68%
PF3 48 6.68%
PF7 48 6.68%
PF1 47 6.54%
PF15 47 6.54%
PF4 47 6.54%
PF11 46 6.40%
PF5 44 6.12%
PF9 43 5.98%
PF13 42 5.84%
PF6 41 5.70%
Grand Total 719 100.00%
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Supply Chain Analytics
The chart below illustrates the above information.
0
10
20
30
40
50
60
70
60 55 54 49 48 48 48 47 47 47 46 44 43 42 41
Total Customer Complaints Raised by Product Family
iii) Association between complaint type and product family
We also conducted an association test to verify whether there is significant association between
type of complaint and product family. The following hypothesis was tested;
H0: There is no significant association between type of complaint and product family
H1: There is significant association between type of complaint and product family
Tested at 5% level of significance
Chi-Square Tests
Value df Asymp. Sig. (2-
sided)
Pearson Chi-Square 142.012a 126 .156
Likelihood Ratio 144.794 126 .121
N of Valid Cases 719
a. 90 cells (60.0%) have expected count less than 5. The minimum
expected count is .17.
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Supply Chain Analytics
A chi-square test of independence was performed to examine the relation between type of
complaint and product family. The relation between these variables was insignificant,
χ2 ( 126 ,729 )=142.01 , p>0.05 .
Problem definition
The major problem as can be seen is the process of packaging till the products gets to the
product. This was established to be the major root cause of the various issues experienced by the
customers. The company’s organizations structure could also possibly affect the customer
satisfaction levels. It seems there are few employees who have a lot of tasks put on them to
accomplish. This affects the workmanship thereby resulting to some of the issues experienced-
the few workers available are highly overworked to the extent that they get confused. In terms of
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Supply Chain Analytics
the warehouse supervision, there are only two supervisors manning the warehouse and they are
both in charge of the inbound and outbound supervisory work going on.
The equipment and machinery used in the warehouse seems to be faulty thus brining issues such
as wrong quantity packed as well as wrong product (Radovilsky & Hegde, 2011).
Response received also contributed as being one of the major complaints raised. This shows
either the staff deliberately fail to acknowledge the customer complaint or they don’t give a clear
direction on how to handle the customer’s issue.
Solutions and suggestions
Most of the complaints raised by the customers are to do with human aspect (human errors). It is
therefore imperative that all the staff in the warehouse to undergo serious training so that the can
fully understand their roles and how to go about their duties in a more effective and efficient
way. All customer service personnel should also be trained on how to handle various customer
complaints effectively and being empowered to respond in a positive manner.
The company should also ensure that the machines and equipment in the warehouse are up-to-
date and in condition. One problem noted was failure by machines to package right quantities,
this can be minimized by doing away any faulty machine at the warehouse (Yilmaz, et al., 2015).
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Supply Chain Analytics
References
Albrecht, K., 1995. At America’s Service: How Your Company Can Join the Customer Service
Revolution.
Davidow, M., 2014. The a-craft model of organizational responses to customer complaints and
their impact on post-complaint customer behavior. , Dissatisfaction and Complaining Behavior.
Journal of Consumer Satisfaction, Volume 27, p. 70.
Radovilsky, Z. & Hegde, V., 2011. Identifying and Analyzing Quality in Supply Chain.
California Journal of Operations Management. 9(1), p. 58–70.
Yilmaz, C., Varnali, K. & Kasnakoglu, B. T., 2015. How do firms benefit from customer
complaints?. Journal of Business Research, 69(2), pp. 944-955.
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