In this article author has explained ‘Statistical Data Analysis for
Buying House towards better Quality Management’. The purpose of writing
this article is to show some of the difficulties that big buying houses
have been facing during the past years.
Supply chain in the apparel industry has become more complicated since
companies have been seeking for lower cost and they have started to
source their suppliers all around the globe. That brought the need for
designing better control system of already very complicated supply
network.
The Supply Chain in Apparel industry, illustrated in
Figure-1, is comprised of its main subjects: customer, retailer, garment
supplier and fabric supplier. This kind of supply chain is more or less
similar with most of the apparel companies. Usually, larger size
companies can have more complicated structure, especially in the garment
supply segment. Figure-2 illustrates the garment supply in larger
apparel company. Several subjects can be distinguished: buying house
(BH), garment supplier –contractor (GSC), garment supplier
sub-contractor (GSSC). In cases like this, where garment supply network
is getting more complicated, the company needs to think of establishing
efficient Quality Management System (QMS). That will ensure more
systematically approach in Quality Assurance (QA), detection of causes
and solving the problems for low quality.
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Figure-1: Apparel Industry Supply Chain |
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Figure-2: Garment Supply Hierarchy |
In order to have record for the QA performance of every supplier,
Statistical Data Analysis is necessary to be obtained. Getting necessary
data, that will describe the real QA situation in the company, can be
ensured by designing sufficient supportive documentation. One of the key
documents is the inspection report.
Inspection report should contain information which after analysis can
give clear picture for the Quality status in the company. The following
table presents the most important information that one QC report needs
to have.
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Table-1: Information to be collected from QC Inspection Report |

The information from the QC report can be digitalized and incorporated
into the ERP system of the company. Digital version of the QC report
should be able to satisfy the needs for providing the necessary
information and making the work process easier. The following picture
illustrates an IT solution as QA support in the company. Beside features
like, attaching pictures, adding comments and generating electronic
document that can be send via e-mail, the IT solution for QA support
should be able to keep history records and making statistical analysis.
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Figure-3: IT Based MIS System for data analysis |
Statistical analysis can be conducted based on the historical data from
the QC reports. The analysis can be designed according to the needs for
QA. The Statistical analysis report can present the supplier performance
in terms of quality during the last 3 months, 6 months or one year.
That will help the QA manager to have visual image about suppliers who
have had bad performance during the last period. To know the biggest
quality problems or the most problematic product types Pareto analysis
can be done based on data collected from quality inspection reports.
Also this kind of analysis can show the cost due to low quality (rework,
2nd choice pieces, delay). On the other side, the analysis can locate
problems related to quality inspectors and their performance. An
extended list of statistical analysis can be done, and it is presented
in addition.

You can do analysis based of last 3 months data. Following parameters
can be considered while collecting data. You can use multiple forms
instead of one. Later make matrices for supplier performance on various
parameters.
- Number of orders per supplier;
- Number of pieces per supplier;
- Cost of orders;
- Type of products per supplier;
- Number of RTS orders;
- Number of defective pieces;
- Cost for poor quality (2nd choice pieces, rework, delay);
- Type of defective product types (color, sizes);
- Type of defects;
- Number of defects per piece;
- Number of defects per order;
- Supplier name (responsible for low quality);
- Inspector name (responsible for low quality);
- Department (occurring the low quality);
- Inspected orders per QC inspector;
- Inspected quantity per QC inspector;
- Travel distance (to supplier) per QC inspector;
- Type of products per QC inspector;
- Number of orders without approval (raw materials approval, sample approval, size set approval);
- Number of orders with late approval;
- Number of delay delivery date orders;
By knowing the existing quality problems, it is much easier to locate
the problem causes and came up with solution for problem solving.
The most important thing is that the QMS should be accepted and
understood by all the participants in it. They need to follow the work
standards and get the knowledge from the statistical data that can be
used for problem solving and setting goals for the future.
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