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| Case Study |
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Global communications leader designs Early
Warning System for RMA |
A leading global communications leader partnered with Patni to design a system that helped the
former reduce product recalls through an early warning system.
The Client
A global communications leader well known for its products in the wireless and broadband domain.
The Challenge
With the goal of improving product quality, the client was constantly on the
lookout for reducing product recalls and solving quality problems before they
mushroomed. This involved analyzing returns and repairs information, shipment
information and manufacturing related information. For analyzing product
quality, the client required information on various metrics pertaining to Return
Material authorization (RMA).
With a diverse landscape consisting of ERP systems, CRM systems and regional
Manufacturing Execution systems, the client was forced to use reporting tools for
extracting and consolidating the data. The complexity of the process can be seen
from the fact that more than 1000 users across the globe analyzed the
information, requiring the systems to be up and running on a 24x5 basis.
As data was stored on different applications, data mining activities could not be
performed across different technologies easily to determine similar design,
component or process problems. A further level of complexity was added due to
the fact that there were huge data volumes generated as a result of queries
related to sales order, shipment information and repairs information from a
global user base. With more than 6000 reports generated on a daily basis, the
client was finding it extremely challenging to complete analysis of data and take
effective decisions within specified time frames. The delays in analysis of data
allowed more unreliable parts to be shipped before a potential reliability
problem was identified. In an era of intense competition, this hampered and
delayed the client's ability to take effective decisions. Further, as the process
was manual, human error was always a possibility.
For addressing this issue, the client wanted to build a global repository that
would centrally hold shipment information, serialized information and
returns-repairs details. Through this exercise, the client also wanted to estimate
and allocate the warranty liability for different suppliers, who were responsible
for bad or substandard quality.
The Solution
Patni partnered with the client to extract and consolidate data from multiple sources into a
single data warehouse. As a first step, sales order shipment data present in one global ERP
system was combined with serial details present in the three regional manufacturing
systems. Returns information of the received products present in one global returns
management system was extracted and put in this datawarehouse.
Information about the returned products was compared with the shipment
information to calculate various Returns metrics like ERI (Early Return Indicator),
YRR (Yearly Return Rate) and LTR (Long Term Return Rate). These metrics provided
the users with early warning signals about the products which were getting
returned immediately by customers and prompted them for corrective measures.
Further, information about the returned products was compared with the
manufacturing details and shipment information to calculate various key
performance metrics like MTBF (Mean Time between Failure), MOB (Month of
Build), MMA (Monthly Moving Averages), and SAR (Survival and Reliability). These
metrics provided various types of trend analysis that were subsequently used by
the client to track product field performance, detecting early issues, and taking
corrective measures. For example, shipment tracking using the MOB and plant
code allowed the repair centers to forecast and plan repair capacity.
As part of the exercise, Patni helped the client in customizing and generating
standard reports, ad hoc reports as requested by individual users. These reports
helped the client in quickly analyzing information such as top products being
shipped in last month/quarter, top products being returned in last month/quarter,
typical repairs performed on returned products, and the top customers who were
returning these products.
The Technology
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Informatica Power Center
6.x/ 7.x on Linux |
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Informatica Power
Analyzer 3.x / 5.x on
Linux |
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Oracle 10g RAC. |
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The Benefits
The global repository system has enabled the client to perform quick analysis of the
returned material. Some critical benefits include:
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Efficient RMA process due to early indicators for detecting immediate issues in the
products which could cause returns |
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Ability to proactively alert the returns-repairs center about the possible future
returns the client could expect |
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Automated, fast, efficient and reliable process of generation of Returns metrics has
helped the client in tracking the product's field performance and provided it early
indicators on product performance |
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Return Rate metric generation was done in accordance with the TL-9000 standard. |
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