Warranty Analysis - Amazon Web Services

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Warranty Analysis
Why

Customer Value Proposition



Improve field reliability of the products
Reduce downtime of products
Supplier Value Proposition





Reduced warranty costs
Better planning of funds, inventory & logistics because to more
accurate warranty forecasts (while estimating and setting targets
for EBIT, net working capital, etc)
Profitable pricing of extended warranty/services
Increase brand reputation & customer loyalty
Useful as lesson learnt for next generation products
How
Utilizing field failure data collected during warranty period
 Improve products



Identify and prioritize field failures which can increase reliability
and reduce warranty cost significantly
Initiate design/process changes and implement them to mitigate
or contain priority field failures
Forecasting warranty


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Create stochastically models to capture failure trends at failure
mode level
Generate forecasts from the models at failure model level and
roll them up to product levels
Forecasts should based on requirements like failure count for
inventory planning or recall strategy, costs for reserving amount
to pay warranty, costs of extending warranty
Improve Products
Improve
Field Failures
Identify
Prioritize
Fix
Forecasting
Recall ?
Model
Estimate
Make Decision
Data
Extended
Warranty
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