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Quality and warranty cost reduction strategies


Jim Johnson of IBM gave IBM’s point of view on quality lifecycle management. Jim works in Global Services and works with auto and truck manufacturers. IBM’s research shows:

  • That warranty reserves accrue at between 1% and 3% of sales and this is continuing to increase.
  • Detection to correction cycles average over 100 days and can exceed 220
  • Electronics in cars adds complexity
  • No trouble found issues are increasing and are tricky
  • Disconnected and regionally based claims systems don’t provide a comprehensive view

Global warranty management is their approach to addressing these isues and this involves a common system, common processes and governance and global business rules. The need is to identify and correct warranty issues as quickly as possible, as early in the lifecycle as possible. Business rules and advanced analytics (decision management, in other words) are critical to managing this.

Also, they see that bringing new data sources from blogs, enthusiast sites, call centers and integrating with the data from claims can really improve the results. But this data must be managed and turned into an asset through the use of analytics and the application of business rules – make sense of the data and get earlier awareness of what is going on.

Their model involves defining a strategy, building on standard processes, ensuring governance, thinking globally and doing all this on a solid architecture. Key elements:

  • Diagnostic information systems are part of the architecture and are important to bringing the raw data captured about vehicles with problems back to the engineering community.
  • Warranty Claim Processing using business rules and integrated with diagnostics
  • Data warehouse that integrates all the various data elements
  • Sharing the data to suppliers and manufacturers as needed
  • Quality analytics using diagnostic data analysis, claims analysis (including accrual forecasting and fraud trends), supplier quality analytics and predictive early warning for problems.

It is all about “earlier warning”. He gave an example of using telematics and diagnostic systems to both collect data automatically from vehicles and push early warnings back to owners. Obviously this requires the rapid integration of the diagnostic data, effective analysis of this data and automated actions taken as a result (using rules).

Clearly this vision of IBM’s for future warranty systems is heavily reliant on the use of decision management to make all the data being collected active.