Objective Root Cause Analysis, ORCA

Objective Root Cause Analyzer, ORCA was specifically designed for the needs of manufacturing and automobile sectors. It analyzes large field data from the OEMs. It caters to one of the major growing concerns of OEMs like increasing warranty cost and claims.

Warranty analysis has become the need of the hour to survive in today’s competitive world. In many industries, the current state of warranty analysis can be categorized as first generation (1G) analysis, where the primary focus is on defect count rather than cost and there is no substantial inference from trendline analysis.


With the advent of ORCA, we have introduced second generation (2G) analysis. In this methodology, we provide single as well as multi-model comparison of all the products, a detailed cost analysis of all the products, identification of root cause of high warranty claims and how to reduce these costs.


ORCA comes with a patent pending recommendation system that helps give insights on how to improve engineering design of the product and also helps prioritize tasks. Along with this, a thorough inferential statistics and component analysis helps organizations for new product development. ORCA’s Product Health Monitor helps organizations to acquire fundamental information at a glance. Above all, ORCA provides all of this information in just a few seconds.

ORCA is designed by keeping the ease of operation, product manufacturers’ needs, and the end users’ product perception in mind. It analyzes 3 million data points in just 40 seconds. Users are given multiple graphical visualizations to interpret the results. Apart from this, ORCA generates a downloadable report which is the analysis in textual format. This report gives useful information from finance, engineering, quality, and manufacturing perspective.

Quick, action-oriented, analysis by ORCA, shortens time to fix the issues thereby cutting the vicious cycle of increasing warranty claims by not taking quick action on components with high failure rates.

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