An Early Warning System (EWS) with over 95% accuracy in predicting critical service requests was created, saving $20 million per quarter for a Fortune 500 technology hardware company.
The Problem
In the hardware services space, preventive maintenance is 40-45% cheaper than ‘after the event’ corrections, but in order to prevent, one needs to precisely predict service requests (SRs) that can turn critical.
The Before State
Account Managers through manual inspection flag critical SRs which lead to errors and person dependent situation.
The LatentView Solution
Utilized text analytics techniques to extract behavioral data which was combined with structured data like service logs to generate predictions on each SR turning critical.
The After State
Early Warning System (EWS) with over 95% accuracy in predicting critical SRs saved the client $20 million per quarter.
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