Case Study: a Fortune 500 Technology Hardware Company achieves 95% accurate critical service request prediction with LatentView Analytics

Fortune 500 Technology Hardware Company saves $20 million per quarter with LatentView Analytics

LatentView Analytics helped a Fortune 500 technology hardware company address a significant challenge in its hardware services division. The client needed a way to predict which service requests would become critical, as preventive maintenance is vastly more cost-effective than reactive repairs. The existing manual process of flagging critical issues was prone to errors and inconsistency.

LatentView Analytics developed an Early Warning System solution that utilized text analytics to extract insights from behavioral data, which was then combined with structured service log information. This system could accurately predict critical service requests. The solution achieved over 95% prediction accuracy, resulting in substantial quarterly savings of $20 million for the client.