The analysis addresses the following questions:
Our predictive models were suspiciously powerful with nearly 80% precision. A reverse causality case was uncovered: received claim cases undergo different measurement procedures. By removing the measurements that were done after a claim date, the picture became more realistic.
There are no obvious predictors of claims, rather hundreds of subtle ones that accumulate to form one strong predictor.
Classifier built which predicts future customer claims.
Process improvement recommendations provided.
Measurements optimally sequenced to reduce assembly time required.
Your message has been sent. Our team will get back to you as soon as possible!
Please fill in the contact form below and we'll get back to you as soon as possible.
Your message has been sent. Our team will get back to you as soon as possible.Close this window