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The Opportunity

  • The company needed to predict when, over the next three months, certain components would trigger alerts indicating a need for repair.  They wanted to take a date-driven approach and use data mining and machine learning tools to help them move from reactive, to preventive maintenance.

Our Approach

  • As part of our business model to “help companies compete on analytics” we offer services where our team of data scientists work side-by-side with our clients’ analytic team.  In this case, we helped our client process the data for analytics, identified the appropriate methodology approaches suitable for the task, and taught them how to use the technology to produce predictive models.

The Impact

  • The client became proficient in building predictive models and was able to demonstrate to stakeholders that they could reduce unscheduled maintenance through predictive analytics.
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