Meetup #88

The Not So Talked About Reasons Model Monitoring Fails

Congratulations! You’ve researched, developed, and deployed your model. Obviously, the next step is monitoring. Now it’s tempting to focus on the technical and dive into drifts and data anomalies, but there are other critical organizational challenges that can negatively impact your ML operations just as severely.  In this talk, we’ll cover both hard organizational challenges like building signal vs noise tolerances, and soft organizational challenges like stakeholder identification and aligning expectations. We’ll also share some best practices on how to lead model observability discovery in your organization and build measurable KPIs for success.