Case Study: StrongArm Tech achieves 54% reduction in workplace injuries and $5.3M annual savings with Databricks

Reducing workplace injury rates by 54% with Databricks

StrongArm Tech builds wearable sensor solutions to protect industrial workers but struggled to turn massive, high-frequency time-series data (about 1.2 million points per person per day) into reliable analytics. Data was spread across disparate systems, ETL and cluster provisioning were slow and brittle, and data-science work was constrained by limited compute and poor cross-team collaboration—hindering their ability to predict and prevent costly workplace injuries.

By adopting Databricks as a unified data platform—using Delta Lake for reliable ingestion, Databricks Notebooks for collaboration, and MLflow to manage the ML lifecycle—StrongArm streamlined pipelines and accelerated model development and deployment for haptic-feedback wearables. The result: up to a 54% reduction in workplace injuries, roughly $5.3M in gross annual savings (about $5.35M) with a 355% ROI, and a 78% reduction in the margin of error for evaluating injury risk.

StrongArm Tech

Bryant Eadon

Chief Information Officer