Maximize Fleet Efficiency for a Competitive Edge

Improve on-road performance, eliminate unplanned downtime, reduce fleet fuel consumption.

With transportation and logistics demand expected to double in the next two decades, reliability will assume paramount importance.

Identifying and predicting anomalies helps keep the fleet on the road generating revenue.

Gain Complete Control Over Fleet Operations

Reliability reigns supreme in your demanding industry. Progress DataRPM Anomaly Detection and Prediction will help find every opportunity for improved business results and an enhanced customer experience. The result? Complete control over fleet operations.


Anomaly Detection

The key is anomaly detection—the process of identifying outliers in a normal range of performance. Historical data, current data and external influencing factors are analyzed simultaneously to establish baselines for asset performance on an ongoing basis.


Predictive Maintenance

When implemented through unsupervised machine-learning, anomaly detection can help predict future anomalies before they happen so you can take appropriate action. The result is assets that last longer and perform at their best—helping you avoid costly repairs and downtime.


On-Time Arrivals
75% reduced service disruption
65% higher uptime
50% reduced warranty cost per repair
Improved Operational Visibility
70% reduction in diagnostic time per repair
54% earlier advance diagnosis of potential failure measured in days
25% accelerated root cause analysis
Strategic Cost Savings
54% improvement in year-on-year service cost
40% reduced warranty cost
10% lower operating costs
Success Story

Leading Telco Achieves Multi-Million Dollar Savings

DataRPM identified 85% of customers that were likely to be affected by set-top box failures and the reasons behind the failures using an automated predictive model.

Read the Story

Progress Anomaly Detection and Prediction

Detect and predict anomalies by automating machine learning to achieve higher asset uptime and yield maximization.