Forecasts Future Failures
Our experience has proven there is no “one size fits all” approach, therefore each machine learning model is run on your data and evaluated for accuracy and precision to find the model with the best fit for your system.
Probability of failure (PoF) is the likelihood an asset will fail over a defined timeframe. pureAnalytics’ unique PoF Analysis, through Machine Learning, yields a highly-functional data-driven metric that accounts for data uncertainties and is easily updatable as new (future) failure data becomes available. Pipe break and leak history, GIS data, environmental hazards, and many other inputs are evaluated for their influence on future failures.
Understanding the “Why”
pureAnalytics’ approach to data analysis is to communicate a deep understanding of which data inputs are influential, the process for evaluating them, and the key insights so you can make the most informed decisions. We work with you to highlight specific trends, conclusions, and potential next steps, bringing insight and value to the PoF Analysis.
pureAnalytics adds additional value through data augmentation using a vast and exclusive utility asset database that includes millions of leaks, breaks, pipe inspections, valve inspections, and other related records. The augmentation approach has proven to minimize the impact of many data gaps and increase the accuracy of the PoF results.
pureAnalytics believes that each utility’s data, analysis, and decisions should continue to evolve as more insights are drawn from the many utilities we interact with. pureAnalytics will provide quarterly communications on new insights into your data based on the continuous learning and improvement approach we so strongly believe in.
Why Choose Us?
Our success is defined by the strength of the partnership between our teams and exceeding your expectations while improving on what matters most – delivery of safe, clean drinking water to your customers.