Delivering clean water to the people of the United States is a significant accomplishment, especially with a total pipe network of almost 2.2 million miles of underground pipes with a total asset value of almost 2 trillion dollars.

However, in maintaining this service, water organizations are faced with challenges from their local infrastructure as assets deteriorate over time, and they must make critical decisions on how to invest their capital before service interruptions occur.

Historically, asset managers and engineers have worked with consultants and relied on age-based analysis to develop optimal investment plans. As the water industry evolved, more modern technologies have been used to help manage assets and prevent failures.

Now, cameras and sensor devices are playing a greater role in helping water utilities gain more control of their assets. In addition, the rise of analytics has provided organizations with useful insights and smarter ways of gathering information.

Let’s explore how data analytics and machine learning support organizations with their investment decisions, as well as demonstrate how factors such as likelihood of failure (LoF), consequence of failure (CoF), and risk are essential parts of the planning process.