Forward looking water main management is critical for water utilities. With responsibilities that include water safety, water loss, keeping customer rates low, and minimizing public disruption, utility leaders have their hands full. A comprehensive, efficient approach to understanding the state of their buried water infrastructure and addressing risks before they become big problems is critical.
Yet for too long, utilities and engineering firms have relied on outdated methods and heuristics when attempting to assess risk for water mains. Though tools like internal experts, spreadsheets, and weighted models can start to provide a picture of risk, none are able to provide a complete, highly accurate, dynamic view of your water main infrastructure needs. Without a comprehensive approach, the ability to proactively and effectively plan for and address system needs is highly limited.
Predictive machine learning models are the new standard for water main management. Predictive analytics go beyond current industry practice to put the most cutting edge, academically rigorous algorithms and predictive processes into the hands of local leaders. With this enhanced data, water leaders are able to make the best, most informed decisions for the infrastructure they manage.
Let’s explore why predictive analytics is the new standard for water main risk management.
Predictive modeling puts your data to work for you
Most utilities have mountains of data, often going back decades. But data digitization alone isn’t enough to enable the simple, effective use of this data for the majority of employees. While this data sits in a database (or several), it is often still difficult to access or to engage with for decision makers, forcing critical decisions to be made based on incomplete data or with single, limited heuristics.
Predictive analytics can take all of this data, integrate it into a unified model, and identify what influences risk based on your own data. These predictions then serve as accurate, actionable insights to empower local leaders.
High quality predictive tools, like BlueConduit’s Water Main Predictions, offer explainability alongside predictions to help water system leaders understand some of the complex dynamics contributing to water main risk of failure in their water system. This improved understanding of water system dynamics, alongside the predictions themselves, lets the data speak and empowers water system leaders with all of the data they need to make critical decisions related to condition assessment, water main maintenance, and capital improvement projects.
Machine learning offers higher accuracy than traditional regression models (with similar effort)
Traditional regression models offer reduced accuracy because they are limited in their ability to explore how different variables interact. This is a significant challenge because assessing water main risk is all about how different factors interact with each other (for example, main material, soil type, and weather) to create a circumstance in which the main will fail.
New machine learning models aren’t limited here. These models can explore non-linear relationships between variables, as well as how different variables interact with each other. Accordingly, machine learning models regularly provide more accurate predictions, measured across multiple performance indicators.
This statistical approach takes a similar amount of data & effort compared to traditional regression analysis, but the results generated are far more accurate and useful. So if you’re already committing effort and resources to statistical methods, it just makes sense to use methods that will generate the best results.
Models are dynamic and evolve over time
Does vulnerability and risk in your water infrastructure evolve with time? Yes. This means that traditional, static analyses are out-of-date almost immediately, limiting their usefulness.
On the other hand, predictive modeling embraces your dynamic data and provides similarly dynamic, continuously updated results. For example, BlueConduit’s Water Main predictions provides likelihood of failure predictions for every water main on multiple time scales (ex, 6, 12, and 18 months) to account for seasonality and other dynamic change in risk profiles across time. In addition, the predictions are continuously updated as new data, from breaks to weather, is added to the model, to give a real-time snapshot of risk based on the most up-to-date information available.
Highest quality predictions enable local decision makers to make the right decision at the right time
Local water utility leaders, and their engineering partners, are experts in water infrastructure and deserve the highest quality, most advanced tools available to enable them to have the right data to make the right decisions at the right place at the right time.
Predictive analytics and machine learning models are the gold standard for water main risk assessment and decision making. And beyond the models themselves, the tools delivering predictive analytics matter too. That’s where BlueConduit comes in.
With BlueConduit, you can put our academically-based data science process & expertise to work for you. Our success is your success; we’re creating easy-to-use technology tools that work to limit expensive digging and focus your resources on the most critical areas of need.
Ready to learn more about how BlueConduit can help you better manage risk in your water main infrastructure? Reach out for a conversation today!
