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Predicting Asset Failure and Process Changes with Self-serve Analytics

Jan 26, 2021

Predicting Asset Failure and Process Changes with Self-serve Analytics


Water utilities have no shortage of data – real time and historical, and the promise of analytics to harness this data is well documented and widely promoted. However, how does the hype compare with reality when it comes to non-data scientists using these tools and driving meaningful outcomes? The benefits are clear for analytics, mine your existing data to reap the rewards:


  • Drive down cost
  • Improve efficiency
  • Improve accuracy for water demand planning
  • Decrease unplanned downtime
  • Improve chemical management


Wrangling data, building models and algorithms are often considered the realm of data scientists, resulting in analytics projects that limit the number of use cases and therefore the wider benefit across a water utility. However, the journey to success doesn’t mean that process engineers need to suddenly become data scientists. Proven processes and software technologies make analytics achievable for every industrial organization. Using analytics, engineers can combine data across industrial data sources and rapidly identify problems, discover root causes, predict future performance, and automate actions to continuously improve quality, ease compliance, and decrease chemical and energy consumption.


With analytics, utilities can discover previously missed opportunities to act quickly and proactively to identify process variability, troubleshoot issues in the water network, and ultimately drive more efficient operations.


Participant takeaways:

  • Understand how simple analytics can greatly optimize the water network
  • Learn how to align engineering domain expertise to five analytics capabilities
  • Discover how other utilities – large and small rural – used analytics
  • Tips on how to get started



Brian Radmer; Senior Solution Architect Analytics, GE Digital

Akos Jancsik; Senior Solution Architect Analytics, GE Digital


Event Details

DATE AND TIME Jan 26, 2021 Starts at 11:00 AM - Ends at 12:00 PM Times listed are Mountain Time, USA

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