Water Utility Work Order Analytics & Optimization

Overview

This utility provides drinking water and wastewater services to 80,000+ residential and commercial customers. They maintain over 1,483 miles of water distribution pipelines, over 1,234 miles of wastewater collection system pipelines, and a growing reclaimed non-potable water system. The client’s goal was to increase Business Intelligence capability, leveraging the benefits and scale of Microsoft Azure to support operational data analytics and reporting. As such, the leadership team tasked Tallan with shaping and implementing a pilot to prove the concept of the next-generation data platform.

Industry

Utilities

Annual Revenue

$59.8 Million

Technology

Data and Analytics, Cloud

Mapping out a Target Architecture.
  • An assessment of the current data estate, data sources, and conversation with leadership revealed that the best pilot use-case was to track, report on and analyze work orders in the customer’s SAP system, combined with location data from their GIS system.
  • Tallan specifically focused on plant maintenance for the five different locations this customer manages, to ensure smooth growth across an entire district.
Streamlining 600+ Data Pipelines with Azure.
  • Data pipelines from SAP and GIS sources, previously having been pulled manually, were automated for geospatial reporting on work orders, providing key insights for areas of optimization across 140+ source entities.
  • Monitoring these data pipelines helped sustainably manage utility resources from a hardware and staffing perspective. Increased accuracy in data analysis also allowed for more efficient operations, proving the next-gen data platform as a valuable investment.
Looking Ahead.
  • Tallan provided training for this organization’s internal teams to ensure smooth adoption and empower the expansion of the platform. This client’s team has already started making their own ETL processes using the methods and best practices Tallan taught them!
  • This pilot has successfully evolved into a larger data estate project, with more data sources being ingested and actionable insights produced as a result. Sensor (SCADA) data, additional data points from disparate systems & databases, and larger volumes of data are now being integrated into the new platform to support additional analytics in other departments.
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