Thames Water had a pump problem, and as a massive water and wastewater agency serving over 15 million customers in the London area, the problem needed to be addressed as quickly as possible. The company noticed that one of its pumping stations was using an unusual amount of electricity, yet the output of that station remained the same. This is often a sign that impeller blades have worn down and that the system needs repairing, so crews were dispatched to find and fix the problem.
After opening equipment covers, inspecting blades, and still finding no issue, technicians began to talk to operators, who, as it turned out, were often using two pumps when using one pump would have been sufficient. By reviewing the training of these operators, Thames was able to reduce their power consumption at the site by 10,000 British Sterling per year.
This anecdote perfectly speaks to the state of analytics in the water industry - big data, IoT, and analytics have continued to have profound effects on how the industry operates, but the technology itself isn't a panacea. At the core of it, software is better than humans at collecting, sorting, and classifying data, but a human touch is still needed to understand the data and draw meaningful conclusions.
The bottom line is that “you're not buying analytics to solve a problem. You're buying analytics for your employees to solve more problems.”
Read the full article on Water World here.