Information Overload in Water Systems

PM: What does not get measured does not get managed. This is a principle I subscribe to. But you need a second principle to make this work: Avoid information overload. Here is an example of how a company figure out how to analyze large amounts of data to identify useful information that can be acted upon.

Pipe Dreams: To plug leaks from the water supply, you first have to find them.
An effective way of detecting leaks [in municipal water systems], both accidental and deliberate, would therefore be welcome.
TaKaDu, a firm based near Tel Aviv, thinks it has one. The problem, in the view of its founder, Amir Peleg, is not a lack of data per se, but a lack of analysis. If anything, water companies—at least, those in the rich world—have too much information. A typical firm’s network may have hundreds, or even thousands, of sensors. The actual difficulty faced by water companies, Dr Peleg believes, is interpreting the signals those sensors are sending. It is impossible for people to handle all the incoming signals, and surprisingly hard for a computer, too.

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