Big Data

The Holy Grail of analytics: How to get purposeful big data

Read how one Australian tram company is using the Internet of Things to get purposeful data that delivers reports to central ops and real-time alerts to maintenance techs and passengers.

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Image: Yarra Trams

In 2013, I heard Neil Roberts, Director of Information Communications Technology for Yarra Trams in Melbourne, Australia, talk about how the company was harnessing big data and particularly Internet of Things (IoT) sensor-driven data to develop a better transportation system.

Robert's dissertation impressed me because everything Yarra did with its big data was being plugged directly into the business and was driving immediate benefits to almost everyone. It reminded me of what an acquaintance who had spent a summer at a meat processing plant told me: "They don't waste a thing from the animal. Even the hair gets sold for use in hair brushes. The nails get sold to soap manufacturers."

Yarra is no meat processor; it's a 100-year old tram network with more than 250 kilometers of double tracks, and is considered to be the largest tram network in the world. But like the meat processor, Yarra seems to have left "nothing wasted" by wringing the most out of its big data.

Yarra performs rigorous monitoring of its large tram network with the help of 91,000 data sensor points that have been placed on 91,000 separate pieces of tram equipment that range from new to aging. In some cases, automated wheel-measuring machines stationed at tram depots are programmed to detect the condition of a tram's wheels. In other cases, sensors are set out on track and are programmed to issue automatic alerts when they detect signs of track wear or breakage.

Both sensor-originated and employee reports are channeled back to a central operations center, and they are also channeled in real-time as alerts to field maintenance technicians and to tram passengers.

To illustrate, if there is an impending failure condition with a piece of track, a sensor automated alert is sent to mobile devices of the field maintenance crews, and a crew is immediately dispatched to repair the track. Better yet, these same sensors produce predictive analytics that signal a piece of track that has not yet failed but that is on the decline; this enables maintenance to repair the track before it fails and causes delays in transit times throughout the system.

Automated alerts from IoT system sensors are also turned into mobile device messages to tram passengers. If a passenger is waiting to board a tram for a specific destination that is obstructed because of a maintenance or other issue in the system, the passenger is advised over his mobile and is given a choice of alternate routes he can take.

There are many pages that others can borrow from the Yarra story.

Not long ago, I visited with John Lucker, Principal and Global Advanced Analytics and Modeling Leader for Deloitte. Lucker was telling me that, "Many of the CXOs we talk to about big data and analytics tend to respond, 'Yeah, we do analytics,' but when we probe deeper, we discover that these same CXOs also don't feel that they have a good handle on the concept, or that they really know what they want from analytics."

I'll take this one step further to say that the Holy Grail of what C-level executives (and enterprises) are seeking is purposeful data that delivers immediate benefits to everyone — the operations staff, customers, and the corporate strategic plan that focuses on how the company and its products and services will be even better tomorrow than they are today. You get there with a clear understanding of where you need to be strategically as an organization, what you need to do operationally to get there, and how big data will specifically deliver value to the endeavor.

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About Mary Shacklett

Mary E. Shacklett is president of Transworld Data, a technology research and market development firm. Prior to founding the company, Mary was Senior Vice President of Marketing and Technology at TCCU, Inc., a financial services firm; Vice President o...

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