Nishant Dhyani is a fleet efficiency manager at China Navigation, a job he describes as innovative and exciting. It is a job that sees him at the front line of data management. Here he puts forward his thoughts about how to make use of this new industry tool.
THE latest buzz word in the shipping industry happens to go by the name of ‘Big-Data’. More and more companies are attracted towards it and difficult time in shipping makes it even more seductive when there is enormous pressure on cutting company’s operational costs.
Big-data service provider companies are making merry by showing off their hi-tech products which can transmit data from ship to shore at the highest possible frequency. Their analysis module can literally make a co-relation between your mother-in-law’s weight and main engine’s specific fuel oil consumption over a period of time! There is no doubt, they do an impressive job and are definitely there to stay. But can we trust them blindly without any cerebral discussions?
We as a shipping industry, are somehow stuck in a time capsule. Clearly, there is a big gap between the two realities of this one world. One reality happens to be on shore where big electronic,IT companies are doing wonders by inventing hi-tech gadgets and products while continuously enhancing people’s skill to effectively utilize them. Then we have a second reality on the ship where people are expected to use these intricate products and somehow adopt them in their ongoing age old operations and primitive equipment to create value for the company.With the big-data concept, we have access to high frequency data which can display different trends and fancy graphs over a dash-board. But can we really use all this data to take important decisions yet?
We ourselves know, how accurate the flowmeters are when not maintained and calibrated regularly. When is the last time you sent a technician on board to check all the meters? How about those speed logs and shaft power meters? Accuracy of some measured data points are imperative for controlling operations but are conveniently ignored due to underlying cost or the complexity involved. Having a data base of inaccurate and unreliable measurements only strengthens the old saying of “Garbage In, Garbage Out” without much benefit.
I am certainly not against the ‘big-data’ concept, in fact I am a great user and supporter of it. The larger point i tried to make here is that we need to get our fundamentals right, do our home-work before confidently diving into the big ocean of data.
Mr Dhyani originally posted this opinion on Linked-in.
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