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In the article Is Data the New King of Manufacturing Technology?, the author wishes to establish a relationship that fits the phrase “the tail is wagging the dog.”  In broad terms, it is a relationship where a secondary offshoot actually becomes the main operation or begins to run the main operation.  In this case, manufacturing information technology is the dog and the tail is big data analytics.  Big data analytics is quickly becoming enterprise platform of the future, and those that which to stay at the cutting edge of manufacturing need jump in so they don’t get left behind.

In the manufacturing world, data has been collected since at least the 1980s, but in most cases, the data collected was just a byproduct of the process itself.  The data was stored and mostly unused.   As business intelligence tools began to transform the landscape in the 1990s, managers and process owners began to realize more could be understood from all the data collected.  This evolution has led us to the big data analytics of today – the answer to the question of how any part of the process can be improved via analyzation of data.  The Industrial Internet of Things (IIoT) has evolved to be able to capture data from any sensor, equipment, or even phone and send this data to a platform, such as the cloud, to be analyzed and have insights developed.

This data analytics tools, and the profits companies are experiencing given their usage, has accelerated the entire industry forward.  Manufactures are connected on all their platforms and have the ability to trade their assets on a global scale – thus satisfying demand quickly.  This data ecosystem has allowed for personalized processes for creating and delivering products because manufacturers know more about their customers.  With the power of big data analytics, a manufacturer can mine vast amounts of production and customer data to improve and even redesign processes.


Do you believe all this data collection will create more jobs?

Remembering that correlation does not always equal causality, do you believe that some trends will emerge within manufacture’s data that do not actually exist?

With more industries relying on data, do you believe the human aspect of understanding processes may be left behind?


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