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In the article Big data Analytics is Transforming Manufacturing, the author reviews a study done by Alan Turing Institute and Warwick Analytics regarding how big data analytics is finding its way into manufacturing.  The main points of the study indicate that many manufactures understand the usefulness of big data analytics, but not many are actually not using big data to its full potential.  The study indicates 7 key points where big data could offer benefits to manufacturers, and it also reveals some interesting findings.

The study itself gleaned its findings from views of 50 senior industrial executives, most of whom are with global manufacturing companies in the UK.  Its noted that the greatest value of big data analytics is in its predictive powers, giving companies the ability to extract meaningful insights on processes, production, and maintenance, to name a few of the important manufacturing functions.  Three of the seven key areas addressed in the study were improving yield, predicating and/or preventing maintenance, and improving supply chain operations – all areas where manufacturers could extract value through big data analytics.

The findings of the study paint an interesting picture of big data at this current point in time.  Just over 40% of businesses are in the experimental stages of using big data analytics, but surprisingly, 50% didn’t know the difference between big data and previous business intelligence tools.  With a knowledge gap present, it’s not surprising that more widespread adoption of big data analytics isn’t happening.  Without an understanding of how big data will improve a corporation, it’s hard to get big data programs sponsored and rolled out.  Though these issues are certainly present, there are few absolutes.  One of them is that the data is being collected, in huge amounts, and that this data is normally being used to some extent.  The issue lies in that the proper analytics are not begin done so the possible benefits are not being realized.


What will it take for more manufacturers sponsor big data programs?

What are the differences between big data analytics and previous business intelligence?

A reoccurring question seems to be – are we collecting too much data?  If so, how do we begin to collect only the pertinent, necessary data?