In the article Big Data Analytics and its Impact on the Manufacturing Center, the author examines the increasingly important role big data analytics is having on manufacturing. Big data services are projected to jump to $187 billion in 2019 from the $122 billion in 2015. With such rapid growth, manufacturing stands to greatly benefit from big data in ways such as increased productivity and preventative maintenance. Big data analytics really comes down to understanding the data and having a set goal in mind when analyzing it. Those companies that fail to take advantage of this growing industry could be a serious disadvantage in the very near future.
Big data analytics can be simplified a bit by understanding exactly how the data is initially organized and analyzed. Initial run throughs of large data sets usually are to identify any obvious trends using mean and standard deviation. The data can be visually represented to better observe these trends. Further examining the data for core determinants and correlation analysis can lead to deeper understanding. After these initial methods, more powerful statistical methods such as artificial neural networks and significance testing. Although there are certainly more methods that can be used, the four mentioned are arguably the most popular and can yield deep insights into large data sets. From the results obtained using the above methods, process understanding and improvements are almost a guarantee.
The article further goes into some particular avenues that big data analytics has already helped manufacturers. Cost savings is always a hot topic and manufacturers have experienced cost savings in production and packaging as well as warehousing and inventory. Understanding workforce efficiency is another aspect of the process where big data analytics has been useful. All the workforce data can be summarized and analyzed to see where and how employees work most efficiently. Finally, the most powerful way big data has been helping manufacturers is in its ability to help collaboration between departments. The flow of information between such places as engineering, management, and the production floor allows a much greater understanding of the entire manufacturing process thus allowing improvements not previously thought possible.
Do you know any reason other an unfamiliarity that a manufacturer wouldn’t invest in big data analytics?
Do you think there is a chance that big data analytics services will grow even faster than projected?
With the growth of big data analytics, do you think big data analytics jobs will be some of the most important in the future?