Big data more recognized as needed in the manufacturing sector

A new study from the Alan Turing Institute and Warwick Analytics found that big data analytics is becoming increasingly accepted by the manufacturing industry and is seen as offering a competitive advantage by those using it.

However, 41% are still in the beginning stages and 50% did not understand the difference between business intelligence, big data analytics, and predictive analytics, showing that big data practices are still in their infancy.

When asked to rank the main technical inhibitors to adopting big data analytics, data being spread among too many systems, which take too long to join and transform, topped the list, followed by concerns over the quality of data and the amount of time required to clean it.

Other technical inhibitors included key data being unstructured; a lack of the right data; technology being too new/unproven; problems associated with having too much data, and answers being too difficult to understand and/or implement.

Manufacturers that do “get it” are using data obtained from the use of actual products “to improve the development of the next generation of products and to create innovative after-sales service offerings,” the report stated.

The report also noted that manufacturers “have tremendous potential to generate value from the use of large datasets, integrating data across the extended enterprise and applying advanced analytical techniques to raise their productivity both by increasing efficiency and improving the quality of their products. However, the reality is that very few of today’s manufacturers are close to this vision yet.”

The Manufacturer has a more complete breakdown of the report at this link.