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Big data, analytics key to manufacturing headway

Posted: 30 Dec 2014 ?? ?Print Version ?Bookmark and Share

Keywords:IDC? manufacturing? big data? analytics?

The present state of development in the Asia-Pacific region provides tell-tale signs of the significance of new technologies to make them better and faster, especially in terms of executing accurate and precise business decisions.

A good part of the global supply chain management industry has been turning its attention to big data and analytics technologies in order to analyse large volumes of data (including real-time and/or historical) from a vast variety of sources. This allows data to be processed and analysed at great velocity to reveal its value. In turn, this is helping companies to stay competitive in the global market, increase the return on investment faster than ever before, and become part of a more efficient and agile supply chain driven by valuable data.

However, according to research, analysis, and surveys by IDC Asia/Pacific, manufacturers there might need a little push. These organizations seem to remain cautious in the adoption and use of analytics tools, as we can see in the infographic below. This is not limited to the Asia-Pacific region; other manufacturers around the globe also need to be aware of the paramount importance of the tools that are part of next-gen manufacturing and become faster adopters.

Big data analytics

Despite the benefits big data and analytics can offer, manufacturers are still adamant in going all out in terms of adopting the tools that would speed up processing of large volumes of information, said IDC.

Waking up to needed changes

Labour costs in China have doubled in the past five years, and its share of all exports have gone from a mere three per cent in 1995 to 11 per cent in 2012. Despite this growth, two out of five manufacturers in the region are not aware of big data and its paramount importance in today's business environment, IDC Asia/Pacific stated. Manufacturers are analysing only 47 per cent of their transactions, 45 per cent of their text and 32 per cent of their machine data.

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