Big Data & Analytics: Core to Next-Gen Manufacturing

Looking at the current pace of development in the Asia-Pacific region, it is not surprising that manufacturers are looking at new technologies and tools to help them make better, faster, and more accurate 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 analyze large volumes of data (including real-time and/or historical) from a vast variety of sources. This allows data to be processed and analyzed 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. (Click here for a larger version.) 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.

Waking up to needed changes
Labor costs in China have doubled in the past five years, and its share of all exports have gone from a mere 3% in 1995 to 11% 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 says. Manufacturers are analyzing only 47% of their transactions, 45% of their text, and 32% of their machine data.

Countless case studies and industry leaders have referred to the topic and have proven the efficiency of big data analytics in reducing costs, improving supply chain resilience, reducing unscheduled maintenance, improving productivity with the aid of implementing robotics and automation, attracting new customers and partners, and advancing expansion. Yet there are some challenges that have to be addressed and overcome.

Overcoming challenges
In IDC Asia/Pacific surveys, 37% of respondents say their top It problem is an inability to find the right people with the right skills. However, there is a global knowledge that the real problem is not that talent is hard to find, but that companies don't want to pay the talent what it is worth. Instead, they try to find cheaper labor wherever they can find it. Accepting, valuing, and recruiting the right talent with the right skills is an investment that has proven to pay off more often than not. At the end of the day, happy employees make a happy company, which leads to more efficiency and higher productivity.

One-fifth of repondents said the top IT challenge is the cost of technology infrastructure. However, without investment, there's no advancement in any aspects of a business.

Also, 17% of respondents said the top IT challenge is deciding what data is relevant. To overcome this challenge, choosing the right ERP for the company's specific needs is paramount. It is the best way of making sense of the vast amount of data collected and get real value from its analysis.

Toward next-gen manufacturing
IDC Asia/Pacific predicts that, within the next two years, manufacturers will use big data and analytics technologies to:

  • Improve real-time sales and operations planning to produce a “Brand Oriented Value Chain”
  • Gain real-time asset management, leading to an “Asset Oriented Value Chain” and “Engineering Oriented Value Chain”
  • Improve supply chain management to produce a “Technology Oriented Value Chain”

According to all this, it should be clear that the benefits of being early adopters of big data and analytics technologies are too good to be ignored.

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2 comments on “Big Data & Analytics: Core to Next-Gen Manufacturing

    December 10, 2014

    Eventually developing nations will be on a cost par basis with today's developed nations and then the game will change from one of low cost manufacturing to value added services which requires a good grasp of “big data”

  2. Susan Fourtané
    December 12, 2014


    And then it's when it will become more interesting as well. 


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