Manufacturers are increasingly relying on the advanced analytics made possible through big data to drive some of their most important decisions. In this high-tech era, use of analytics is essential for increasing productivity and efficiency without sacrificing quality. Analytics can also accelerate innovation. If you haven’t already used big data to accelerate innovation, your company may be left behind.
There are seven key areas where big data is making inroads in manufacturing:
For instance, using predictive analytics in testing may provide significant cost savings, but a single product could require hundreds or even thousands of tests. This number can be dramatically reduced through pattern recognition and analysis of big data. The analytics will determine the number and types of testing that are essential. Furthermore, sensor data analytics can identify and detect defects earlier, reducing the time and money spent on adjustments to processes and procedures.
Big data also identifies machinery that should be replaced and extends the life of equipment that is kept in good working order. Manufacturers can avoid sudden failures that might cripple a business without any warning.
However, to recognize sustained growth from BTO, a manufacturer must construct a platform to efficiently analyze customer behavior and sales data. Specifically, big data is added to project order volumes for each configuration and to determine profitability. Accordingly, manufacturers can incorporate changes in the supply chain that address problems and provide solutions.
Use of big data in daily activities leads toward growth opportunities, maximization of resources and potential cost savings. However, as is usually the case, you must have the right tools to do the job right.
These insights can help drive global decisions such as where to build factories, when certain work sites should be closed or relocated and when and how new products may be introduced into the marketplace. Big data makes the difficult questions easier to answer.
With greater visibility into supplier quality levels and other performance data, manufacturers are better able to assess, manage and negotiate risk management aspects. Because supplier needs are quantifiable, companies can make informed risk management decisions and develop appropriate strategies.
Big data analytics can boost manufacturing efficiency, help executives make smarter decisions and discover new ways to drive innovation moving forward. Those seeking a competitive edge will need to find ways to integrate and manage essential data to increase profits and improve operations.
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