In addition, IDCMI predicts that big data initiatives will remain one of the top priorities for the manufacturing sector in the foreseeable future.
However, when compared to other industries, manufacturers seem to be on the trailing edge of this development rather than the leading edge. That’s not surprising given the huge IT and factory-infrastructure investments that can be required to tap into the business-transformative power of seemingly infinite loads of data about manufacturing functions.
There are some manufacturers, such as Caterpillar, who are taking the plunge and leading the way. One example is Caterpillar. It’s “Cat Connect” network, for example, connects Caterpillar’s customers to dealers. “It monitors everything our machines are doing, so engineers can see whether it has a high exhaust gas temperature or is running low on oil—all the things the engineer needs to know to run that machine in his fleet more efficiently,” Chairman and CEO Doug Oberhelman told Chief Executive’s Smart Manufacturing Summit audience in May.
ADDRESSING THE CHALLENGES
The difficulty of tapping into big data is compounded in some processing environments where extreme variability is a fact of life even after lean techniques have been applied, McKinsey & Co. consultants say. So companies in these industries need a more granular approach to diagnosing and correcting process flaws—an approach provided by advanced analytics.