InsightaaS: Louis Columbus’s A Passion for Research blog is one of the most interesting sources of information on the internet. In past months, I have highlighted several of his “roundup” posts – compiled perspectives on forecasts and estimates on the cloud computing industry, analytics/Big Data and business intelligence, 3D printing, even on available cloud courses – and found broad interest across our reader community. Today, we are featuring some of Columbus’s own analysis, on how Big Data can improve manufacturing industry results. Columbus begins the post by citing a McKinsey piece on the subject of Big Data in manufacturing, and then lists ten ways that he believes Big Data can and will improve manufacturing processes, outcomes and business results. While a number of these are specific to process manufacturing (which, being heavily depending on sensor information, is a natural fit for Big Data applications), other items in Columbus’s list apply equally to both process and discrete manufacturing, and it’s likely that any manufacturer would quickly see several areas where Big Data might yield business benefit.
This kind of analysis leads to a related question: what will happen to manufactures that are not early adopters of Big Data technology? Will they be eclipsed by more aggressive competitors? Then answer is likely to be ‘yes’, raising the stakes associated with effective IT management in these firms. Staff and management working within manufacturing businesses, and those that are linked with them in supply chain relationships (such as resource and logistics companies) would do well to look for evidence that the areas that Columbus highlights are being addressed in the IT strategies and deployments of their employers or partners.
McKinsey & Company recently published How Big Data Can Improve Manufacturing which provides insightful analysis of how big data and advanced analytics can streamline biopharmaceutical, chemical and discrete manufacturing.
The article highlights how manufacturers in process-based industries are using advanced analytics to increase yields and reduce costs. Manufacturers have an abundance of operational and shop floor data that is being used for tracking today. The McKinsey article shows through several examples how big data and advanced analytics applications and platforms can deliver operational insights as well.
The following graphic from the article illustrates how big data and advanced analytics are streamlining manufacturing value chains by finding the core determinants of process performance, and then taking action to continually improve them:
Big Data’s Impact on Manufacturing Is Growing
In addition to the examples provided in the McKinsey article, there are ten ways big data is revolutionizing manufacturing:
- Increasing the accuracy, quality and yield of biopharmaceutical production. It is common in biopharmaceutical production flows to monitor more than 200 variables to ensure the purity of the ingredients as well as the substances being made stay in compliance..