Analysts McKinsey said that harnessing the full power of advanced analytics requires not only new technology, but a new mindset among workers and managers.
Jamie Miller, senior vice president of GE and president and CEO of GE Transportation, said that the “Industrial Internet” is already here today and that digitization is increasingly becoming more integral to their products. The company’s “Brilliant Machines” campaign highlights how its new machines use sensors and software to understand processes and improve performance.
IoT technology also is making it easier than ever to generate and track information on everything from individual machines to performance to process efficiency. For example, sensors are becoming more cost-effective and offer reliable data transmission with powerful control software. Affordable storage options also make it easy to aggregate and collect large amounts of data and process it in real time.
But McKinsey says technology is “only one part of the equation,” and that to really achieve a financial impact from analytics, manufacturers must also consider the human element. They must attract and retain the skilled talent across the entire organization to make new methods and solutions a part of the day-to-day routine. This analytics-based transformation must be established in processes that carry from the shop-floor operators to process engineers and managers.
“This course requires manufacturers to develop the management capabilities and mind-sets that can mobilize the entire organization to harness the new analytics technology,” said McKinsey.
To succeed, manufacturers will need to deploy analytics hundreds of times across their organization while ensuring consistency, quality and the development of a continuous improvement cycle. While outside companies can help establish the framework and implementation, manufacturers must implement the practices and have experts across the organization to manage it all.
McKinsey noted that manufactures also will need IT expertise to aggregate data from platforms, as well as process engineers who can collaborate with data-analytics specialists to create models that consider how local plants are set up and how their processes behave. Employees will also need to be trained to work with the new technology on a daily basis and act correctly on its recommendations. This also may require changes in management as new information can challenge existing knowledge and dispositions.
McKinsey reported that heavy manufacturers and their workforces will need to embrace a “new mindset” centered around data-driven decision making and the ability to analyze and apply new insights to draw the right conclusions. “More real-time information ultimately changes how decisions are made and leads to an agile way of operating,” McKinsey said.