By Patricia Panchak
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Download the slides from the presentation at the 2018 North American Conference
Attendees of the MESA North American Conference got a preview of results from the latest “Analytics That Matter” survey. Conducted by MESA International in collaboration with LNS Research, the bi-annual study was originally designed over a decade ago to identify “Metrics that Matter,” but evolved in the past few years to explore the use of new technology advancements around the Internet of Things (IIoT), Cloud, Big Data Analytics, and Mobility.
“Our focus now is beyond just KPIs and metrics, beyond the four walls of the plant,” said Chris Monchinski, Chair of MESA’s Analytics Working Group and VP Manufacturing Intelligence at Automated Control Concepts, Inc., Neptune, New Jersey, introducing the presentation. “Analytics and Big Data is more than just revving up our dashboards. It’s about looking at all sorts of streams of data, different types of data, and trying to glean new insight out of them.”
With the research, Monchinski said, one of the big ideas the Working Group is tackling is “analytics at scale.” That is, “How do I turn the analytics engine loose and use it at the enterprise level. How do I scale it up? What architectures do I use to do this? What is the right way to do this?”
Why is this important? “We are on a journey,” he said. “Thirty years ago we lived in a data-assisted world, where we would go and get data, interpret that data and make decisions about it.”
“We are now in a data dependent world: When electronics and computer systems no longer work, we can’t do our jobs. The line stops, production stops.”
“In the future, we’re going to be data immersed. We’re going to be surrounded by data and interacting with it.”
One of the most important goals of the research, according to Monchinski, is to evaluate and develop guidance by creating maturity models that allow manufacturers to test themselves against their peers, to see where they are on this digital transformation journey. It also seeks to provide guidance about how to start that journey and how to manage success along the way.
A few “surprising” results
Among the results shared in the presentation by Andrew Hughes, Principal Analyst at LNS Research, Cambridge, Massachusetts, were a series that explored the adoption of digital technologies by companies that have successfully implemented traditional continuous improvement practices, such as lean or six sigma.
“When it comes to adding digital capabilities to those traditional programs, there’s a huge resistance,” Hughes said.
Still, the small group of respondents who had applied digital capabilities to their continuous improvement program, “were much, much more likely to be implementing predictive and prescriptive analytics,” Hughes said.
Similarly, people who were doing digital continuous improvement were much more likely to be processing in the public and private cloud and on the edge. “That was a fairly dramatic finding,” Hughes added, “and one everyone should be taking home and saying ‘how can I start putting some digital technology behind my very traditional programs, which have been fantastic and successful.’”
Simply looking at the impact of digital continuous improvement on improvements in metrics, the research found “again, across the board, if we used digital continuous improvement, we had a bigger improvement in the metrics than before,” Hughes said, adding that manufacturers that combine digital technologies with traditional CI practices “probably also started from a better position.” A deeper dive into the data is required to see if that’s the case, he added.