The traditional industrial equipment (IE) business model is changing – and fast. In the relentless pursuit of new revenue streams to offset declining margins, and thanks to the advent of the Internet of Things (IoT), leaders in the field are finding new ways to deliver greater value to manufacturing customers.
“Traditional productivity levers have been widely exhausted,” said Dominik Wee, Munich-based leader of the Digital in Automotive & Industrial initiative at global consulting firm McKinsey. “But IoT is opening up a whole new avenue of revenue. Networking physical objects through embedded sensors, actuators and other devices that can collect or transmit information about the objects generates a huge amount of effective data. A number of leading-edge IE companies are leveraging this opportunity to offer pay-as-you-go and subscription-based services that can differentiate them from competitors.”
The shift is coming just in time to avert a profit recession for IE manufacturers, said Paul Boris, head of Manufacturing Industries at GE Digital. “Previously, IE manufacturers have managed to achieve gains of 4%-5% in productivity year on year, but today it’s down to 1% overall. Plants and machines are running more efficiently than ever, so we need to find alternative ways of reducing waste and cost across the entire value chain. For us this meant leveraging IoT.”
“THOSE IE COMPANIES THAT DON’T RETHINK THEIR BUSINESS MODELS ARE AT RISK OF JEOPARDIZING THEIR ENTIRE BUSINESS.”DOMINIK WEE
LEADER OF THE GLOBAL DIGITAL IN AUTOMOTIVE & INDUSTRIAL INITIATIVE, MCKINSEY
GE has invested US$1 billion to turn the IoT into a new revenue engine, installing sensors and developing software systems for its power turbines, jet engines, locomotives, medical equipment and other machines; connecting them to the cloud; and analyzing the resulting flow of data to improve machine productivity and reliability. “One billion dollars represents a big swing for GE,” Matthias Heilmann, chief digital officer of GE Oil & Gas Digital Solutions, said in a recent MIT Sloan Management Review article, “GE’s Big Bet on Data and Analytics.” “It signals this is real, this is our future.”
POWER BY THE HOUR
The mountains of data generated by GE’s new sensor networks are actually changing the company’s business from selling machinery to selling outcomes, including efficiency and uptime.
“By leveraging the same IoT technologies that have helped our customers reap rewards, we’re improving the performance of our own 400+ manufacturing factories,” Boris said. “For example, we’ve just signed a 10-year agreement with Texas-based drilling services company Diamond Offshore, which transfers full accountability for blowout-preventer (BOP) performance to GE Oil & Gas. In this ‘Pressure Control by the Hour’ model, Diamond Offshore will pay GE Oil & Gas only when the BOP is available. We’re applying these very same tools and technologies to enable the digital thread inside our plants.”
Japanese robotics and factory automation producer FANUC – which supplies robots to some of the world’s biggest manufacturers, including General Motors (GM), Apple and Samsung – is also moving toward an outcomes-based business. “We’re just beginning to identify the opportunities,” said Joseph Gazzarato, director of FANUC America’s Zero Downtime (ZDT) Service Center. “We are piloting our ZDT application to collect data from more than 6,000 of GM’s robots in 26 factories. We monitor these robots to see if there’s any abnormal wear that could lead to a failure.”
If a potential failure is identified, Gazzarato said, “We send parts with support to address the issue before any downtime occurs.”
ZDT has already proven its worth. “We’ve been 100% successful in detecting faults,” Gazzarato said. “In one truck plant in particular, we prevented an outage that could have taken four hours to resolve. When you consider that a single minute of factory downtime costs GM up to US$20,000, then you begin to understand the ramifications.”
Global bearing manufacturer SKF, which is headquartered in Gothenburg, Sweden, is also reaping the rewards of an outcomes-based approach. “SKF technologies currently monitor over 1 million assets around the world, many remotely,” said John Schmidt, SKF’s president for industrial sales in the Americas. “We understand the complex language of the bearing and – since the bearing is at the heart of the machine – this can tell us the dynamic health of our customers’ machinery. Every customer is individual, so we offer a variety of ways to work with SKF. This ranges from simple product transactions and traditional service models to performance-based contracts.”
Andy Neely, head of the Institute for Manufacturing at the University of Cambridge (UK), believes that programs like those underway at GE, FANUC and SKF represent a fundamental transformation in how the IE industry defines its mission.
“There’s a noticeable shift from delivering products to solutions, outputs to outcomes, and transactions to relationships,” Neely said. “It’s a win-win scenario – IE providers get closer to their customers, achieve greater loyalty and increase revenue, and manufacturing customers experience better value for their money, greater uptime and improved efficiency.”
For IE organizations that have yet to make the IoT leap, however, expert observers believe the outlook may be bleak. Douglas Bellin, global lead for the Manufacturing and Energy industries at Cisco, observed in a recent blog post, for example, that “71% of manufacturers say IoT will have a significant impact or some impact on their business over the next five years…Yet, 24% have no companywide understanding of IoT. There’s a significant knowledge gap in how to best plan for and capitalize on these technologies.”
“PLANTS AND MACHINES ARE RUNNING MORE EFFICIENTLY THAN EVER, SO WE NEED TO FIND ALTERNATIVE WAYS OF REDUCING WASTE AND COST ACROSS THE ENTIRE VALUE CHAIN. FOR US THIS MEANT LEVERAGING IOT.”PAUL BORIS
HEAD OF MANUFACTURING INDUSTRIES, GE DIGITAL
GE’s Boris said the lag is understandable, however. “There are undeniable challenges for those starting out on this path,” he said. “What’s key is to think carefully about which data paths to unlock first. In a manufacturing value chain there are so many small pieces of data that determine the true performance of an asset – it’s important to avoid the temptation to boil the ocean.”
What’s important, Wee said, is to get started. “The opportunity is huge, but there is a lot of uncertainty for companies, as there is with any emerging trend,” he said. “What’s clear is that those IE companies that don’t rethink their business models are at risk of jeopardizing their entire business.” ◆
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