Is the Industrial Internet of Things (IIoT) just the latest Y2K, or is there real business value? Analysis by LNS Research shows potential for great returns on investment, but it takes commitment. “It’s starting to happen, but there’s still a lot of room for early adopters to gain competitive advantage, providing they’re willing to buy in and get started,” said Matt Littlefield, president and principal analyst, LNS Research, in his keynote presentation at Rockwell Automation TechED this week in Orlando.
LNS Research focuses on the industrial space using a social model: Companies that participate by sharing information gain access to research results. Current council member companies number in the hundreds and are about 60/40 discrete/process, with company size and location demographics representative of global industry as a whole.
LNS’ recent “Metrics that Matter” study explored their level of understanding and participation in smart industry initiatives such as Industry 4.0 and Smart Manufacturing, as well as their results from any implementations of IIoT technology.
It takes a framework
Mature companies – those that have an effective approach to harnessing IIoT – implement technology on multiple levels, using strategic objectives to drive operational excellence, operational architecture, business case development and selection of solutions. Each level involves different technologies and expertise. Some suppliers might promise a one-stop, integrated solution, but “Companies that take an ecosystem approach, using a set of partners that address individual needs, will be most successful,” Littlefield said.
While the vast majority of companies are not mature when it comes to IIoT, “over the past year we’ve seen a dramatic reduction in companies that don’t know what it is and how it can help their businesses, with the number that say they’re not going to adopt it dropping from one-third to one-quarter,” Littlefield said.
The number of companies “in deep implementation” is rising, but only 13% are “enthusiasts” and 22% are “visionaries,” leaving two-thirds still skeptical or waiting.
The key is to find an application where IIoT technology will provide rapid return on investment (ROI), and expand on that experience. Littlefield pointed out that operational excellence is built on five pillars: productivity, asset performance management, quality, energy efficiency, and environment/health/safety (EHS). “Building out that foundation is critical, and if a pillar starts breaking, the whole system becomes unstable,” he said. Those pillars are often where early adopters have found their first opportunities.
At the enterprise level, ERP, MES, PLM and supply chain applications often involve strong analytics, but “no connection to the things,” Littlefield said. Look for opportunities where it will pay to bring in data.
Got big data?
To qualify as “big,” data must have velocity, volume and variety (variety means it is unstructured). Plants typically quickly generate lots of structured data, but, “The industrial sector has typically lacked variety, so it’s not big data,” Littlefield said. In contrast, “The consumer world is all over unstructured data,” he said, which can offer breakthrough opportunities for manufacturers.
Big data calls for analytics, which are common at the enterprise level. “Many companies are doing analytics, but only 14% apply them to manufacturing data,” Littlefield said. “Many of the rest don’t think they have a problem yet, but they will be surprised by their competitors.”
Powerful analytics must be adapted and tailored to be used for operations. “When we did statistical process control, we didn’t put statisticians in the plant,” Littlefield said. Like SPC, “We have to put analytics in a form that manufacturing can trust and use.”
Build the business case
“The biggest challenges to IIoT implementation are funding and building a business case, not security or executive support,” Littlefield said. “It’s difficult to predict the benefit without having the tools, and difficult to get the tools without proving the benefit.”
Surveyed adopters show their top four current opportunities are “what you’d expect,” Littlefield said: remote monitoring, energy savings, predictive maintenance/reliability, and quality. But a year from today, they expect two of those top four to include “business model transformation and material optimization – not what you’d expect,” he said.
Mature companies that have processes in place for adopting new technologies and ways of doing business may be able to go straight to “full smart manufacturing,” Littlefield said. “But a less mature company can start in a department, such as quality, to prove the concept and be sure it’s ready to move into that big value application. Map your journey. Use metrics to show results.”
LNS Research reports show that IIoT implementations can pay. “Don’t anticipate step-change performance gains, but many companies are outperforming the typical 1% to 2% yearly performance improvement,” Littlefield said.
Get started by instituting a digital transformation network to allow data to flow easily throughout the organization. Then deploy IIoT-enabled big data architecture. Build a business case and gain competitive advantage, and then justify more advanced analytics to achieve strategic objectives.
“If you aren’t collecting the data yet, you’re behind the curve,” Littlefield said. “Use IIoT to solve today’s problems, and be ready for tomorrow’s.”