Manufacturers Stop Flirting With IIoT

Image credit: iStockphoto/Eucalyptys

Manufacturers know that industrial internet of things (IIoT) can offer the transparency they sorely need.

It is why Accenture believes that IIoT “promises to be the most transformative industry revolution yet for manufacturers, changing the way they think about source allocation, production processes, material handling, and the workforce.”

But industrywide IIoT implementations are still few.

One argument is that the ROI picture wasn’t clear. Many saw it as for those with deep pockets who could refit their manufacturing plants. COVID-19 made that argument mute by highlighting how IIoT-ready supply chains withstood shocks.

McKinsey & Company, in its “A manufacturer’s guide to scaling Industrial IoT” report, notes that another reason is the heterogeneous IT landscape and legacy manufacturing applications that many manufacturers still use.

There are also other challenges: like the ongoing battle between ERP players and IIoT platform providers confusing manufacturers about which functions should support which applications. And then you’ve the governance question on who manages IIoT — IT or OT?

But the same consultants now see a mindset shift with manufacturers. IIoT is about to become mainstream.

Winds of IIoT change

For Robert Merlicek, chief technology officer for the Asia Pacific and Japan at TIBCO Software, the shift is a realization by manufacturers that they have little time to ponder challenges and wait for industrywide best practices.

This is because the global supply chain is under tremendous strain, partly due to the lockdowns, U.S.-China tension, and events like the Suez Canal obstruction. Another reason is that the supply-demand equation for some industries is becoming lopsided and impacting other unrelated sectors.

Take car manufacturers, for example. “The automobile industry is now looking at a huge loss because they don’t have the chips to manufacture. This happened because the chip manufacturers looked for new markets, like consumer electronics, during the lockdowns,” Merlicek explains.

It allowed them to release their inventory, diversify their revenue base, and create demand for semiconductor manufacturers. Meanwhile, car manufacturers who stalled during the global pandemic as demand slowed are now caught between a rock and a hard place as they cannot procure the chips to meet the demand. Hence, the predicted loss that KPMG says totals USD 100 billion.

“In the end, this is really about real-time visibility, which is becoming important for forward planning,” says Merlicek. It is also where IIoT analytics play a crucial role.

Creating a living supply chain

Manufacturers have constantly been fed the promise of real-time supply chain visibility. Yet, this level of visibility is still hard to achieve.

“I'll give you an analogy. If you get an Uber, the app tells you where your driver is and informs you when the driver is going to arrive. So why can't I see that with my supply chains?” says Merlicek.

He also thinks IIoT analytics will finally deliver on the visibility promise.

One reason is AI. “They give that visualization that allows supply chains to sense and respond to conditions. It’s almost like we’re talking about a supply chain nervous system,” explains Merlicek.  

Another is data virtualization. Manufacturers are moving away from data silos after facing operational challenges during the lockdowns. They are now allowing key decision-makers to access the data from all their systems by virtualizing them.

That’s why Merlicek thinks metadata management of supply chain data will be “huge in the future.” “It helps me understand my data interactions and data lineage across the broader supply chain,” he explains.

With IIoT offering a broader view, manufacturers can see unfolding risks with machine learning and respond quickly. “For example, if I can see changes in demands as my partners change their requirements, I can mitigate that,” says Merlicek.

In the past, getting such information was difficult and time-consuming. However, with the uptake of API management in the supply chains, more corporate data assets are now exposed to the different ecosystem partners. With IIoT online, it adds a real-time depth to supply chain visibility.

ESG will make IIoT mandatory

Analyzing IIoT data streams needs a lot of processing power. And in some instances, these data only matter for real-time operational decisions at manufacturing plants and not strategic decisions.

So, Merlicek sees edge-based computing as becoming essential for spurring IIoT deployments. It’s one reason why TIBCO Software developed the TIBCO Flogo Enterprise. It results from the work done under Project Flogo that deployed ultralight, event-driven microservices in serverless environments, containers, and IoT devices.  

“It provides you with agility at the edge. By leveraging data science on top of that information, we can change how we use IoT data,” says Merlicek.

This will matter as manufacturers face ESG (environmental, social, and corporate governance) compliance headwinds.

“So, if a consumer wants to know whether the goods are ethically sourced, we can now find out the information from the supply chain and ecosystem, right down to each supplier, mine, or farm,” says Merlicek.

Are manufacturers ready for this kind of visibility and scrutiny? At least, we know that it is no longer a technology question.

Winston Thomas is the editor-in-chief of CDOTrends, HR&DigitalTrends and DataOpsTrends. He is always curious about all things digital, including new digital business models, the widening impact of AI/ML, unproven singularity theories, proven data science success stories, lurking cybersecurity dangers, and reimagining the digital experience. You can reach him at [email protected].

Image credit: iStockphoto/Eucalyptys