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5 Cost Challenges Affecting IIoT Adoption

Oct. 30, 2019
Installing equipment is not enough: the Industrial Internet of Things requires manufacturers to focus on compatibility, security, ROI, implementation plans, and data applications.

The Industrial Internet of Things (IIoT) encompasses the connected devices implemented at the enterprise level. Machine shops, or any other industrial outlets, can gain new insights with gadgets like connected sensors and data analysis interfaces when they invest in IIoT equipment. Moreover, the gathered data can help these businesses to avoid equipment downtime and other pitfalls.

And yet, despite these well discussed advantages, many industrial businesses encounter cost challenges when they set out to incorporate IIoT technologies and practices into their processes. Here are five of those challenges, plus how to solve them.

1.Equipment incompatibility — When a business decides to adopt IIoT technology there may be a belief that it cannot do that without replacing all its legacy equipment. Coming to that realization may bring discouragement to its representatives that they conclude that they cannot afford the IIoT investment.

However, an increasing number of IIoT-focused businesses offer "wrap and extend" solutions that retrofit old equipment to make it compatible with IIoT technology. Those options won't work for every piece of machinery, but enterprises should investigate such possibilities instead of hastily assuming that its legacy equipment will prevent IIoT adoption.

2. No network security— A 2018 IIoT Security report by SANS showed respondents cited a variety of challenges when securing their networks after starting to use connected devices. One of the top concerns mentioned was that security would not be a prime consideration for the chosen products. Moreover, respondents feared an inability to keep IIoT products adequately patched against vulnerabilities.

An even more worrisome finding from that research showed that the majority of respondents were not sure if their organizations had established budgets for IIoT security. Other issues may emerge if members of a company's IT team have trouble getting the attention of decision-making executives at their organizations.

Sometimes, those people at the topmost levels of an organization focus only on the perceived benefits, and do not consider the costs that are necessary for keeping the IIoT devices and the respective systems free from preventable cybersecurity risks. When those in charge of setting a company's budget evaluate the costs of IIoT technology, they must not forget to prioritize the expenses associated with security.

3. Determining expected ROI — Some executives may be set in their ways when faced with technology adoption. Or, they frequently have hesitations regarding the return on investment (ROI) for IIoT tech.

Bain & Company published a report on challenges respondents experienced when attempting to scale their IIoT investments. The findings indicated that about 25% of the respondents in 2018 mentioned the IIoT's unclear ROI as an issue.

If a business’s representatives want to invest in the IIoT but get pushback from the people who oversee the enterprise's financials, one of the best responses is to admit that seeing a strong ROI will not happen immediately.

It's also helpful if outside parties weigh in about whether adding IIoT tech to an industrial operation would help the bottom line. For example, an energy consultant could give an informed perspective about how the IIoT ties into the enterprise's energy efficiency goals. When the Bain & Company researched which IIoT use cases that appealed to customers most, energy management was a high-ranking option.

4. Implementation expenses — Sometimes when companies decide they want to begin using IIoT technology, they don't get as far into their projects as expected. That's because ultimately it is too expensive for businesses to reach the implementation stage. Microsoft recently polled 3,000 decision-makers at enterprises currently using technology from the Internet of Things (IoT) or intending to do it. The conclusions indicated that 30% of projects fail in the proof-of-concept stage due to implementation seeming too expensive, or because the organizations cannot see the bottom-line benefits.

But, another interesting finding pointed to a different reason that companies may decide that IIoT technology costs too much.

Microsoft's data showed that 38% of adopters mentioned complexity and technical challenges regarding their use of IoT tech. Also, nearly half of respondents (47%) believed there were not enough skilled workers to assist with their IoT adoption. Half of those polled brought up how the lack of training and talent posed challenges, too.

The IIoT is among the tech areas suffering from a talent shortage. Besides the more generalized qualms that companies may have about their IIoT implementation, it's understandable if the costs become even higher once enterprises discover they cannot hire the necessary expertise. Not having experienced employees to facilitate an IIoT adoption could, indeed, make expenses rise too much.

Getting around these problems requires two solutions. First, businesses need to adequately research the costs of projects and ensure they can bear the expenses before getting too deep into things. Also, enterprises must come up with strategic and effective ways to tap into the talent required to assist with the implementation and adoption. These steps will not be easy, but going through them should prevent cost-related surprises.

5. Failing to apply data — Another cost-related concern with the IIoT is that businesses may invest in data-gathering equipment to a small extent, but then fail to tap into that data to learn how to make the organization more profitable. With that outcome, IIoT adoption may never reach its full potential at a company because the executives believe the investment is not paying off as expected.

So, the lack of positive outcomes is not due to a problem with the IIoT equipment, but a fault of users who are not applying the data correctly to help the company's profits. According to a Frost & Sullivan study, the enterprises polled saw an average 12.1% improvement on their overall business metrics after launching IoT initiatives.

Relatedly, a publication from McKinsey Digital included a case study about a metals manufacturer. During its IIoT deployment, the enterprise connected three sensors to rolling mills to capture data from the machines. The executives were happy about getting the new system running in three weeks, but it became apparent that frontline employees didn't use the information generated by the equipment.

Once managers realized this they changed several production floor processes, including altering the inspection routes and introducing daily huddles for team members. These practical and behavioral alterations led to a 50% increase in equipment efficiency, saving hundreds of millions of dollars’ worth of planned capital expenditures.

The lesson here is that IIoT adoption will quickly get perceived as too costly if companies do not take direct action to use the information provided by IIoT equipment. That assumption could hinder the wider IIoT implementation, especially if business leaders give up too early. Overcoming this cost challenge means taking a long-term look at how to benefit from the data. It's not enough to merely install the equipment.

This list shows that IIoT technology can and does present obstacles related to cost. However, manufacturers should not see these requirements as barriers. They can get past the challenges by making careful plans that target the difficulties and thoughtfully address them.
Kayla Matthews writes about the IoT, IIoT, automation and smart technologies for publications like InformationWeek, Manufacturing.net, Robotiq others. To read more from Kayla, follow her personal tech blog, Productivity Bytes.

About the Author

Kayla Matthews | Freelance Journalist

Kayla Matthews writes about the IoT, IIoT, automation and smart technologies at her personal tech blog, Productivity Bytes, and for publications including InformationWeek, Manufacturing.net, Robotiq, and others.

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