The Industrial Internet of Things (IIoT) is a name for the Internet of Things as it is used across several industries. However, just like the Internet of Things in general and the Consumer Internet of Things, it covers many use cases, industries and applications.
The Industrial Internet of Things is defined as ‘machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes” (see infographic at the bottom).
Among the often mentioned industries in IIoT are manufacturing, aviation, utilities and energy, oil and gas, logistics, transportation and more (see below). The Industrial Internet of Things is the biggest and most important part of the Internet of Things now but consumer applications will catch up, probably starting 2018. Some data, evolutions, benefits and challenges regarding industrial IoT.
Industry 4.0 and the Industrial Internet of Things
Initially the main purpose of IIoT was to automate, save costs and optimize but today the focus is more and more on innovation too.
The Industrial Internet of Things enables industries to rethink business models. Generating actionable information and knowledge from IIoT devices, for instance, enables the creation of a data sharing ecosystem with new revenue streams and partnerships.
The Industrial Internet of Things is often used in the context of Industry 4.0, which is the term that describes a new industrial revolution with a focus on automation, innovation and data. On top of IIoT, Industry 4.0 also is about other technologies; which are related with it.
Examples include robotics, cloud computing but also the evolutions in operational technology (OT). In the Industrial Internet of Things, IT and OT need and meet each other. Industry 4.0 further refers to cyber-physical production systems (CPPS) and typical embeds the so-called third platform technologies and accelerators of the DX economy.
Industrial Internet of Things use cases
Despite the link with factories, manufacturing and heavy industries like mining, , aviation, oil and gas, defense, power and electricity and energy overall, the IIoT is often used to describe most Internet of Things applications outside of the Consumer Internet of Things.
So it is also about industries such as agriculture, connected logistics, finance, the government sector (including smart cities), public transport, utility firms, healthcare (hospitals) and others.
Below are a few typical IIoT use cases and business contexts.
- Smart factory applications and smart warehousing.
- Smart metering and monitoring.
- Smart environment solutions.
- Smart city applications (parking, traffic, waste management,…)
- Smart farming and livestock monitoring.
- Security systems
- Energy consumption optimization
- Industrial heating, ventilation, and air conditioning
- Asset tracking and smart logistics.
- Ozone, gas and temperature monitoring in industrial environments.
- Safety and health (conditions) monitoring of workers.
- Smart maintenance and equipment management.
The Industrial Internet of Things market: size, growth and impact on economy
The market opportunity of the IIoT is big. According to IndustryARC research (June 2016), the industrial IoT market is estimated to reach $123.89 Billion by 2021 at a high CAGR, as we cover in our Industrial Internet of Things market state and outlook 2016-2017. In the graphic below you can also see some forecasts by Morgan Stanley, data on the impact of IIoT on the global economy by Accenture and another forecast from Research and Markets. Leaders in the IIoT space, such as GE, also have impressive forecasts but of course it all depends on what you exactly measure and how you define IIoT.
Industrial Internet of Things adoption barriers: the major challenges
Although the Industrial Internet of Things is poised to grow significantly, challenges remain. The infographic by Visual Capitalist at the bottom of this article shows a few, as does research by Morgan Stanley and others. An overview of IIoT challenges as perceived by executives.
Data integration challenges (and data is the key of the IoT).
Industrial data is complicated for the reasons mentioned in the infographic (based upon IDC 2016 data), of which most also are among the (big) data challenges of our times.
Think about the variety of data source types, big data volumes (certainly in ‘heavy’ industrial applications), varied date frequency and complex data relations. The answer, just like in the big data ‘chaos’ picture overall: intelligent data systems.
Data integration is the number one barrier according to the research with 64 percent of respondents. It’s the eternal challenge of moving from data to business value, which becomes clear in the IIoT context. However, data and more specifically insights and knowledge in ecosystems of sharing are where the future revenue opportunities reside.
Lack of skills (and access to skills)
Another major reason why companies are not ready for the Industrial Internet of Things according to the survey is a lack of skills.
Limited access to the right skills and expertise is a problem for 36 percent of respondents. This issue of lacking skills is not just one of data integration but also one of other skills, which are needed for the IIoT.
A lack of skilled workers also was mentioned in the Morgan Stanley-Automation World Industrial Automation Survey, where 24 percent of respondents cited a lack of skilled workers. There is a lack of highly specific skills in general but at the same time it might also deem necessary to look more ‘outside’ to get access to the right skills. If there is one thing that is clear in this age of digital transformation and of the Industrial Internet of Things, it’s that no organization can do it all alone and networks, ecosystems and platforms of partners are extremely crucial to succeed.
Cybersecurity and data security
By far the major challenge for executives in the survey by Morgan Stanley and Automation World magazine, was cybersecurity and data security.
In fact, when Morgan Stanley posted some of its findings in April 2016, it said that data security was even more of a growing concern for organizations which rely on universal connectivity and that’s of course typical for the Internet of Things which in industrial applications often needs a mix of IoT connectivity solutions, depending on the use case.
It’s why companies who are active in the Industrial Internet of Things as service providers offer hybrid IoT connectivity solutions for industrial applications, ranging from cellular and low power wide area networks to industrial connectivity solutions, fixed and beyond. Important to note: cybersecurity and data security came out as the first IIoT adoption challenge in the Morgan Stanley research, before the end 2016 major IoT security issues and cyberattacks, even if those were not all using the types of devices and connectivity one thinks of in an IIoT context. We’ve tackled these Internet of Things security priorities previously.
Other IIoT adoption barriers
According to the mentioned survey by Morgan Stanley a lack of standardization is also a concern and there is more.
The top 5 of challenges to IIoT adoption, according to the survey, are, respectively, 1) cybersecurity (46 percent), 2) lack of standardization (35 percent), 3) the legacy-installed base (34 percent), 4) significant upfront investments (30 percent) and 5) the mentioned lack of skilled workers (24 percent).
Data integrity ended sixth (23 percent) as the illustration below indicates. Several of these challenges are reported by others too and seem universal.
IIoT adoption: the driving benefits of the Industrial Internet of Things
The main drivers of Industrial Internet of Things adoption, according to research by Morgan Stanley are:
- Improving operational efficiency.
- Improving productivity.
- Creating new business opportunities.
- Reducing downtime.
- Maximizing asset utilization.
5 steps to optimize Industrial Internet of Things projects
The challenges and barriers blocking the adoption of IIoT in manufacturing are pretty comparable to other IIoT industry segments.
And so is the advice which Dell gives to optimize IIoT benefits, mitigate risks and deploy projects (and do approach them as real projects with all the methodologies we know). Below is an overview with comments of the steps Dell advices you to take in an Industrial Internet of Things project.
As already mentioned, partnerships between OT and IT are crucial.
But of course also the business decision makers need to be involved. Go even further and forge partnerships and join forces with parties (internal and external) that might seem less obvious – as is recommended by IDC for any digital transformation project.
Clarify business outcomes and ROI
This sounds so obvious but as virtually all IoT experts will tell you all too often the business benefits are not clear enough.
Unclear business benefits are simply deadly for IIoT projects, as they are for others. An IIoT project starts with an idea, a need or an opportunity that is detected. But the business case needs to be clear.
This is very often the de facto approach in Internet of Things and Industrial Internet of Things projects.
Pilots, incremental growth, start small, fail, iterate, go bigger, scale, you know the approach and the benefits with which it comes (unless of course there is a reason to deploy fast if you have the right ecosystem in place).
While the business outcomes and partnerships with key stakeholders and others are obviously essential, security is at least as much.
Watch the IoT vendors you work with, look at security from an end-to-end perspective as there are so many components involved: from connectivity to devices and connected applications. Security by design and embedded security is a must. And as in all transformational projects, involve security early on.
Architect for analytics
It’s all about (big) data – and what you do with it: the intelligence, the action, the automation.
It’s about the data which you turn into insights, action and automation in your Industrial Internet of Things project and the need to use analytics in order to turn data into these insights, also for data you already might have. Remember DIKW, in IIoT too.
More about the IIoT
Presentation on IIoT by Accenture
The Industral Internet of Things infographic by Visual Capitalist with some of the research data we mentioned in this article.