Harnessing Industrial IoT: Transforming Operational Technology for a Competitive Edge
This blog has been written by John Keele, Sales Director (MLEU) at Nasstar.
The global Industrial Internet of Things (IIoT) market has surged in the last five years, with projections to reach $1.8 trillion by 2028. This rapid growth reflects the increasing demand across industries like manufacturing, logistics, energy, and utilities to harness production data for competitive advantage.
For businesses, striking the right balance between over- and under-maintaining industrial equipment can lead to significant cost savings and uptime improvements. In sectors like water utilities, where environmental reporting is becoming more stringent, the shift from traditional to digital production offers not only commercial and human benefits but also a critical path to sustainability.
Embracing this next era of innovation requires strategic partnerships and an agile, fail-fast mindset to optimise digital transformation while ensuring long-term reliability. This article delves into the essential role of the 4th Industrial Revolution in driving success through cost control, efficiency, and optimisation.
Understanding IIoT
The Industrial Internet of Things (IIoT) describes networks of interconnected systems that monitor and control processes in a wide range of industries including manufacturing, healthcare, transportation, and utilities. IIoT relies on both wired and wireless networking and is designed to operate in challenging or remote environments such as factories and production facilities.
IIoT is a component of Operational Technology (OT), distinct from Information Technology (IT). Historically, these two technology estates were separate, but there’s an increasing need for interoperability and integration between the two.
Adoption of IIoT is a key consideration in any digital transformation strategy. Gaining insights from real-time data within production and delivery facilities or across the supply chain will drive improved safety, efficiency, and cost control. The affordability of processors and sensors from IIoT vendors has made this option ubiquitous when considering OT solutions, so its adoption is a significantly growing strategic focal point.
Strategic advantages of IIoT
The interconnection of production and operational systems is crucial for transforming industries and realising strategic benefits. By moving from siloed, manual processes to automation and data-driven insights, businesses can optimise production, minimise costs, and improve efficiency.
Modern businesses, like Amazon, aim to predict demand with high accuracy, ensuring the right amount of inventory is produced and delivered at the right time, fostering both profitability and sustainability. It is touted that “Amazon knows with 98% accuracy what you will buy 6 weeks ahead of you buying it.”
IIoT and OT systems play a key role in driving this transformation across industries, whether producing sustainable electricity or vehicles. For example, Nasstar has helped an energy producer predict component failure by combining production data with climate information, improving grid availability.
We also helped a global car manufacturer use vehicle telemetry to predict failures and refine component designs. Additionally, IIoT enables businesses to meet growing sustainability and safety reporting requirements efficiently, ensuring compliance without adding significant overhead.
Some of the key strategic advantages of IIoT include:
- Improved efficiency: Sensors can monitor equipment and processes to identify inefficiencies, which can be addressed quickly.
- Predictive maintenance: Wearable sensors can monitor equipment performance in real time to detect early signs of wear and tear and predict maintenance needs.
- Improved customer service: IIoT networks integrate customer experience and input, which can lead to more seamless shopping experiences.
- Quality control: IIoT-enabled quality control solutions can automatically and continuously monitor every stage of the production process.
- Supply chain management: IIoT can help reduce operational costs in the supply chain.
- Advanced analytics: By collecting and analysing large volumes of data, businesses can find areas for improvement and predict problems in production.
- Enhanced safety: IIoT can help keep equipment running safely and provide insights into productivity improvements.
- Better productivity: IIoT can enhance efficiency, productivity, and competitiveness.
Data-driven insights
With the proliferation of IIoT and the increased networking of OT systems, businesses face the challenge and opportunity of deriving insights and value from the data surfaced from production environments.
Conventionally, this data is aimed at a single informational use such as monitoring metrics and events, or consumption figures. But when combined with additional corporate data from applications like ERP and CRM, other internal data sources, and enriched with data from external sources, it’s possible to elicit insights of significant value, both operationally and commercially.
Examples of this include:
- Predictive maintenance to determine the optimal time to plan operational downtime.
- Demand and logistical mapping to determine what, where and when to produce, at what cost and thereby what margin can be added.
- What new business or product to pursue based on demand, current internal capacity and capability, and the likelihood of success based on historical performance.
All these applications exemplify the goals of digital transformation in making operational and production decisions based on current data, in real-time if required.
IIoT challenges
The adoption of what has become known as Industry 4.0, combining IIoT, AI, cloud computing, automation, and data analytics, is a challenge for many businesses. Legacy businesses face costs of re-tooling, re-skilling and organisational resistance combined with an uncertain ROI. However, it is anticipated that non-adoption will mean that such businesses will be eclipsed and replaced by those that do adapt or have been born during this era of industrial innovation.
That said, the end state of digital transformation and incorporating IIoT is also not without its challenges.
The engine of the transformed business is the creation, transmission, and interrogation of hugely increased volumes of data. This brings concerns of capacity and cost, increasing regulatory pressure on data usage and the continuous need to innovate to maintain competitive advantage.
Cyber security exploitation is a common concern with a magnified surface area. By placing more internet connected sensors and networking legacy OT systems to use their data outside the production line, the opportunities for compromise are hugely increased.
The original designs of OT systems allowed freedom of integration, interoperability, and access in a multitude of ways, but the expectation was that they would only operate in an air-gapped, factory-style environment. The advent of remote data processing, monitoring, and access requirements has required connection of these systems to the internet.
Furthermore, the requirement for data exchange with corporate systems like ERP has effectively exposed the whole corporate network, significantly increasing the security risk. The Hollywood scenario of hacking into a defence system via an IOT vending machine may be a little farfetched but it is based on reality.
These challenges are recognised by the industry, resulting in organisations having to innovate or die, while also mitigating for the increasing security threat. To support businesses with these challenges, security vendors like Fortinet and managed service providers like Nasstar, have developed propositions to reliably and securely facilitate digital transformation.
Implementing IIoT
The use of IIoT and its data is a key element in digital transformation strategies, but achieving full success requires additional technological advancements. A secure and reliable underlying network is essential, as is the ability to identify and address OT vulnerabilities, which are less mature in patching compared to IT systems. Security vendors can offer temporary patches while OT vendors work on their own updates. Similarly, solutions that isolate compromised parts of the network are crucial, particularly for critical infrastructure like hospitals or energy suppliers.
Equally important is a robust IT infrastructure, increasingly hosted in the public cloud, driven by the adoption of SaaS and other cloud solutions. For custom applications, leveraging data analytics and Generative AI is necessary to optimise interoperability between IIoT and OT systems.
A unified data fabric that integrates both internal and external sources enables the application of AI and data science, realising Industry 4.0 goals like Smart Factories, Cyber-Physical Systems, and Digital Twins. While the journey to full digital transformation can be challenging, it can be achieved in phases with a clear business case for each stage.
Future trends in IIoT
The adoption of IIoT and OT as part of digital strategies is becoming essential for businesses, although the pace varies across industries. Companies that embrace digital transformation often outperform those that do not, with the banking sector leading in digital adoption through mobile banking. This trend is becoming increasingly relevant across all industries.
Industry-specific trends in IIoT
In manufacturing, IIoT has demonstrated tangible improvements, such as a 5-15% increase in production line availability and up to a 40% reduction in energy consumption through data-driven insights.
In retail, businesses that have leveraged innovation in customer experience, targeted marketing, and inventory management have outpaced their competitors. Similarly, in healthcare, advancements in remote monitoring, diagnostics, and early disease detection are enhancing patient care and outcomes.
IoT-enabled smart energy grids are also optimising production and distribution, while agricultural sensors are improving sustainability by boosting yields and reducing waste. We expect to see more of these industry-specific benefits over the coming months and years.
An employment shift in automation and reskilling
It is also predicted that the use of data insights and AI will reduce jobs, and this is highly likely to be true in areas of repetitive work functions that can be automated. However, this will be offset in part by a skills shift that requires more technically advanced competencies.
Upskilling and reskilling initiatives will be essential for businesses to thrive. This may also reverse the trend of outsourcing to developing countries as the demand for low-cost manual labour moves to high-skill data science and technology competencies that favour proximity to technology hubs in America, China, and Europe.
Economic impacts and technological solutions
At a macro-economic level, there is a challenge to maintain growth in the face of finite natural resources and land use in a way that is sustainable for the future. Global population growth is slowing and is expected to peak then reduce within the next 25 to 50 years, resulting in reduced GDP growth through lower demand and output.
Nations with aging populations will see higher per capita spending on healthcare and pensions, reducing flows into the wider economy. The adoption of next generation technology and innovation offers higher economic output through productivity gains at a lower cost. Underlying growth is thereby increased by using technology to reduce cost, increase efficiency, and improve re-use and sustainability in all areas of the economy.
Regulations and security
The increased adoption of IIoT and digital strategies will come with business challenges and regulatory hurdles, particularly in data security, sovereignty, and protecting against cyber threats. The risk from malicious actors, including state-backed entities, cannot be overlooked. Therefore, businesses must approach digital transformation with a strong understanding of the associated risks and the necessary safeguards.
IIoT at Nasstar
At Nasstar, we help businesses with digital transformation road-mapping and realisation. We look at business-based outcomes that are aligned to KPIs and targets that have been set by the executive. We recognise there are differing levels of maturity and ambition, so we consult and deliver at each step from network security through application modernisation to data science and Gen AI adoption.
Our engagement model can be tactical to meet a known challenge such as OT security or to deliver an AI Bot for a single use case. Or it can be long term, designing and defining a coherent strategy with milestones to be delivered over many months or years.
Speak to our team today to find out more.
