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The Internet of Things (IoT):
A practical guide 

The Internet of Things (IoT) is a network of physical devices, machines and other objects that use sensors and software to collect data and exchange it over the internet, enabling remote monitoring and control.

The IoT architecture starts with an IoT device—a piece of technology that supports internet connectivity and is equipped with a sensor or means of measurement. An IoT device transmits sensor data automatically, without human or manual interruption, to an IoT platform. The IoT platform processes the data and takes actions that can include updating systems across the enterprise, providing insights to users, or triggering automated actions. Business and IT users can use the IoT platform to maintain their IoT ecosystem, manage devices, apply analytics, and build new services based on IoT insights. Put simply, IoT enables things such as wind turbines, paint robots or cars to communicate and give real-time updates on their status.

How does IoT work?

Four key components make up the IoT system architecture: IoT devices, connectivity, an IoT platform, and the application layer. Let’s look at each of these more closely to understand their role in the environment.
High-level overview of IoT architecture
First, there are IoT devices.

These physical devices can be practically any object that contains a way to measure and transmit information. Common IoT devices include sensors, cameras and actuators that measure data relating to the function of a device such as temperature, velocity, pressure, vibration or location. Devices communicate this information to an IoT platform.

Second, there is connectivity.

Network protocols are used to standardize the format of information flowing from IoT devices to the platform, whether the platform is located on an on-premises server or, more likely, on the cloud. Common IoT network protocols for commercial applications include LoRaWAN (LoRa Wide Area Network) and lightweight M2M (LWM2M).

The third component is the IoT platform.

An IoT platform is the central hub that connects everything in your IoT ecosystem. The IoT platform connects IoT devices to the internet, enables the management and analysis of data, and provides the necessary tools to build and deploy IoT applications. The general capabilities of the IoT platform include: 

  • Device management – Monitor and govern device connectivity, communication, data storage and maintenance.
  • Data management – Collect, store, and manage data from IoT devices, and provide access to that data for further analysis and processing.
  • Integration – Integrate device data with enterprise apps, cloud apps, big data apps, data lakes and third-party ecosystems. Assemble integration flows and start automated actions based on IoT events.
  • Analytics – While IoT data is valuable, IoT analytics applies context to IoT data to reveal useful information to make impactful decisions. Analytics allows you to identify patterns, act in the moment, learn from the past and forecast future behavior.
  • Application development – The IoT platform provides an application programming interface (API) and software development kit (SDK) to enable development of new applications that can interact with and control IoT devices.
  • Security – IoT data includes proprietary information to, and control over, sensitive systems. Unauthorized access can cause devastating equipment failure or costly downtime. IoT platforms also include security measures to protect against unauthorized access and malicious attacks on the devices and data. This includes the use of encryption, secure communication protocols, and authentication mechanisms.
Finally, the application layer.

This layer comprises the applications and software a company uses to run its business, such as ERP, CRM and enterprise SaaS applications. IoT data integration can drive updates to these applications to alert users and trigger actions. The users of these applications often span many different departments, from operations to sales to HR.

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Common IoT use cases

IoT provides a foundation to build smart, connected devices that enable a detailed understanding of how your assets, processes, business and customers operate. The applications of IoT are versatile—practically every business model and industry can earn substantial benefits with the right approach.

For example, retailers can use IoT for smart ordering to prevent waste and overstock. They can use shopper analytics to optimize store layouts for better sales or send notifications through the app to users near a store location.

Telecoms can remotely monitor equipment and predict maintenance to prevent technical issues or unexpected downtime for customers who depend on their communication services.

Logistics companies can keep track of their fleet, inventory and personnel to improve efficiency and reduce loss of goods due to late deliveries.

Healthcare devices that incorporate IoT technology can help patients and their providers monitor chronic conditions in real time, so patients live with more independence and less worry.

Energy companies can accelerate efficiency and sustainability with IoT initiatives that connect every “thing", from hydroelectric turbines to wind farms and water meters. Sensor-embedded infrastructure enables them to detect changes in equipment in real time to prevent outages, make workplaces safer and avoid rework.

Utilities can monitor energy consumption in real time and distribute energy or other products where they’re needed, when they’re needed, to enhance smart grid initiative and reduce outages.

Manufacturers can enhance process efficiency, reduce downtime and gain insights into equipment performance based on sensor data from connected equipment.

These examples are just scratching the surface of the ways organizations across industries can leverage the benefits of IoT insights.

What is IIoT?

In this era of manufacturing, operational efficiency and data go hand-in-hand. This is where IIoT comes into play.

The Industrial Internet of Things (IIoT) refers to the application of IoT technology in the industrial setting. The use cases, capabilities and requirements of IIoT are generally more advanced than the application of IoT in other industries due to the extensive network of connected devices and the volume of data involved.

IIoT enables manufacturers to operate better using real-time data analytics and monitoring to keep agile, informed and in control. And driving IIoT is the equipment makers—those who shift from making “traditional products” to creating “smart products.”

Smart, connected products enable manufacturers to deliver new innovative solutions to customers, with the ability to transform business models and offer Equipment-as-a-Service to build even greater value.

According to the IoT Analytics Equipment as a Service Market Report, the size of the Equipment-as-a-Service market is expected to be $131 billion by 2025, a 6x increase from 2019. Soon enough, accelerating to an EaaS business model won’t be about staying ahead of the competition; it’ll be about staying in the competition. 95% of McKinsey Machinery & Industrial Automation survey respondents expect to change their business models to be successful in the future.

The difference between IoT and IIoT

IoT creates a wide range of opportunities for new use cases across both consumer and business environments. Industrial IoT (IIoT) is a subset of IoT, with solutions tailored for industrial applications such as manufacturing and energy management.

Because IIoT focuses on the management of critical infrastructure and production assets, there are critical factors that separate IIoT applications from general IoT. These critical features that separate IIoT from consumer grade IoT, and general-purpose business IoT, include:

  • Interoperability
    The freedom to design a new application from the ground up can make it easier to avoid certain challenges, but this is not a luxury that IIoT developers are afforded. Industrial IoT applications must integrate in environments with a wide range of OT assets and devices, legacy enterprise IT solutions, and communication protocols. Given the tradeoff between the capabilities of cloud computing tools and the cost of transmitting and storing data on the cloud, IIoT solutions also need to provide a single UX for edge, hybrid, and cloud deployments.

  • Scalability
    While IoT use cases for an individual consumer may integrate data from dozens of endpoints and commercial deployments may involve hundreds or thousands, industrial IoT deployments can scale orders of magnitude beyond. IIoT deployments frequently require the integration of tens of thousands of data points and can involve incorporating data from different locations across the globe. One of the most important aspects of industrial IoT solutions is their ability to scale vertically and horizontally across an enterprise.

  • Adaptability
    The programming and reconfiguration of industrial machines is frequently performed. This can be done remotely, on site or in the field. Industrial IoT solutions supporting industrial and manufacturing processes must provide reliable flexibility and adaptability.

    IoT solutions operating in industrial environments must be serviceable in order to sustain the levels of performance required. This can extend from swapping out sensors and updating firmware to configuring gateways and servers—the ability to maintain industrial IoT solutions over their entire lifecycle is an essential requirement.

  • Reliability
    Industrial products are often designed to operate for decades before a scale replacement is performed. With strict requirements, such operating in harsh environments—sometimes subject to extreme cold, heat, high vibration, pressure and hazardous conditions—the IIoT applications must be reliable for equipment to maintain high availability.

    Industrial operations also require higher levels of accuracy. Automated, high-speed machinery is synchronized to a matter of milliseconds. Therefore, quality must be assured for such systems. Any small variation in the operation of such high-volume manufacturing processes must be corrected right away. Deviations or lag can result in poor efficiency or downtime, which can result in considerable amount of lost revenue.

  • Security
    Every kind of IoT solution requires security, but industrial IoT solutions require more robust measures. Resolving security on a merely superficial level can have a disastrous outcome for a high-volume manufacturing process, resulting in lost production costing huge amounts of money. Poor control processes can also put the system into an unstable and unsafe condition. IIoT solutions incorporate sophisticated security measures including secure and resilient system architectures, specialized chipsets, encryption and authentication threat detection, and secure management processes.
Debunking IIoT myths

Business benefits of IIoT

Manufacturers like using smart, connected equipment because the benefits can be felt along their entire production process. Insights can help them reduce downtime and improve efficiency, with benefits starting at a single type of machine and scaling to the entire production line. And equipment providers also see many opportunities to enhance their business by offering smart, connected products.

Manufacturers often look for the following benefits from IIoT:

Reduce downtime

The average automotive manufacturer loses $22,000 per minute when the production line stops, and overall, unplanned downtime costs industrial manufacturers as much as $50 billion a year, according to a survey of automotive industry executives. Operators use IIoT to fight this costly, unexpected downtime with 24/7 insight into how equipment is performing and capabilities to react immediately to unforeseen conditions. IIoT lets you predict and plan for maintenance, detect operational problems before they arise, learn precisely why an incident happened and automate actions on the asset when specific parameters are met—all of which promise more uptime and better performance.

Enhance sustainability

In Transforma Insights’ Sustainability Report, 95% of business leaders attributed electricity and fuel savings to the deployment of IoT-enabled applications. IIoT enables transparency into manufacturing energy and material consumption, offering you the expertise to make and take more sustainable and smarter decisions. Energy savings, and a proportional reduction in an organization’s carbon footprint, are enabled through the deployment of traditional IIoT use cases: remote monitoring, smart field services, and performance management.

Improve quality of output

With advanced insights, automation and real-time control over of your production lines, IIoT ensures every product leaving your line is consistent, reducing the number of defective products.

Increase safety

When you can monitor and manage equipment remotely, you’ll be the first to know if something is wrong with your equipment. And, you’ll limit the number of trips employees take to the field, which is especially crucial in hazardous environments.


Equipment providers primarily focus on the following benefits from offering smart, connected equipment:

Differentiate products through new features and capabilities

Providers can create new, resilient revenue streams through digital services and develop value-adding features faster, especially when they understand how customers use their assets. In addition, energy-efficiency is attractive both to customers looking for greener products, and those looking to reduce energy expenses.

Gather greater insights into product usage

Collect accurate data on how your equipment is used in a production setting for insights into how customers actually use, or misuse, your products. Then, optimize your product accordingly.

Unlock new business models and new revenue streams

Equipment makers are using IIoT to unlock new service-based business models, such as Equipment-as-a-Service, focused on aligning product performance with customer needs. This new business model shifts the reliance on shrinking hardware margins to more profitable after-sale services and parts.

Improve the customer experience

Differentiate from the competition and keep customers happy with IIoT. According to the Global Machinery & Equipment Report from Bain & Company, machinery companies that implement value-added, IoT-enabled services have a shareholder return 8x greater than those that don’t. Equipment makers can deliver an in-depth overview of equipment conditions to customers while handling the tasks customers don’t want to worry about, such as software and firmware updates for performance and security.

IoT buyers guide

IIoT use cases

The power of IIoT-connected equipment is that deployed correctly, it provides benefits both for equipment makers and the manufacturers that use it. There are numerous use cases for IIoT; the following show examples of common use cases in action:

Remote monitoring

IoT remote monitoring uses connected devices to gain live insights into equipment use and performance. These insights accelerate the development of new product features that matter most to customers.

Remote monitoring also saves equipment users—whether they are manufacturers, utilities, logistics providers or in other industries—costs associated with maintenance and downtime. According to McKinsey, remote asset condition monitoring can reduce maintenance costs by 30% and cut machine downtime by 50%.

When the City of London set an ambitious goal to create the world’s first Ultra Low Emission Zone in central London by 2020, Sensor-Technik Wiedemann (STW)—a leader in automation, electrification and digitalization and a specialist in large vehicle and equipment telemetry—was connected to the effort.

To accomplish this ambitious goal, STW utilized remote monitoring for real-time data on soot particles [PM] and nitrogen oxide [NOx] emissions from a fleet of over 5,000 city buses. This immediate access to bus data gave London visibility on what every single vehicle is doing in real time—from emissions data to vehicle faults, GPS-based locations and fuel consumption with the click of a button.

These remote monitoring capabilities gave London the ability to cut bus particulates by 99% and NOx by 90%. And by enabling automatic fault alerts and predictive maintenance actions ahead of when they are needed, bus routes ran as smoothly and efficiently as ever.

Real-time alerts

Automate real-time alerts that notify you of specific events even before they occur. These alerts can detect signs of possible equipment failure—such as too high of a temperature or too low of a pressure—dramatically reducing downtime while minimizing risk.

The organization behind the world’s first fully electric entry-class single-seater racing series, Electric Racing Academy (ERA), wanted to turn an electric car into a vehicle for connected intelligence. To do this, ERA utilized IoT technology to power a fluid flow of real-time racing data to Software AG’s Cumulocity IoT platform. With continuously streamed data about speed, acceleration, torque, RPM, temperature and more, drivers and coaches can configure real-time alerts for parameters such as weather conditions or regenerated power levels. These notifications help teams make both safety and performance-related decisions in an instant.

Digital twins

An IoT digital twin is a digital representation of a real-world entity—from a single device to an entire manufacturing production process. Even if you have hundreds of assets, each equipped with many different types of sensors, creating digital twins allows you to manage, monitor and run tests on those dispersed assets from a single dashboard.

Digital twins are handy for operating fine-tuned machines in harsh, remote environments. For example, deploying a digital twin of a wind turbine means you have 24/7 access to an identical visual of it. You can monitor the turbine when it’s too dangerous to collect crucial information in person and ensure that environmental hazards, such as wind, waves and temperature, do not damage the turbine. Using the digital twin, you can also act on the physical machine, such as stopping the wind turbine before damage occurs.

The Geico Taikisha Group—a world leader in the design and construction of turnkey automated auto body paint shops—utilized digital twins to stay connected to their customers with access to in-depth production data. This allowed Geico to understand how their machines perform and common errors they encounter, using this information further to improve paint shop cell performance for their customers.

Geico customers also accessed these digital twin capabilities with their machinery. This enabled customers to create live simulations for potential efficiencies, vulnerabilities, and most prominent of all, cost savings.

This transparency enabled customers to predict maintenance and downtime for reduced spending. And with smart energy management capabilities, customers can use the digital twins for detailed optimization of resource usage for sustainability and further cost-saving initiatives.

Smart field services

Field services require employees of the equipment provider to travel to the customer site to perform services such as installation, equipment repairs, part replacement, regular maintenance and consultative services. As a result, equipment makers must manage teams of technical service providers to diagnose, fix and improve customer equipment.

Smart field services use analytics to understand IoT data collected from equipment in the field. Providers use insights to identify, schedule, plan and execute field services, and can share information with customers to offer a more accurate understanding of future maintenance and support needed. This means technicians only visit the field when needed. And when they are needed, the job is completed on the first visit.

SMC specializes in the manufacturing of pneumatic equipment. In a business where “air costs money,” SMC wanted to expand on IoT technology to save the company and its end-users costs associated with leakage-caused air loss.

Instead of traveling to the equipment site to assist with leakage issues, SMC measures and shows end-users where the compressed air leakages are and how they can reduce the incidents—no travel required. For SMC, smart field services eliminate the risk of unplanned downtime for customers and allows factory managers to conduct maintenance quickly and remotely for a better experience for all.


IoT analytics allows you to understand, predict and act on the powerful insights revealed in your IoT data. It can be categorized into three categories:

  • Historical analytics helps you understand what has happened
  • Streaming analytics helps you understand what is happening now
  • Predictive analytics helps you understand what is likely to happen in the future

According to the Forrester report on the economic impact of IoT, advanced analytics produce recommendations that can extend the lifetime of equipment by as much as 200% while reducing electricity costs by up to 20%.

Huntsman, a family-led leading global manufacturer and marketer of differentiated and specialty chemicals, identified an opportunity to optimize their production process with analytics. Using TrendMiner, a powerful self-service analytics tool, Huntsman enhanced its operational visibility with a combination of daily data, new sensor data and lab-analysis data.

Advanced analytics allows Huntsman’s process experts to make micro-adjustments to process setpoints to proactively minimize impurity levels in their product. For example, predictive analytics now forecasts the hydrolyzable chloride levels in the final product, allowing Huntsman to mitigate any impact on product quality. In addition, streaming analytics made it possible for Huntsman to obtain 24/7 quality control, which reduced the demand for lab resources by as much as 10%.

Predictive maintenance

Predictive analytics enables manufacturers to offer predictive maintenance services, which helps their customers maximize uptime, anticipate maintenance needs and reduce maintenance costs.

Predictive maintenance services improve key efficiency metrics for field services like first-call repair rate, costs to serve and customer lifetime value. They also increase customer loyalty and satisfaction by preventing costly downtime.

Dürr, one of the world’s leading mechanical and plant engineering firms, saw IIoT analytics as a way to revolutionize the automotive painting industry. On Dürr’s robotic paint applicators, the dozens of tiny air nozzles that are responsible for shaping the airflow get contaminated over time. This meant fixed cleaning cycles—whether or not cleaning was even needed—as well as the occasional contaminated paint run of multiple car bodies before the defect could be spotted.

By equipping robots with hundreds of IoT sensors, Dürr applied advanced analytics to sensor data so they would be able to conduct predictive maintenance on the tiny air nozzles. As a result, nozzles are cleaned only when needed to prevent contamination. And defective paint runs due to contaminated shaping air nozzles no longer happen thanks to data-backed, accurate predictive maintenance planning.

Performance management

IoT performance management allows you to improve operational performance, and overall equipment effectiveness (OEE) is the trusted standard for measuring machine availability, performance and quality.

With a rich stream of data from connected equipment, you can manage the performance of your operations with accuracy and ease. You can use OEE calculations to quantify equipment performance and help you increase machine life. For equipment makers, this ensures customers get maximum use and value from equipment. For customers, they’re empowered to view OEE themselves for smart, fast decision-making to keep their production lines flowing.

Ashland, a company that originally manufactured construction materials, shifted its product focus toward personal care and pharmaceuticals. However, this transition sparked fresh challenges.

The company experienced seemingly “unsolvable” production issues and recognized a need for increased operational efficiency to boost quality and profitability. Using IoT performance management, Ashland solved production issues, enhanced quality control and increased good manufacturing practice (GMP) production throughput. This was achieved with TrendMiner’s easy-to-use dashboards, where everyone was provided pain-free insight into the performance of equipment and processes. Ashland used root cause analytics to determine unknown correlations upstream and adjust processes based on the findings. This resulted in an on-target production of GMP products increase from 70% to 95%.

Shifting to an Equipment-as-a-Service business model

Manufacturing is undergoing a transformation in how it delivers its products to the market. Customers demand more from their equipment, seeking data-driven services to boost operational efficiency. At the same time, many are hesitant to invest in capital-intensive hardware and would prefer to pay instead for the machine’s output. This means that manufacturers’ products must evolve to enable new models like Equipment-as-a-Service (EaaS).

IIoT is powering this evolution to EaaS. Manufacturers delivering smart equipment can stay connected to their machines to improve productivity, predict maintenance issues and hit high efficiency goals—saving not only costs but the environment. Equipment makers use IoT to gain access to operational data, enabling them to analyze the performance of installed equipment and guarantee certain service-level agreements (SLAs). With services the improve insights into, and control over, equipment, plus lower up-front costs, improved uptime and lower total cost of ownership (TCO), leading equipment makers are leveraging EaaS to improve the customer experience.

Overcoming IIoT challenges

IoT has the potential to transform organizations—but that doesn’t come without challenges. Many IoT projects are not meeting expectations, and many fail completely. In fact, Beecham Research tells us nearly 75% of all IoT projects aren’t considered a success. The roadblocks come in several forms from both a technical and business perspective. Here are some of the most common IoT and IIoT challenges that organizations face on their IoT journey:

Technical challenges of IIoT

Self-service device management

Device management refers to the lifecycle management of your connected devices, including device onboarding and configuration. This process of managing your devices isn’t a simple one—especially if you have thousands of devices. And managing the connectivity of these devices brings a whole realm of additional issues.

Self-service device management can help you operate independently from a vendor, but challenges still arise for those without advanced software-engineering expertise. This is particularly frustrating for those just starting on their IoT journey and wanting to deliver IoT services to their customers without standing up dedicated software teams.

The solution? An IoT device management platform that simplifies management with pre-integrated device connectivity and management capabilities. The right platform should offer no-code capabilities and allow you to manage and monitor the entire lifecycle of devices and sensors with ease and in one place—from planning and onboarding, to monitoring and maintenance, through to retirement.

Device updates

It’s a challenge to deploy software and firmware updates to IoT devices, and it’s even more of a challenge to ensure that those thousands, even millions, of IoT devices update reliably.

While an IoT platform simplifies the deployment of firmware or software to devices to patch security vulnerabilities and update code, many platforms leave users lacking confidence that these crucial updates—ones that aim to reduce cyber risks and boost reliability—were pushed through to devices.

To make matters worse, frequent failures with updates may require a significant level of manual intervention, taking valuable time from IT administrators. Your platform should allow you to update any number of devices efficiently in a controlled, phased way to avoid failures while offering status visibility.


According to Beecham Research, 60% of those involved in IoT projects said that they had problems with scalability.

As IoT-enabled services become an increasingly important part of how organizations serve their customers, delivering scalable IoT services to internal and external customers is a challenge. Additionally, as customers’ adoption of these services occurs over time, many organizations find themselves in a position where IoT platform costs can’t scale with deployments.

The solution is a reliable, scalable IoT platform that can support your long-term business goals and also offers a pricing model that can scale with your deployments. This allows organizations to experiment with new concepts and business models without a prohibitively high up front investment.


The benefits of IoT—reduced downtime, increased performance, incredible insights—are only obtainable if your IoT system is reliable. Without reliability in accurate and truly real-time data, your insights and decisions are flawed.

IoT plays a critical role in your business processes and the products your customers use. You need to ensure that your IoT solution is enterprise-grade—and, if not, that you have a plan to improve it.

Enterprises need higher levels of quality and resiliency than legacy IoT platforms can provide. And according to Machnation’s whitepaper on Six Steps to Replacing Your IoT Application Enablement Platform, too many IoT platforms are unable to provide the service levels required to support business-critical enterprise IoT applications and typical IoT workflows.

For insight on how to overcome this challenge and deliver enterprise-grade IoT for the ultimate in reliability, security and performance, read Machnation’s whitepaper to learn six critical steps to accelerate success when switching IoT platforms.


Security is a common challenge for all new technologies, and IoT is no exception. A loss of data or an IoT security incident could lead to the compromise of other systems and downtime.

For organizations who opt to build and implement their own IoT system, security challenges lie in wait at the intersection of competing demands. The platform must be bulletproof while ensuring the right people can access the right information. On the other hand, purchasing a platform that claims to offer built-in security measures may make you blind to new vulnerabilities or leave you unaware of ways to improve security techniques.

You’ll need an IoT platform built with enterprise-grade security woven into every line of code.

The right IoT platfom can make managing and ensuring the security of IoT devices much easier. It can enforce security standards, help you protect data by implementing segmentation and encryption, and allows you to easily manage, update and upgrade access to specific devices or device groups. With these measures, you can rest assured your devices and data have the appropriate security functionalities at all times.


According to Forrester Consulting on the economic impact of IoT, organizations that deployed Software AG’s Cumulocity IoT platform received up to a 125% increase in incremental revenues from advanced IoT analytics solutions over three years.

Advanced analytics helps you understand you and your customers and improve equipment and process performance. And while offering advanced analytics allows smart equipment manufacturers to develop new revenue streams, it also enables customers to realize the maximum value from their investments in equipment, building loyalty.

However, offering and deploying analytics is a challenge to both makers and customers. When solutions can’t live up to the promise of cloud and edge computing, “insights” are not quite as real-time, transparent or valuable as one would have hoped. This is especially harmful as IoT analytics is a capability that enables important IoT use cases, such as remote monitoring and predictive maintenance.

To add to the challenge, few companies have the necessary integration and data analytics expertise required to get the most out of the IoT data they’re gathering. The solution? A platform that supports advanced analytics for any IoT ecosystem with sophisticated, highly configurable, and out-of-the-box dashboards empowering all users to get the most out of IoT data.

Data integration

To act on your IoT data and use it to improve operational efficiency, data must be integrated into a variety of existing enterprise applications and systems such as enterprise resource planning (ERP) and CRM solutions. However, IoT integration can be difficult for organizations if their IoT platform locks them into proprietary standards and hardware.

To avoid this challenge, use an IoT platform that offers easy integration capabilities with your IoT ecosystem and enterprise apps, whether they’re in the cloud or on-premises. Make sure the platform offers open standards and OPC Unified Architecture (OPC UA) as a machine-to-machine communication protocol, so you’ll be able to leverage all your existing IT and other infrastructure investments, from applications to industrial machines.

With an IoT platform that offers prebuilt connectors and predefined recipes, you can build integration workflows quickly between pre-integrated enterprise and cloud apps. Your solution should also make data lake integration easy, allowing you to integrate historical data into a wide range of applications.

Business challenges of IIoT

Business aims

IIoT is exciting because it can enable a wide range of new capabilities. That’s also one of the challenges. There’s not only enormous variety in what people are connecting and the data they are generating, but also their objectives. Are you looking to increase safety? Reduce costs? Improve productivity?

96% of IoT adopters say that a clear understanding of the desired outcomes is important to the success of IoT projects. Make sure you can state your business case clearly. Engaging with senior management can help you work through how the project will function logistically and align with the organization’s larger objectives.

Cross-functional collaboration

IoT projects tend to include departments that span a range of functions. Everyone in the organization needs to work together to make the project a success—a challenge in instances where departments have different goals and different ways of thinking. Beecham Research found that nearly every professional who worked on an unsuccessful IoT project said that lack of cohesion among cross-functional teams was a factor in their failure.

Consider the challenges your company’s organizational structure might introduce to IoT initiatives, whether caused by friction between new IoT process and older working practices, or simple resistance to change. Effective coordination is critical, both between technical and managerial teams internally, and with external ecosystem partners.

Vendor relationships

Implementing IoT projects can be complex, making the right vendor relationships essential. The majority of organizations that rely entirely, or almost entirely, on in-house resources deliver IoT projects that fail to meet expectations.

Bringing in an external solution provider is not a cure-all, but it can help provide needed expertise: not only technical guidance but also guidance on the feasibility of plans, strategy for implementation, and setting realistic financial targets. The most successful approach is to combine the experience of an external solution partner and in-house project leaders who also have IoT expertise.

Business model evolution

Equipment makers making the shift to new business models find that transitioning to service-based relationships can be an organizational challenge. According to Beecham Research, just 4% of businesses striving to enable new business models reported that they’d been fully successful.

Evolving your business model requires a new customer-centric mindset among everyone in the organization. Fortunately, IoT platforms that are designed to support this evolution equip businesses with data needed to transition with confidence. IoT data helps equipment makers improve design, understand user needs and best support customers.

An enterprise-grade IoT solution helps you evolve with IoT for faster business results and sustained innovation.

4 steps to building value with IoT

Prior to adopting IoT, equipment makers sold unconnected products and only interacted with their product when a customer called about a problem. This business model leaves them vulnerable to ever-shrinking margins on hardware and at a disadvantage in delivering new insights and services that help customers perform better.

However, building an IoT solution is challenging. Beecham Research showed that virtually all IoT adopters found connectivity was a challenge. 87% felt they lacked the right expertise, and 60% had constrained analytics.

Avoid these costly challenges and accelerate your IoT project with a “buy and build” approach.

Buy an IoT platform that’s easy to deploy—no coding needed in many cases—and comes with pre-integrated device connectivity and management, application enablement and integration, as well as streaming and predictive analytics.

With IoT now simplified, you can focus on building differentiating capabilities on top—with use cases that follow the IoT maturity curve.

The IoT maturity curve

The first step to IoT success is to think big, start small and move fast. Moving to an “as-a-service” model goes far beyond technology—creating new business models means changing your culture and building a new kind of relationship with customers.

The IoT maturity curve helps guide equipment makers to take right-sized bites that, step-by-step, add up to a truly transformational outcome.

1. Remote monitoring

IoT remote monitoring is a great place for equipment makers to start because it gives the power to gain insights that accelerate the development of the new product features that matter most to customers.

2. Smart field services

Once your devices are connected, you can use the data from IoT devices for smart field services. Know exactly what, when and why your customer’s equipment needs servicing. This reduces costs and ensures customers get greater uptime—increasing your value as a strategic partner.

3. Performance management

Apply IoT data analytics to continuously improve the customer experience and create new outcome-based services based on improved uptime, lower energy consumption and more consistent output quality.

4. Equipment-as-a-Service

The last step on the IoT maturity curve is transitioning into a “product-as-a-service” model. EaaS helps equipment makers reduce customers' TCO while shifting focus from one-off product sales of capital-intensive equipment to a model that generates more predictable, recurring revenue.

To get the most value out of your IoT journey, you’ll need a solution that can foster transformation and empower you to successfully move up the IoT maturity curve.

4 steps to IoT value and climbing the maturity curve
The ROI of Industrial IoT

IIoT users need a robust, reliable IoT platform to offer ROI while supporting both existing and changing business models.

According to Forrester Consulting research on The Total Economic Impact™ Of The Software AG Cumulocity IoT Platform, customers using Software AG’s Cumulocity IoT platform across the IoT-enabled business cycle see a 339% ROI. Here’s how:

  • Reduce downtime and increase the life of assets:
    Using advanced software to monitor and analyze performance, companies can recommend specific, proactive steps to ensure equipment uptime. According to one company, Cumulocity IoT advanced analytics produce recommendations that can extend the useful lifetime of equipment by as much as 200%.
  • Efficient repair and maintenance processes:
    Organizations see significant savings for unplanned repairs and maintenance thanks to predictive maintenance and monitoring capabilities with Cumulocity IoT. One equipment manufacturer saw a 30% to 40% reduction in unplanned maintenance calls and, on average, makes 35% fewer visits to sites where equipment is monitored remotely.
  • Real-time detection for real-time action:
    Proactively detecting equipment performance issues in the field means you can act on the equipment before maintenance and damage costs arise.
  • Improved product quality:
    Leveraging the Cumulocity IoT platform for remote monitoring and advanced analytics capabilities makes it possible to build zero-defect assembly lines. You’ll know when something might go wrong with your product long before it’s in process.
  • Optimize processes throughout:
    Monitor manufacturing processes and machinery in real time and optimize these processes to eliminate bottlenecks—from supply to delivery—to reduce costs.
  • Accurate data on environmental impact:
    IoT data helps organizations understand energy usage and waste so they can act more responsibly. According to one company, Cumulocity IoT’s advanced analytics detect and fix irregularities in real-time, resulting in up to 20% savings on energy consumption. For revenue growth, enhanced customer experiences, streamlined field-force operations and the ease of IoT service delivery, choosing an industry-leading IoT platform will not only support but empower your business’s evolving IoT project—promising unbeatable ROI.
For successful edge IoT projects, buy and build

Meet our IIoT solutions

Cumulocity IoT is a leading self-service IoT platform, top-rated, with fast ROI.

An open and independent platform, Cumulocity IoT works with the things you’ve got—and what you may add in the future. Wherever you are on your IoT journey, Software AG can help you make the most of your investment and achieve the best outcomes for your business.

The streaming analytics capabilities of the Cumulocity IoT platform are built with Apama. With Apama, you can filter, aggregate, enrich and analyze big and fast data from many different live data sources in any data format to identify simple and complex patterns.

TrendMiner is Software AG’s self-service industrial analytics software for smart factories and Industry 4.0 operations. Based on a high-performance analytics engine for sensor-generated time-series data, TrendMiner allows process engineers and operators to easily search for trends and question process data directly—on their own, without the help of a data scientist. If you’re on a quest to continuously improve your production processes, take a look at TrendMiner.

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Why Cumulocity IoT?

1. Faster ROI in building IoT solutions

Build your own branded IoT solution and generate business value in weeks rather than months. How? The Cumulocity IoT platform simplifies things for you with self-service tools and a configuration-driven approach.

Innovate on the only completely open IoT platform and free your business from the constraints of any one technology stack. Because you’ll be using open standards, you’ll be able to connect any “thing” today and tomorrow. That means you can bring your own hardware and tools and pick the components that best fit your business.

Rather than reinventing the wheel, your team can focus on the fun stuff: building differentiating logic and applications on top of a solid foundation. Everyone in your organization has access to the Cumulocity IoT specialized applications that drive success, such as:

  • OEE App: Accelerate time to value with ready-to-go mobile IoT apps, partner solutions and insightful applications, such as our Overall Equipment Effectiveness (OEE) app.
  • Digital Twin Manager: The pre-packaged Digital Twin Manager application allows you to create solutions around business assets instead of IoT devices for the enrichment of digital twin representations, resulting in a greater understanding of all your connected assets.
  • SmartRules: With SmartRules, you can visually define and associate rules and alarms to an individual device or a device group with automatic activation on registration.
  • Analytics Builder: Simply “point and click” to apply data science techniques and get maximum value from your IoT data.
  • Application Builder: The Application Builder for Cumulocity IoT offers a no-code, drag-and-drop approach to create great-looking Cumulocity IoT applications directly inside your browser.
2. Easy-to-scale mass IoT deployment

Develop once, deploy anywhere with our enterprise-grade IoT solution. From one console, you can onboard and manage devices, including bulk registration and updating. Integrate third-party apps and systems—without coding—to automate actions, workflows and processes across OT and IT assets. You’re also free to run your solution wherever you need it—cloud, on-premises and/or at the edge—and do analytics anywhere, for example, at the edge near data sources. Easily evolve and expand your IoT solution using a building block approach as your needs change over time.

3. IoT for all roles

Cumulocity IoT is designed so that every person in your organization is empowered by IoT data and analytics. Your data scientists will be thrilled at what they can do, and everyone else will be thrilled they won’t have to be one. That’s thanks to its low code/no code options, built-in suite of specialized apps for IoT projects and data, and industry leading support for white labeling and multi-tenancy for B2B2X.

Cumulocity IoT has something for every role. Product developers can quickly build, test and scale IoT solutions with our proven self-service IoT platform. Field services and support can increase service revenue, maintain SLAs and improve the effectiveness of their service management team. Operations technologists can use remote monitoring to ensure customers’ machines are always operating at peak efficiency, with minimal unplanned shutdowns. IT leaders gain both reliability and innovation with our open, scalable, and secure solution that delivers results fast with minimal risk of project failure. And executive leadership can be sure their IoT solutions deliver greater competitive advantage and provide a path to increasing profitable growth.

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