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Industrial Internet of Things (Industrial IoT) is the term that connects smart devices to business values. Industrial IoT introduces several new ways to enhance and innovate existing business models or to evolve a new business model from core business.

As organizations are always willing to grow their business in all possible terms (revenue, productivity, market reach, user satisfaction), involving new technology in a business is one of the ways to improve all areas of the business. The 2020 Covid-19 pandemic has revealed the fact that organizations that are more adapted to new technologies have more possibilities to grow even in times of the pandemic.

The growth opportunities will remain out of reach until there is a real harmonization of interoperability, optimization of data collection, sharing, and analytics. The Industrial IoT offers the possibility to connect all knowledge streams from all sectors of business.

Organizations can adopt new business models based on Industrial IoT to extend their growth opportunities in new directions such as services, platforms, or product innovation.

Industrial IoT provides multiple opportunities to enhance the existing business of an organization. By using Industrial IoT, companies can take advantage of multiple business models by refocusing on possibilities. Industrial IoT gives the opportunity to extend business models from business-to-business (B2B) to business-to-customer (B2C).

IoT business models

Over the last few years, many business models evolved around the Industrial IoT. Some of the popular models are :

Platform-based business model

The platform-based business model gives the opportunity to generate more value by providing exchanges between two or more groups, more appropriately between consumers and producers (different manufacturers). The platform-based business model can be totally software-based. In this case, a software-based digital platform gives consumers the opportunity to use smart devices using a single platform, application, or API. Platform-based business models provide customers freedom from vendor lock-in and deep insights into device data.

A platform such as Amazon Alexa, Google Assistant, etc. is providing customers opportunities to use smart devices from multiple vendors with one application. The interoperability and internetworking of devices give a seamless experience for the consumer of smart devices and platform-based businesses generate revenue by monetizing the transaction between device and platform from the manufacturer.

Outcome-based business model

The idea behind the outcome-based business model is that it allows end-users to pay for the very specific value/service/asset that they really need. Today's mobilities service providers (e. g. Uber, Lime Scooter, etc.) are using the outcome-based business model. The manufacturing-based organization can extend their business using Industrial IoT for providing leasing or maintenance service based on the outcome-based business model.

Self-monitoring products that can automatically reorder consumer goods or replacement parts or can create a service request are typical examples of this kind of business model.

Data-driven business model 

As famously quoted by Mathematician Clive Humby “Data is more valuable than oil in the 21st century”.

Over the last decade, the success of big IT tech giants like Facebook, Google, and Amazon shows that when an organization embraces what data is saying to them there is an opportunity to generate a huge amount of gains.

One of the most important achievements of the 21st century is the wide adaptability of the internet and low-cost data storage. Smart devices are sending hundreds of zettabytes per year already. This vast amount of data enables organizations to build new businesses to turn data to profit.

Organizations can generate more value by analyzing the collected data by smart devices in Industrial IoT infrastructure. They can offer services like predictive maintenance, field service management, automated reordering, anticipated production, production optimization solutions, etc.

Service business model

In the service business model, your business offers a solution (software-/hardware-based) that offers Industrial IoT capabilities and services to existing products. This enables the organization to extend its business through Industrial IoT capabilities without much modification.

For example, add an embedded device to existing products that send your production-related machine data of different types of production machines to the Industrial IoT services and integrates the production line to Industrial IoT infrastructure. This gives manufacturing organizations the opportunity to optimize their production line, offer predictive maintenance, integrate field service management services, etc.

In such a business model companies have to collaborate with multiple organizations to provide a generic solution. To maximize their prospects and diversify their revenue streams, several businesses are integrating them into the business and processes.

You can provide an extension solution as an IoT vendor, provider, or partner by providing additional value to your clients.

Selected IoT use cases

In several of our projects, we've seen how companies gain profit from different business models once they've built their Industrial IoT infrastructure and apps. The IoT is a critical enabler for businesses to reorganize their operations into numerous streams of digital services and improve every aspect of their operations.

Organizations frequently build their Industrial IoT architecture around a single business model, and once the architecture is in place, they can explore a variety of business models.

Business Model: 

A good example of multiple business models is the "container leasing platform" we developed for a container manufacturing company. The company brings a solution to make containers smart using sensors (temperature, pressure, level, and light). The containers also have geolocation awareness with network connectivity. The Industrial IoT application offers multiple solutions such as asset monitoring, compliance management, process optimization, and warehouse optimization.

Initially, the platform was developed for a single customer as a data-driven business model, later realizing the widespread use of similar applications for different organizations. Since many organizations use the containers for different industrial purposes, the sensory capabilities can be customized to fit other companies' containers.

The application for a single organization is then transformed into a platform that can be used by multiple organizations, and a logger device is produced with all required sensing capabilities that can be added to any container to turn it into a smart device.

In other projects, we have developed an Industrial IoT solution for production line optimization that was based on the data-driven business model to get device insight while on duty to optimize production and predictive maintenance. Later on, realized multiple use-cases can be realized like automated reordering parts-based damage analysis, incident creation, field service management, product innovation, and warehouse management. The organization can take advantage of a combination of the data-driven and outcome-based business models from their smart products and Industrial IoT applications.

The Industrial IoT gives organizations a synergy effect by extending the visibility of multiple business divisions and set up a correlational understanding between them such as production - warehouse - logistics or product innovation - product services. The synergy effect provides the opportunity for businesses to optimize processes, improve products, and introduce new digital services.

These are some classic examples of how an organization can benefit from merging multiple business models once the Industrial IoT infrastructure is ready.

Associated risks

It is important to point out the failure of big investment without proper business models research and technology adoption tests. While there are many benefits of Industrial IoT adoption there are also possible negative consequences. There are many factors that can lead to a project failure in new technology adoption, some of the main issues are as follows:

  • Definition problem

    • Weak business use case

    • Imprecise business objective

    • Infirm project outcome matrix

  • Scope problem

    • Poor requirement management

    • Unclear requirement definition and prioritization

  • Support problem

    • Inept corporate technology leadership

    • Inadequate technology provide support

  • Management problem

    • Poor project management

    • Poor communication

  • Talent problem

    • Inadequate technology experts

    • Lack of overall development resources

In our experience of Industria IoT implementation projects, we have observed that the first three problems are the key dangers for project failure, delay, and escalating costs. It is very important to give more time to project definition and scope definitions before starting the technological development.

Incremental projects are often more successful than megaprojects. When it comes to innovative technology, "big" projects are much more likely to fail than small ones.

To succeed in business transformation, an organization should restrain itself from big-budget megaprojects. On the contrary, it should invest in small MVPs (minimum viable product) until proven worthy and look for big wins in very small packages. Small MVPs give an opportunity for all organizations to adopt the best of innovation with a low amount of risk.

“Fail early, fail often, but always fail forward.”
― John C. Maxwell

Unprecedented benefits of IoT MVP projects

 “A ship in the harbor is safe, but that is not what ships are built for,” observed 19th-century philosopher William Shedd. In the best words, organizations that do not focus on innovation through IoT and digitization are ignoring growth. If the potential of Industrial IoT is not exploited at the right time, it is also possible that companies will lose their competitive advantage in the long run.

To maintain the innovation cycle pace and to avoid the risk of project failure in new technology adaptation, it is important to start small with an MVP. MVP projects give organizations the opportunity to understand and experience the benefits of the product at a low cost. Through IoT MVP projects organizations can prove the values of IoT in their business. The business model can be improved or extend using Industrial IoT MVP.

With a low risk of failure, businesses can take advantage to generate values through Industrial IoT such as product innovation, digitized product services, improved maintenance, and life cycle of a product, optimized production, and improved brand value through reliable products. It is important to keep evolving the business model with changing times and technologies.

As the faith of the organizational success in the upcoming years will be defined by the coronavirus pandemic and agility of businesses to adapt to ever-changing scenarios. Digitalization with IoT is like a ship loaded with technology that has a huge capacity for transforming the business in the upcoming decade.


The blog is inspired by the following articles and resources

Business Models for IIoT:

Ludwig, Fabian, "Business Models Enabled by Industrie 4.0 and Internet of Things" (2016). Open Access Master's Theses. Paper 893.

J. Gao, Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5 – 7, 2017, University of Greenwich, UK   ISBN: 1614997926, 9781614997924

Daniel Kiel, Christian Arnold, Kai-Ingo Voigt,
The influence of the Industrial Internet of Things on business models of established manufacturing companies – A business-level perspective,

Project Management and Risk

J. Liebowitz, "IT Project Failures: What Management Can Learn," in IT Professional, vol. 17, no. 6, pp. 8-9, Nov.-Dec. 2015, http://10.1109/MITP.2015.110.

K. Fenech and C. De Raffaele, "Overcoming ICT project failures - A practical perspective," 2013 World Congress on Computer and Information Technology (WCCIT), 2013, pp. 1-6, http://10.1109/WCCIT.2013.6618719.

Jessica Greene, The top 9 reasons for IT project failure: Is your project at risk?


A Proven Methodology to Maximize Return on Risk,

V. Lenarduzzi and D. Taibi, "MVP Explained: A Systematic Mapping Study on the Definitions of Minimal Viable Product," 2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2016, pp. 112-119, http://10.1109/SEAA.2016.56


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