Industry 4.0: Business Opportunities for Manufacturing Companies

Industry 4.0 is the latest catchphrase among technology enthusiasts. Everyone envisages how their companies can make giant strides using emerging technologies and data. But in reality, not everybody is equipped to take on the attendant risks: modernization demands considerable investments and the dividends may take several years to arrive.


At the same time, data-driven manufacturing opens up new business partnerships and profit-making opportunities. In this article, we’ll examine three scenarios where manufacturers monetize data, discover new revenue sources through data-driven services, and reduce investment risks.

Industry 4.0 Concept Explained

Industry 4.0 simply means the Fourth Industrial Revolution – the next big step in industrial development. The overarching theme of Industry 4.0 is the use of IoT data for production. Basically, production machines are equipped with sensors that generate data and send them to the cloud. There, artificial intelligence interprets the data, recognizes and predicts anomalies, and notifies workers at regular intervals or in real-time. The most advanced of these solutions optimize manufacturing processes without human involvement.

As expected, such advancements usually require considerable investments. A few visionary companies do make the investment to implement Industry 4.0 in their plants, though, because they know that with modernization comes new sources of revenue.

Industry 4.0 Business Models: New Business Opportunities

Data technologies propel new Industry 4.0 business models. These models offer data-driven value creation, introduce new players in the value chain, elicit cooperation between companies, and unlock fresh revenue-generating channels. Let’s take a closer look at three new models and their real-life implementations.

Scenario 1: Providing Additional Services with New Players in Value Chain

By equipping products with sensors, it becomes possible to track how your products are used. Sensor-generated data can be analyzed for insights to provide your customers with additional data-driven services. These enhanced modalities can be used to track product status, notifying the operator if something goes wrong. Ultimately, product life is extended through timely maintenance to ensure a sustainable production process. All you need to do is incorporate IIoT platforms into your value chain. 

How It Works

  1. The product manufacturer adds sensors to their product, connecting it to an IIoT platform which obtains all the data about how the product is used. After analysis, the manufacturer offers data-inspired services to its customers.
  2. The IIoT platform provider operates an IIoT platform with AI capabilities where sensor data is stored and analyzed. They charge the manufacturer a fee for using the platform. The fee depends on the number of sensors connected and the data volume.
  3. The customer pays the manufacturer based on the actual use of the service. 

Real-life Example

HELLER is a global manufacturer of machine tools and systems for metal-cutting processes. The company has developed a solution that enables its customers to avoid losses caused by sudden downtime. The solution uses MindSphere, an IIoT platform from Siemens that aggregates and processes machine data. All operations and maintenance data are visible via a mobile app to both the manufacturer and the customer. HELLER notifies the users immediately if maintenance is necessary or an unexpected machine overload occurs.

Value for Customers

With IIoT integration, your customers will enjoy a high equipment lifespan and avoid downtime. They will no longer have to search for service providers, making them focus fully on core aspects of the business.

Benefits for Manufacturers

Besides being an additional revenue source, IIoT shows you real-time data on how customers use your products. Based on this direct feedback, you can improve your product’s features and functionality.

Scenario 2: Product-as-a-Service and No Financial Risks for the Manufacturer

The next model involves not only the provision of additional data-driven services but also the interest of an intermediate business.

In what is essentially a business-to-business (B2B) relationship, a distributor buys the product connected to an IIoT platform from the manufacturer and provides direct access to the customer. The customer benefits from the equipment without owning it. Thus, the supplier owns the product and bears any investment risk that ensues.

How It Works

  1. The manufacturer sells a product generating one-off revenue to a provider (or distribution company).
  2. The provider company purchases the product and provides it to a customer for a fee.
  3. The IoT platform provider controls the usage and pricing according to the contract. They also provide the data on the product usage to the manufacturer and the provider company.
  4. The manufacturer ensures that a customer has unlimited access to the product. They also charge a provider for integration and maintenance services.
  5. The customer pays a fee to a provider per product use. Usage is controlled through sensors connected to the IIoT platform.

Real-Life Example

Machine manufacturer TRUMPF Group and provider, Munich Re Group, are teaming up to provide innovative services of laser cutting machines. They developed a pay-per-part model that enables manufacturing companies to use a full-service laser machine without having to buy or lease it. Instead, customers pay an agreed price for each cut sheet metal part they use.

Essentially, Munich Repurchases the machine and bears the resulting investment risk. Relayr, a subsidiary of Munich Re, provides an IoT data analysis platform. TRUMPF supplies customers with machines, software, and services for manufacturing sheet metal parts.

Value for Customers

  • Easy to start. Customers pay for the product based on the actual usage and don’t need huge initial investments to use the product.
  • No unexpected costs. Customers avoid unexpected expenses, such as charges for repairs and maintenance.
  • No minimum usage requirement and scalability. When the customer doesn’t need the product, they do not need to pay for it. When customers need to scale their businesses, they can easily scale the usage of the asset as well.

Benefits for Manufacturers

With this data-oriented model, manufacturers can increase revenue five-fold. Also, they can strengthen relationships with buyers and satisfy their customers better.

Scenario 3: Selling Data

Perhaps the most direct method to monetize data and secure returns on investments via IIoT innovation is to sell your manufacturing data on a data marketplace—a platform for trading different types of data. 

How It Works

  • The data marketplace is an infrastructure where companies buy and sell anonymized data. They evaluate the quality of the data, oversee data security, and ensure compliance with the terms of data use. 
  • The manufacturer sells manufacturing data collected from IoT devices installed on their equipment.
  • The data buyer buys this data to develop new solutions, improve existing products, or provide additional services. The buyer can be a system integrator, smart sensor supplier, or original equipment manufacturer.

Real-Life Example

Swiss startup, Steamr, created a platform that helps manufacturers make money from their real-time data. The marketplace uses blockchain technology to allow manufacturers to track how their data is used. Buyers can use an Ethereum-based cryptocurrency to pay for data usage.

Value for Customers

Data buyers gain access to data sources that help them optimize the performance of their own devices, train AI systems, optimize production, provide new services, and/or perform research and development in a cost-efficient manner.

Benefits for Manufacturers

Selling sensor data is a quick way to monetize data. Some marketplaces may offer additional perks such as granting access to more extensive databases with pre-analyzed data or data exchange with other companies.

Bottom Line

Data-driven manufacturing, as a unique genre, may require considerable investment, but the financial benefits outweigh the costs. By using sensor data wisely, companies can provide value-added services, improve their products with real-time feedback, sell their data, or open up new channels for profitable collaboration with minimal financial risks.

If you’re looking to take advantage of these contemporary industrial IoT business models and need assistance with technical implementation, Softeq professionals are on-hand to help. At Softeq, we enhance your machinery with sensors, create a cloud-based platform for data analytics, and improve the performance of your equipment by enabling a smooth data transmission.

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