It’s almost become cliché to say that we are living through the fourth industrial revolution. While the first dealt with mechanization, the second with mass production, and the third with automation, Industry 4.0 brings together the virtual with the physical through sensors and rapid electronic decision making (the industrial internet of things (IIoT) to enable truly “smart” factories and quick responses to changing production circumstances.
However, “smart factory” and “Industry 4.0” have become buzzwords. Everyone wants to talk about the increase in profits that new technologies might yield. However, despite the potential rewards, not everyone is ready for the risk, the whole-of-business retooling, or the lengthy payback period that this emerging tech can require.
Industry 4.0: Implement Now to Profit Later
We’ve already pointed out that “Industry 4.0” has become a buzzword – and there are good reasons for this. The thoughtful deployment of IIoT and the new data-driven insights from linked equipment promise to change your business in ways you wouldn’t have imagined even a few years ago.
Similarly, data-driven industrial production gives your company new opportunities—and while any change represents a risk, it doesn’t have to be a gamble! Below, we’ll look at three scenarios for how manufacturers monetize data, find new income streams through data-driven services, and decrease investment risks.
Business Models For Industry 4.0
The new business models of Industry 4.0 arise directly from data technologies. These models can involve new actors within the value chain, value creation driven by data, new business-to-business (B2B) cooperation methods, and entirely new ways of generating revenue. Read on for a closer examination of these new models with some real-life examples of possible implementation.
Case 1: New Services with New Actors in Value Chain
This model relies on introducing an IIoT platform provider and installing sensors into your products. Data generated by these sensors can give insights to your consumers and yield opportunities for further data-driven services, such as:
- Product status monitoring
- Notifying an operator if something goes wrong
- Increasing product life through regular maintenance
- Improving production procedures
Clients can benefit from extended equipment lifespan, less downtime, and an improved cost of ownership (even with the marginal fees for additional services). In addition, they won’t have to hunt for a supplier of these services because they already deal with you. Therefore, they can focus entirely on their primary business.
In this scenario, you get an additional revenue stream and real-time data on how clients utilize your equipment. This direct input can be a goldmine for improving your operations and production. In addition, it eliminates the cost and tedium of after-sales customer follow-up to gain imperfect and low-confidence versions of the same information.
How It Works in a Nutshell
- As a manufacturer, you install sensors in your equipment, enabling it to connect with an IIoT platform.
- An IIoT software provider runs an AI-enabled IIoT platform that collects, processes, and analyzes sensor data. This provider bills you for utilizing its platform. The fee may vary based on the number of connected sensors and the volume of data they collect.
- The IIoT platform collects the relevant information on how the customer uses your equipment.
- The IIoT platform performs an AI-assisted, cloud-based analysis of the data. Following this analysis, you offer data-driven solutions to your clients.
- Finally, your customer pays you a fee based on the actual use of this service.
Better Equipment Maintenance through IIoT
HELLER is a global manufacturer of metal-cutting machine tools and systems. HELLER has developed a solution to help clients minimize unscheduled downtime and avoid the resulting losses. This system uses MindSphere, a Siemens-created IIoT platform for gathering and analyzing machine data. This solution allows the manufacturer (HELLER) and the customer to view all maintenance and operation data within a dedicated mobile app. The insights from this data allow HELLER to respond immediately if a machine overloads or requires maintenance.
Case 2: Product-as-a-Service and Eliminating Manufacturer Financial Risk
The following concept includes not only extra data-driven services but also new actors in the form of a finance company and an Internet of Things (IoT) platform provider.
Manufacturers can boost revenue through this model by multiples of up to five times. Manufacturers can also use the data they obtain to enhance customer interactions and boost loyalty.
How it Works in a Nutshell
- The finance company purchases the equipment from the manufacturer and provides access to the customer.
- The customer does not buy the equipment outright; rather, it pays the finance company for its use. The finance company owns the product and carries the investment risk instead of the customer or the manufacturer.
- The IoT platform provider controls the access and pricing of the product based on the contract. The IoT platform provider also transmits usage and access data to the manufacturer and the finance company.
- The manufacturer maintains the product and charges the finance company for maintenance and integration.
- Simple to begin. Customers pay for the product based on real usage and do not require large upfront payments to utilize it.
- No unexpected expenses. Customers avoid unpredictable costs like repair and maintenance fees while ensuring continuous access to the product/equipment.
- Continuous expandability, with no threshold usage requirements. When customers do not require a product, they don’t have to pay for it. Customers can also increase the asset’s utilization as their operations require.
Cutting Edge Laser Machinery On a “Pay-Per-Part” Basis
TRUMPF Group (a machine manufacturer) and Munich Re Group (a finance company) collaborate to offer laser cutting machines with advanced services. Their model operates on a “pay-per-part” basis, providing access to a complete laser machine without buying or leasing equipment. Instead, the customers (primarily manufacturing companies) pay a set price for each sheet metal part cut by the machine.
Munich Re finances the equipment and assumes the investment risk. A Munich Re subsidiary, Relayr, offers an IoT data analysis system. TRUMPF provides customers with the equipment, software, and services to produce the cut sheet metal parts.
Case 3: Data Marketplaces and Big Data Trading
Aside from manufacturers employing data, there is a more direct way to monetize data and benefit from your investments in Industry 4.0. You can put your manufacturing data up for sale on a data marketplace.
Trading sensor data is a quick additional method for monetizing your data. Some markets may provide additional compensation alternatives besides paying for your data. These might include access to larger databases with pre-analyzed data or data sharing with other businesses.
Data purchasers have access to data sources that enable them to enhance the operation of their own devices, train AI systems, optimize manufacturing, create new services, and undertake Research & Development at a low cost.
How It Works in a Nutshell
• The data marketplace serves as a platform for businesses to trade anonymized data. These organizations evaluate data quality, maintain data protection, and ensure compliance with data usage agreements.
• The manufacturer sells data obtained from IoT devices fitted on their machines.
• The data buyer acquires this information to create new solutions, improve existing offerings, or provide extra services. Buyers may be system integrators, original equipment manufacturers (OEMs), or smart sensor vendors.
Cryptocurrency-Backed Web3 Smart Factory Data Trading
Streamr, a Swiss startup, developed a platform to let manufacturers sell their real-time data. The marketplace employs blockchain technology to enable manufacturers to track how buyers use their data. Buyers pay for data consumption using Streamr’s cryptocurrency, the DATA token. This token currently trades at $0.0267/DATA, with a total market capitalization of over $18.6 Million at the time of writing. Data providers can convert their DATA tokens into conventional or “fiat” currency via Uniswap or other cryptocurrency exchanges.
Manufacturers who embrace Industry 4.0 will reap the benefits of efficient data collection and analysis through new revenue sources, lower operational costs, and improved products. Of course, implementing this modern business paradigm will require investment. However, it also opens up many possibilities for enhanced efficiency and increased profitability.
Whether you are still preparing for Industry 4.0 or already in the middle of a transformation project, take advantage of industrial IoT services full potential. Let Softeq help you unlock new business opportunities and adopt the advanced technologies you need to succeed in the manufacturing industry of tomorrow. For example, we can enhance your machinery with the right sensors, build a cloud-based platform for data analytics, or enhance your equipment’s performance by guaranteeing smooth data transmission. So don’t let the fourth industrial revolution pass you by – trust Softeq to help you make the smart tech investments for tomorrow, today.