Hybrid models that combine aspects of the Digital OEM and the Digital Equipment Operator are more often the norm than the exception. Nevertheless, differentiating between these two roles can be very helpful for understanding many of the different concepts associated with them. This section will look at hybrid models in more detail, following again the why, what, how structure from the Introduction.
In many cases, companies will seek to create an integrated business model that combines the OEM and operator roles. For example, an electric vehicle manufacturer might also choose to own and operate its own network of fast charging stations (such as Tesla with its network of supercharger stations). In this case, combined KPIs are likely to include revenue and usability.
Alternatively, the OEM may choose an Asset-as-a-Service business model, which also means that it will play a hybrid role. In this case, the hybrid model will be based on a combination of typical OEM and operator KPIs, e.g., including both revenue and OEE.
Another example of a hybrid model is the Productized Retrofit Solution, e.g., a productized predictive maintenance solution. Here, the KPIs will combine revenue with costs for customer-specific modifications to the solution.
The definition of What exactly constitutes a hybrid model will heavily depend on the specifics of the product or solution. The table following compares the typical aspects of the Digital OEM and the Digital Equipment Operator, including aspects such as typical customers, offering, positioning of the assets on the balance sheet, typical KPIs, level of standardization, etc. A hybrid model might differ in any of these dimensions, or provide a combination thereof.
A good example of a hybrid model is the Predictive-maintenance-as-a-Service solution described in detail in the case study from Bosch Rexroth. One product category offered by the company are hydraulic components, including hydraulic motors, pumps, tanks and filters. These hydraulic components are used in many different applications, including manufacturing, mining and off-road vehicles. In order to offer customers of these hydraulics products an improved maintenance solution, Predictive-maintenance-as-a-Service for hydraulic components was developed. The main issue here is that it turned out that the algorithms for detecting anomalies related to the hydraulic components differ from application to application. To address this, Rexroth had to establish a setup that allowed them to standardize the offering as far as possible, and provide customer-specific customizations as efficiently as possible. This is a good example of a productized retrofit solution as per the table preceding.
Example: Drone-based Building Facade Inspection
Another good example of a hybrid model is the Drone-based Building Facade Inspection developed by TUEV SÜD. Again, this is described in more detail in the case study. This solution utilizes drones equipped with cameras, thermal scanners, and lidar (laser scanners) to create a detailed scan of the facades of buildings. On the drone, AI is used for flight path control, collision avoidance, and position calculation. In the TÜV Cloud, AI is used to detect anomalies such as concrete cracks, concrete spalling, corrosion, etc. The customer gets a detailed report about any potential problems with the facade that need to be addressed as part of the building maintenance process. In this case, TÜV SÜD is both the OEM and operator of the solution.
Again, there is no common blueprint for implementing hybrid AIoT business models. However, it is clear that a hybrid model must somehow combine the key processes of the Digital OEM with those of the Digital Equipment Operator, as indicated by the figure following. As we noticed, for example, in the Drone-based building inspection case study, TUEV SUED is both manufacturing and operating the solution. This will be true for many hybrid models.