In the landscape of skills data spaces, dissecting the multifaceted business models that drive their success is crucial. These models operate on different layers, each with distinct complexities and nuances. This layered perspective enriches our understanding of how value is created, shared, and sustained across the data space.
5.2.1. Different business levels #
The following three core layers collectively make up the business framework within a skills data space as described in Chapter “Approach”.
- Data Space Infrastructure: A critical part of this layer is understanding the costs involved—not just in terms of the technology stack but also the resources needed for governance and compliance. Different business and pricing models of data intermediaries and Data Space Governance Authorities serve different purposes at this level, often aiming for long-term sustainability while catering to a broad range of use cases.
- In the EU-Dune use case: InfraTrust and Fire-X materialise this level.
- Data Space Use Cases: This is where specialization comes into play. Specific use cases are designed to address particular needs or challenges, such as data analytics, skills matching, or forecasting. Each use case employs its business model, which could be as diverse as pay-per-use, licensing, or subscription models, all leveraging the foundational capabilities provided by the data space infrastructure and the participants therein.
- In the EU-Dune use case: SkillsFast orchestrates this level with all the use case participants.
- Data Space Use Case Participant: Participants can range from individuals and organizations to data providers and service providers. Each plays a distinct role, contributing to or extracting value from the data space in various ways. Adherence to the guidelines set by the infrastructure is paramount here, as are the tailored business and pricing models that align with the services or data being offered or consumed.
- In the EU-Dune use case: SDAI, SkillsFast, SkillProfiX, YourTraining, the training catalogues, the job boards, IntellIAITraining, DIgitFutUX, Matilda, InfraTrust are all participants.
By adopting this multi-layered framework, one can acquire a comprehensive, well-rounded view of the data space and gain the tools necessary for its effective management and growth. This approach allows for the observation of the dynamic interplay between the infrastructure, the supported use cases, and the myriad participants involved.
5.2.2. Different business models #
The most common used business models are (illustrated with the EU-Dune use case):
- Transaction model – one-off fee for having access to data product. Example: Anita from IntelliAITraining pays one-off fee to YourTraining for each qualified lead sent. YourTraining pays one-off fee to SkillsFast for each profile sent.
- Subscription model – a recurring subscription revenue for access to data products. Example: Francesco from DIgiFutUX pays subscription to SkillsFast to provide the service to his employees.
- Aggregation model – an aggregation of data products from multiple sources. Example: YourTraining aggregates data from multiple training organisations and sells it to SDAI.
- Freemium model – free data products with limited features and charges users a premium for additional features. Example: Matilda will have basic functions and some of trainings available for free.
- Advertisement model – offers data products to consumers without payment (data product is sold for advertisement). Example: IntelliAITraining provides data about its training to be advertised on YourTraining.
- Marketplace model – a marketplace provider typically charges participants on commission on transactions (either per number of transactions or per monetary value of transactions). Example: SkillsFast provides a qualified skills profile marketplace for training catalogues such as YourTraining to access.
5.2.3. Different pricing models #
The mostly used pricing models in data economy are (illustrated with the EU-Dune use case):
- Availability based – charges users for the availability of the data product regardless of whether it is used or not. Example: SkillProfiX buys API access for JobRightNow, Jobijob and Jobo.
- Data based – pays only for tailored or custom data product. Example: SkillProfiX charges for the data included in the analytics towards the employers.
- Usage-based – pays for the usage of a software or data product instead of for its availability. Example: YourTraining pays SkillsFast a subscription according to the number of individual profiles it receives.
- Performance-based – pays for the performance of the data product. Example: SkillProfiX pays for a platform access that will support peak times.
- Value-based – pays for a value that could be financial gain, functional or even emotional outcome received. However, some value streams may not be directly chargeable or it’s difficult to find applicable charging metrics. Example: IntelliAITraining pays to YourTraining a percentage on the trainings it sells thanks to its service.
In the next section, the business model and value sharing of the EU-Dune use case is illustrated (see subsection for an in-depth functional explanation of the EU-Dune use case).