Data Economy Actors
Data Use Cases
Enablers provide all other members of the data economy and beyond with non-data-specific services, technologies and resources such as infrastructure technologies (e.g. Internet providers), capital (e.g. VC), training (e.g. vocational training) or standards. Many framework conditions relevant in the context of the data economy are shaped to a large extend by enablers.
Strategies describe how agents react to their surroundings and pursue goals. They include deliberate choice but also patterns of response that pursue goals with little or no deliberation. Assessment of the success of own actions and the actions and success of other actors influence the change of strategies. Processes of reproduction and copying play an important role in the context of strategies. In the context of the data economy, strategies of actors are closely related to their business models.
Data acquisition: Actors focusing on data acquisition typically address very specific data in terms of content and their value propositions emphasise the access to this data. They publish raw data or interpretations of data, provide better access to or search engines for data or run platforms for data exchange. Demand-oriented pricing strategies are typically used for revenue generation, where the fee is sometimes linked to specific indicators. It also happens that data holders must pay actors to make their data available.
Data manipulation: Actors using data manipulation as core of their business model typically provide technologies or services for generating, analysing, visualising, managing or enriching data. In terms of value proposition, they predominately stress the performance, design or usability of their offers. With respect to revenue generation, subscription fees are typically charged. Implementing a premium model is quite common, while some actors implement a freemium model.
Data exploitation: Actors focusing on data exploitation do not only manipulate third-party data or provide technologies to do so but also exploit data themselves. They typically use data to create new products and services, improve existing ones, add data to non-data products or produce market analyses, surveys, plans and reports. Most actors charge their customers subscription fees. Actors usually highlight the newness of their offers, their experience in the field or performance aspects in their value proposition.
Technology provision: Actors using technology provision as basis of their business model typically provide technology-based services (e.g., a cloud-based analytics service) or technologies (e.g., a NoSQL storage solution). For technology-based services, subscription fees are typically charged, while in case of technology the products themselves are often made available free of charge and fee-based services are offered related to them. Nevertheless, there are also quite some technologies or tools that need to be licensed or bought.
Consultation: Actors focusing on consultation typically provide consulting on how to benefit from data, how to build a successful data-based business model or how to use data technology, data-related trainings or courses, or data skill management. The value propositions are usually focused on the experience the respective actor has. Consulting companies typically charge a fee for their services. The amount of the fee is usually fixed individually.
Enablers tend to reduce or avoid own ICT infrastructures
Cloud-storage and cloud computing services guarantee a certain service quality when service-level agreements are signed, which identify responsibilities, rights and obligations between the service provider and the user. In the last years, the service-based approaches like infrastructure as a service or software as a service have become more and more popular. This allows companies to consume external ICT infrastructure and reduce the need to create and maintain an own ICT infrastructure.
Enablers tend to hesitate to fully rely on services provided by third parties.
Using third-party services might lead to dependency. Dependency in terms of availability can be partly solved with SLAs, which describe a set of guarantees related to a service. SLAs in terms of data-driven services are not that common and need to be developed. Switching a vendor usually causes high switching costs for a customer, which might result vendor lock-ins. This might be critical in the data economy as very specific data might be offered only by few or even one holder.
Enablers tend to benefit from equivalency of transmission speed and Internet access structure all over Europe
Agents tend to benefit from equivalency of transmission speed and Internet access structure all over Europe.
The high-speed broadband Internet network is a fundamental technical requirement of the data economy. The available average speed and guaranteed broadband connection in Europe depends on the national efforts which are influenced by regulations and straightforward guidelines of the EC. However, this issue seems to lose its importance the new fibre generation might make it relevant again.
Enablers tend to benefit from a reduction in the technological gap between SMEs and large enterprises
Agents tend to benefit from a reduction in the technological gap between SMEs and large enterprises.
The data economy is heterogenous. Big companies distinguish themselves by having large financial, human and material capacities, which result strategic advantage to them. SMEs on the contrary often lack in those resources and in the possibilities to cope with latest technology trends. To compensate this beside the governmental financial subsidies the wide spreading of cloud services might provide a solution, which allow SMEs to use latest technologies without hiring expensive consultants or expert staff.
Enablers tend to restrict their activities to national markets
The focus of actors on national markets is the result of lacking integration of the European market, despite of all the serious efforts made by EU policy makers. There are many differences between EU Member States that affect the general opportunities and dangers relevant for the day-to-day operations of data economy actors. Legal, socio-economic and technological differences increase the costs and complexity for an actor that is active on more than one European national market.
What enablers provide are typically not specifically aimed at the other actors of the data economy. Resources of the enablers might include non-data-specific tools or technologies, capital, know-how or skilled workforce.