EU Project AEGIS

Business Models for Big Data: the AEGIS perspective for public safety and personal security

29/06/2018

Since the advent of Facebook and the related breed of social network platforms their main business model have been focused on contents and the creation of network effects able to guarantee the flow of data from users, that actually filled the gap of content management limiting the so called 1.0 ventures. Thus, revenues usually are considered to come from providing businesses, advertisers, marketing companies, and, in some cases, public institutions, access to the users’ data as well as the services developed on these data from new ventures accessing one of the virtual sides of the available platforms. Consequently, with rare exceptions, mainly in the domain of open public data, value meant monetization and economic value, with little attention to the dimensions of public and social value.

The AEGIS project, due to its attention to public safety and personal security, faces the challenge to integrate these different value dimensions: on the one hand, business partners can and should obtain economic benefits that; on the other hand, these benefits have a source in the social and public value for data access and use guaranteed by the platform. Taking these issues into account, we briefly present the early steps of the AEGIS path to identify sustainable business models for big data, that will be completed in future blogposts, likewise. The path aims to provide insights from the AEGIS experience to other ventures or consortia on elements worth discussing and considering to identify business models for big data value chains for public safety and security.

An initial hypothesis of business models for AEGIS has been outlined in the first year of the project (2017), describing it as “a service marketplace and big data-enabled business intelligence creation space for all stakeholders across the PSPS value chain”. In principle, a AEGIS target infomediary business models (Afuah & Tucci, 2000; Janssen & Zuiderwijk, 2014; Rappa, 2001) connecting data providers and users through a mix marketplace and subscription business models. It is worth noting that in a marketplace business model it is relevant to recruit vendors (in this case, users as data providers) and monetization is based on a commission per sale; whereas, subscription asks for a focus on customization and maintenance of the services (in this case, business intelligence solution), and monetization is based on the time of access and features used. Thus, providing users with the following features:

  1. flexibility in terms of data formats the platform can handle (Marketplace feature);
  2. discoverability, acquiring and consumption of interesting data services and seamless combination under a PSPS semantic context (Marketplace feature);
  3. selection from predefined options and the application of various algorithms on the cloud targeting both generic and more specific domain needs (Subscription feature);
  4. intuitive easy to create visualisations, through a set of available visualisation options, configurable to an extent and easy to combine in user created dashboards (Marketplace and Subscription feature).
  5. export the visualisations and analysis results for easier consumption and sharing with others (Marketplace and Subscription feature).

Then, the following early elaborations of the AEGIS mission and value proposition have been proposed

  • AEGIS aims to drive a data-driven innovation that expands over multiple business sectors and takes into consideration structured, unstructured, and multilingual datasets, rejuvenate the existing models and facilitate all companies and organizations in the PSPS linked sectors to provide better and personalized services to their users. (AEGIS Mission)
  • Hence AEGIS aims to develop a curated, semantically enhanced, interlinked and multilingual data platform for PSPS – to allow businesses and developers to provide better and personalized services to users. (Preliminary AEGIS Value Proposition)

Compared to current players in the data platforms competitive environment, such as, e.g. data.world (whose goal is to create a data-driven culture), the focus on “data-driven innovation” in Public Safety and Personal Security  (PSPS) sectors is relevant to differentiate the AEGIS proposals and focus on the above-mentioned different facets of “value”. Accordingly, the AEGIS perspective sees data-driven innovation as “personally” (thus, secure and private, with control over disclosure) accessible and not bounded by technical (advanced knowledge of data management, statistics, etc.) or technological issues (advanced knowledge of big data infrastructure components), especially in PSPS related businesses or organization, where also lay users or managers with no data scientists background are called to take action in decision-making or service proposals/design.  

The focus on tech-wise non-advanced users do not prevent the use of the platform by advanced users. Actually, considering the evolution of the business model of the AEGIS platform as first a “Two-sided platform” to further develop it as a “Multi-sided platforms” (Bharosa, Janssen, Klievink, & Tan, 2013; Eisenmann, Parker, & Van Alstyne, 2006; Hagiu & Wright, 2015), due to the service side of AEGIS,  we can see an opportunity, for example, for advanced data scientists (acting as suppliers) to provide their datasets elaborations (e.g., views) for a fee to tech-wise non-advanced users (acting as customers) or vice-versa these latters providing their datasets for advanced elaboration to advanced data scientists, under a collaboration agreement enforced by the platform itself. In any case, the business model should support network effects to increase the number of datasets offered as well as the number of users demanding for them. As to these issues the above-mentioned features should be oriented towards the building of accessible (also in terms of channels: e.g., via mobile) and connectablepersonal project spaces (i.e. with “must have” security and privacy features that allow easily to decide when, how, and what to connect within each space),which should enable the platform dynamics just exemplified.

 

Blog author: Gianluigi Viscusi (research fellow at CDM-EPFL)

 

 

References

Afuah, A., & Tucci, C. (2000). Internet Business Models and Strategies. Boston: McGraw-Hill College.

Bharosa, N., Janssen, M., Klievink, B., & Tan, Y. (2013). Developing Multi-sided Platforms for Public-Private Information Sharing: Design Observations from Two Case Studies. Proceedings of the 14th Annual International Conference on Digital Government Research. New York, NY, USA: ACM. Retrieved from http://doi.acm.org/10.1145/2479724.2479747

Eisenmann, T. R., Parker, G., & Van Alstyne, M. W. (2006). Strategies for Two-Sided Markets. Harvard Business ReviewOctober, 1–12. https://doi.org/10.1007/s00199-006-0114-6

Hagiu, A., & Wright, J. (2015). Multi-sided platforms. International Journal of Industrial Organization43, 162–174. https://doi.org/http://dx.doi.org/10.1016/j.ijindorg.2015.03.003

Janssen, M., & Zuiderwijk, A. (2014). Infomediary Business Models for Connecting Open Data Providers and Users. Social Science Computer Review32, 694–711. https://doi.org/10.1177/0894439314525902

Rappa, M. (2001). Business models on the web: Managing the digital enterprise. Retrieved from digitalenterprise.org/models/models.html

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