WP7– Business Models

1. WP7– Business Models Julia Doll, SAP AG, 26.06.2014

2. WP Objectives To produce and evaluate possible business models for public-private partnership and support the adoption of these through standard tender templates based on the approach defined in WP3 – note also the iteration between this WP and WP8. Specific goals • Understand the financial implications of ‘utility computing’ for vendors and customers • Define mechanisms for quantifying and controlling risk • Assess the viability of standard cloud-service procurement templates across jurisdictions

3. Effort Contribution • Lead Beneficiary: SAP WP7

4. Recommendationsfrom P1 review • The type of services definition and their cost estimation, the requirements gathered in WP3, should be of reference (and eventually updated) • In the second period of the project, the Framework Contract solution should be analysed with attention to anti-trust and competition regulations • The scenario where a PPP plays a coordination role is expected as well as possible launch of PPI (public procurement for innovation) for cutting edge solutions (for a European Science Cloud)

5. Implementation of recommendations • Current service types and costs were considered in business case and in the business model roadmap as a starting point • Updated services: service extension based on roadmap from Iaas to InfoaaS • Proposed procurement models which will be elaborated on in potential future projects

6. Scientific/technical achievementsand their impact • Business modelroadmap • Proven economic viability of Generic Cloud Computing for European Big Science • Transition to InfoaaS based on roadmap to critical mass • Defined broker, partner and platform roles for effective business operations • Proposed procurement model which will be taken forward in the potential Picse project

7. Deliverables and Milestones – Period 2

8. Overall modifications, corrective actions, re-tuning of objectives D7.3 Focusing on only one flagship sponsor: CERN(By choosing the organisation with assumed lowest costs we were able to show significant results) D7.4 Elaborate on business models roadmap (Since we proposed a business model roadmap it was crucial to show the transition between the first business models, instead of focusing on further business cases )

9. Exploitation and use of foreground(Results of Period one and next steps) • D 7.1 • Issue: Procurement • Challenge: Switching Costs, Investment Risks / Commitment, Transp. • D 7.2 • Procurement Models • Potential Broker Roles • Business Model Roadmap • D 7.3 • Cost Analysis of current business model Generic Cloud Computing for European Big Science • D 7.4 • Transition from current business model to future business model InfoaaS based on network effects and reaching critical mass

10. Collaboration with other beneficiaries

11. Contribution to the dissemination of project results • We supported a master thesis on Helix Nebula focusing on the establishment of partner ecosystems written by Michael Blaschke. This Master thesis might be integrated into a scientific paper later in the year • Internal & external SAP News article on business model innovation to SAP customers and partners which will refer to the success of the project and its webpage • Journal article (360 degree) using Helix Nebula as case study for successful business model innovation

12. Business Model Innovation for Helix Nebula D7.2

13. HN Business Model Options • Information as a ServiceThe selling of aggregated and analyzed data in the cloud • Generic Cloud Computing for European Big ScienceProvision of data capture and processing that elastically meet the need of big science’s growing demand • Versioned Cloud Computing for Science & EducationAddressing the entire world of science and education through explicit versioning of prices, revenue models, SLAs, and services • Worldwide all-in-one enterprise cloudPlatform that offers a unique resource to governments, businesses and citizens • Collaboration & Communication Platform for Science & EducationThis BM combines social networking, collaboration, data interchange, and secure communication integrated in one web frontend • Application CrowdAmarketplace where application users can outsource or “crowdsource” domain-specific development projects to thousands of developers from around the world • Brand ManagementEstablishment of a brand to utilize advertising and franchising as a revenue model

14. Information as a Service Capturing, processing, analyzing and archiving of highly attractive data from ESA and EMBL occupies the potential to cooperate with further data providers in order to enrich the data in its context. The selling of resulting data sets and knowledge is evaluated as the most promising BM in terms of market need, impact on critical mass, differentiation, and thought leadership. Yet, the required time is high. • Who? • How? • What? • Who? • Customers • The confirmed customers‘ data (CERN, ESA, and EMBL) is context enriched with ... • ... further providers‘ data sets (e. g. Unesco, World Bank, OECD) ... • ... which is hosted on HN‘s cloud ... • ... and acquired, standardized, and combined by a data broker role to be assigned. • Partner & Customer Expansion: • The finding an binding of further valuable data providers of e.g. financial data is a key success factor. • According to the expert evaluation extensive marketing is necessary and worthwhile as the “ingredient brands” ESA and EMBL are expected to raise high interest and attention. • Data Processing: • Selling enriched data requires huge efforts to ensure data quality for the intended use in commercial operations, decision making and planning. • The more profitable option of selling knowledge induces data mining involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. • Double-Sided Improvements: • As data is accessible to a greater public, researchers’ problems of identifying missing research instrumentation and research questions can be mitigated. • Core business improvement is achieved by new data sets and knowledge concerning issues like urban development, disaster reduction research, teaching material, military movements, soil moisture etc. • Business Model Strengths: • Being evaluated with highest “impact on the market” among all BMs, the opportunity for a differentiated, thought-leading platform for data and knowledge sale truly exists. • Easy data and tool access yields in community growth. • Business (B2B) including • Manufacturing • Strategy Consulting • Financial Sector • Health Sector • Oil Industry etc. and … • … Public (B2A) including • Universities • Military • Governments • Schools etc. … • … customers are evaluated to have a very high need. • Partners • Operations • Value Prop. Value Creation • Infrastructure cost (virtualization, servers, storage, networking, electricity, licensing) are extremely high recurring cost. • Staff costs for data standardization, context enrichment, and mining also appear recurrently. • Especially the exploitation of a first mover advantage causes high initial one time cost for marketing campaigns. • The role holder will receive a percentage of the revenues that are gained in this BM for lowering risks and cost and raising revenues. • Transaction-based services are of interest for one-time needs. • Preemium subscription ensures updates to follow latest data. • Crowdsourcing allows for data provisioning by anybody. • Data enrichment could be triggered by free or low price cloud access if data is made available to be aggregated and sold. • Costs • Revenue Value Capture • Why?

15. Evaluation Framework We developed an evaluation framework that is based on two dimensions. The “impact” of the BM option to the market is described from the customers’ point of view, whereas the “ease of implementation” is seen from the suppliers’ point of view. The approach allows combining qualitative and quantitative criteria that were defined specifically for the project in collaboration with the HN suppliers. 1: very low / very critical 2: low / critical 3: medium / neutral 4: high / positive 5: very high / very positive

16. Consolidation Matrix *Bubble size:Revenue Potential 1: very low / very critical 2: low / critical 3: medium / neutral 4: high / positive 5: very high / very positive

17. Business Model Roadmap Short Term • Generic Cloud Computing for European Big ScienceObjective of Helix Nebula. Further satisfying needs and requirements of CERN, EMBL and ESA • Information as a ServiceBusiness model of interest to ESA and potentially other data intensive research organization Long Term • Versioned Cloud Computing for Science & EducationAddressing the entire world of science and education through explicit versioning of prices, revenue models, SLAs, and services • Worldwide all-in-one enterprise cloudThe provision of resources to governments, businesses and citizens is a vision of Helix Nebula and hence, the extension of Helix Nebula to these customer segments could be incorporated as a long term strategy

18. HN Overarching Broker Roles • Trading Role (EGI)A trading exchange platform that enables infrastructure provider to sell and buy computing capacity in order to better meet the customers’ needs and to earn money with disused resources  • Yellow Strom Role (Non-HN Commercial Provider)Buys the offerings from HN providers to create frequently demanded bundles or single services ex ante and sells them to the end customer without making transparent from which provider the services come (reseller model) • Work Group Management (EGI)Assigns tasks and coordinates results between all HN partners’ individual work groups. For example the distribution of technical standards, central governance rules, definition of customer segments, service catalogue and a supply side expansion process for Europe and other continents, if approved • The Up-/Cross-Seller (EGI)Exploits the up-/cross-selling potentialsbetween the various services by finding suitable services based on customer’s data analysis • Financial BrokerA financial broker integrates quotas/billings, passes through payments and splits revenues • Law BrokerLegal operations concerning European and national antitrust policies, liability within the ecosystem, taxes and HN’s juridical status could be centrally managed for all providers

19. Procurement Model Demand Supply Genom Analysis IaaS1 Providers Earth Observation Third Party • PaaS2 & SaaS3 Prov. Atlas Experiment Long Tail of Science EMBL: Restricted tender ESA: Through prime contractor, establishing a procurement relationship CERN: Restricted Tender, enabled to procure for other research organizations - addressing long tail of science Implementation of framework contracts or PPP take to long Note: Tender does not assign budget to individual suppliers

20. Economic Viability D7.3

21. Business Case Calculation The private cloud based on OpenStack (IaaS) and Zenodo, a digital repository that offers permanent storage for research data for any science domain (SaaS). The private cloud is relying on other departments that are responsible for tendering, purchasing, customizing, deploying, operating, monitoring and maintaining (new) hardware. The SaaS solution Zenodo is in turn naturally depending on the Infrastructure (OpenStack cloud) Technical specifications: • Private cloud (OpenStack): A virtual node with 2 cores, 8 GB memory, 80 GB local disk space (one 8th of a node) • Zenodo service: 10 VMs, 1 PB of disk space (Dropbox-like), 1.5 PB of Archive Storage

22. Business Case Results Note: Even without gathering all cost components, HN prices for the Zenodo service are very competitive

23. Roadmap to Critical Mass D7.4

24. Network Effects in INFOaaS Experts &Non-profits Governments Data Users TailoredData & Research Requests TailoredServices TransparencyBest PracticesGap IdentificationCore CompetencyEconomiesofScaleGovernanceKnowledge Sharing Revenue Data • Technology Partners Data Providers Quality ofResearch/Inter-organisational Research New Research Questions;System Insight Data UserCommunity Data ProviderCommunity Data Revenue Cloud Financial Partners Data Services:Variety & Quality LawsDirectivesCitizen Alerts FederatedInfrastructure Platform Operator Platform Sponsors Funding & Tax Reduction Content Operators Risk Warnings Broker Roles Consulting Partners All trade marks gratefully acknowledged Pooled Cloud Computing Services

25. Roadmap: OverviewStrategic Steps towards Market Tipping Size ofNetwork Implementation: Move Early Adoption: Create User Balance Scaling: Build Critical Mass Competition: ExtendBusiness Scope 1 2 4 3 4 3 2 1 Time Critical Mass A community is expected to have enough momentum to become self-sustaining at about 15% from the target community opting in, whereby critical mass is linked to consumer’s expectations regarding the performance of a product or service, and the expected final size of the network (Mahler and Rogers 1999). As long as the critical mass point is not exceeded, demand synergies can only develop to a limited extent (Schoder 2000).

26. Summary • Shaped the future direction of Helix Nebula and the types of services provided • Defined the implementation roadmap and the interrelation between proposed business models • Defined Procurement Models that will be elaborated in a potential follow-up project • Determined Broker Roles to ensure smooth business operations • Proven economic viability for suppliers and desirability for customers