WP7– Business Models

Julia Doll, SAP AG, 26.06.2014

1

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 customersDefine mechanisms for quantifying and controlling riskAssess the viability of standard cloud-service procurement templates across jurisdictions

2

Effort ContributionLead Beneficiary: SAP

WP712%

Person-Months per Participant

Participant Person-months

SAP 23.00

TOTAL 23.00

PM24PM2

WP7

3

Recommendations from 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 regulationsThe 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)

4

Implementation of recommendations

Current service types and costs were considered in business case and in the business model roadmap as a starting pointUpdated services: service extension based on roadmap from Iaas to InfoaaSProposed procurement models which will be elaborated on in potential future projects

5

Scientific/technical achievementsand their impact

Business model roadmapProven economic viability of Generic Cloud Computing for European Big Science Transition to InfoaaS based on roadmap to critical massDefined broker, partner and platform roles for effective business operationsProposed procurement model which will be taken forward in the potential Picse project

6

Deliverables and Milestones – Period 2Type Del.

noName Nature Dissemination

levelDate Delivered

Deliverable 7.2 Synthesis and Analysis of Overall Business Models

Report PU 16.09.2013

Deliverable 7.3 Costing exercise comparing in-house vs. cloud based operation for the CERN flagship use-case and incorporation of qualitative cloud adoption criteria targeting prospect members

Report PU 20.02.2014

Deliverable 7.4 Information as a Service – Towards Value Co-Creation in a European Cloud Computing Platform Ecosystem

Report PU 03.02.2014

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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 )

8

Exploitation and use of foreground(Results of Period one and next steps)

D 7.1

1. Issue: Procurement2. Challenge: Switching Costs, Investment Risks / Commitment, Transp.

D 7.2 1. Procurement Models2. Potential Broker Roles3. Business Model Roadmap

D 7.31. Cost Analysis of current business model Generic Cloud Computing for

European Big Science

D 7.41. Transition from current business model to future business model

InfoaaS based on network effects and reaching critical mass

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Collaboration with other beneficiaries

Consortium

• Business Case(CERN)

• Procurement(T-Systems)

ESA

• Network Effects and reaching critical mass

EGI.eu

• Interoperability of public and commercial providers

10

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 yearInternal & external SAP News article on business model innovation to SAP customers and partners which will refer to the success of the project and its webpageJournal article (360 degree) using Helix Nebula as case study for successful business model innovation

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Business Model Innovation for Helix Nebula D7.2

HN Business Model Options Information as a Service

The selling of aggregated and analyzed data in the cloud Generic Cloud Computing for European Big Science

Provision 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 CrowdA marketplace 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

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Information as a Service

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Valu

e Ca

ptur

eVa

lue

Crea

tion

Why?

How? What? Who?Who?

•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.

•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.

Value Prop. CustomersPartners Operations

Costs Revenue

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.

• Revenue Potential: Direct vs. Indirect (Influenced / Cross – Selling)

• Customer acceptance / Brand fit• Portfolio Fit / Impact on Portfolio• Impact on Visibility / Traffic• Impact on Differentiation / Thought

Leadership• Impact on critical mass (network

effect)

Typical Criteria for “Impact of Option”’

• Costs (One Time vs. Recurring)• Risks (Technical, Financial, Legal etc.)• Time for Implementation• Organizational Fit• Synergies / Leverage of network• Privacy / Security Issues

Typical Criteria for “Ease of Implementation’

Evaluation Framework

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Question

Weigthing

Value medium 3.0 medium 3.0 medium 3.0 medium 3.0 medium 3.0 medium 3.0 medium 3.0 medium 3.0

How do you value the potential to raise attention without explicit

marketing campaigns?

What is the average over all

criteria taking into account the weightings?

0.3 0.2 0.05 0.05 0.2 0.1 0.1 1

How do you value the revenue potential?

How do you value the customers’

objective need of this sourcing

solution?

How do you value the customers’

subjective acceptance of the migration effort?

How do you value the customers’

subjective acceptance of

security issues?

How do you value the number of partners and customers

participating?

How do you value the novelty on the market and the distinction to competitors?

Revenue Potential

Customer Acceptance Impact on Critical Mass

Differentiation / Leadership

Visibility / Traffic ResultNeed Effort Security

Impa

ct o

f Opt

ion Criterion

Question

Weigthing

Value neutral 3.0 neutral 3.0 neutral 3.0 neutral 3.0 neutral 3.0 neutral 3.0 neutral 3.0 neutral 3.0

0.20.2

How do you value costs that appear on an ongoing basis?

RecurringOnetimeCosts

1

How do you value conflicts with your

organisation's strategy, structure and processes?

How do you value the required time until the first

service is sold?

What is the average over all criteria taking

into account the weightings?

0.2 0.1 0.1 0.1 0.1

Time Required ResultFeasability Expertise Legal

Ease

of I

mpl

emen

tatio

n Criterion Risk

How do you value initial investment costs?

How do you value the objectve teachnial

feasiblity with today's knowledge?

How do you value your organisation's

knowledge to realize the BM?

How do you value legal risks that might

appear?

Conflict with Suppliers

1: very low / very critical 2: low / critical 3: medium / neutral 4: high / positive 5: very high / very positive

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.

Consolidation Matrix

161: very low / very critical 2: low / critical 3: medium / neutral 4: high / positive 5: very high / very positive*Bubble size: Revenue Potential

2.5 3.0 3.5 4.0 4.52.5

3.0

3.5

Generic Cloud Computing for European Big Science

Versioned Cloud Comput -ing for Science & Education

Information as a Service

Application Crowd

Collaboration & Commu-nication Platform for Sci-

ence & Education

Worldwide All-In-One En-terprise Cloud

Brand Management

Impact of Option

Ease

of I

mpl

emen

tatio

n

Business Model RoadmapShort Term Generic Cloud Computing for European Big Science

Objective 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 & Education

Addressing 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

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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 potentials between 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

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Demand

Genom Analysis

Supply

IaaS1 Providers

PaaS2 & SaaS3 Prov.

Third Party

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

Procurement Model

Long Tail of Science

Atlas Experiment

Earth Observation

Implementation of framework contracts or PPP take to longNote: Tender does not assign budget to individual suppliers

Economic Viability D7.3

Business Case CalculationThe 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

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Business Case Results

In contrast to CERN in-house AWS Helix Nebula

Open Stack IaaS Service 1 year commitment + 19.4 times + 5.6 times

Open Stack IaaS Service 3 year commitment + 14.6 times + 3.9 times

In contrast to CERN in-house AWS Helix Nebula

Zenodo SaaS Service 1 year commitment + 30% - 13%

Zenodo SaaS Service 3 year commitment + 30% - 36%

Note: Even without gathering all cost components, HN prices for the Zenodo service are very competitive

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Roadmap to Critical Mass D7.4

Network Effects in INFOaaS

Pooled Cloud Computing Services

Platform Operator

Platform Sponsors

Content Operators

Broker RolesFederated

Infrastructure

Risk W

arnings

Funding & Ta

x Reducti

on

Data UserCommunity

Data ProviderCommunity

Quality ofResearch/Inter-organisational

Research

TransparencyBest Practices

Gap IdentificationCore Competency

Economies of ScaleGovernance

Knowledge Sharing

Experts &Non-profits

Data Users

Tailored

Data & Research

RequestsTailo

red Se

rvice

s

New Research Questions;System Insight

Data

Reve

nue

Data Services:

Variety & Quality Revenue Data

Cloud

Financial PartnersGovernments

Technology Partners

Consulting Partners

LawsDirectives

Citizen Alerts

Data Providers

All trade marks gratefully acknowledged24

Roadmap: OverviewStrategic Steps towards Market Tipping

Critical Mass

Size of Network

Time1 2 3

4

Implementation: Move Early

Adoption: Create User Balance

Scaling: Build Critical Mass

Competition: Extend Business Scope

1

2

3

4

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).

Summary

Shaped the future direction of Helix Nebula and the types of services providedDefined the implementation roadmap and the interrelation between proposed business modelsDefined Procurement Models that will be elaborated in a potential follow-up projectDetermined Broker Roles to ensure smooth business operationsProven economic viability for suppliers and desirability for customers

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