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Innovacion abierta:
endavant i seny!
David Osimo, Laia PujolOpen Evidence
1-12-2014 - DKV
Kodak Instagram
Created in 1888 Created in 2010
Top value: 30B $ Top value: 1B $
Top employees: 145.000
Top employees:18
Today bankrupt Today part of Facebook
Startup y grandes empresas: dos mundos incompatibles?
Trend 1: sharing
economy
Source: the economist
Los prosumers
El usuario final como provededor de:
• storage & server capacity (P2P), • connectivity (wifi sharing, mesh networks),
content (youtube),taste/emotion (Amazon), contacts (Linkedin), relevance (Google Pagerank), reputation & feedback (Tripadvisor),
– goods (eBay), – Funding (kickstarter)– Habitaciones (AIRbnb)– Taxi (Uber)
» Anything else...
Llegando a todos los sectores
Source: http://blog-en.mila.com/2014/09/30/sharing-economy-in-europe/
Servicios que mejoran cuanta mas
gente los utilizes
6
“Hands-on care by
health professionals
can't scale. One-on-
one advice from
professional
intermediaries, like
librarians, can't scale.
Networked peer
support, research,
and advice can
scale. In other words:
Altruism scales.”
Susannah Fox
! "#$%&' () *(
+, -. %/, (
0 "1 2, -() *("+, -+(
3%4%&#$(
5) /%#$(
67#$) 4(
http://egov20.wordpress.com/2011/11/03/collaborative-e-government-public-services-that-get-better-the-more-people-use-them/
Generando dinero
Consumo collaborativo
Trend 2: big data
• More data
• More granular, specific data
• Real time data
• From different datasets
• “At its core, big data is about predictions”
Growth of the Digital Universe from 2013 to 2020
© IDC Visit us at IDC.com and follow us on Twitter: @IDC 10
4.4 ZB 44 ZB
Data on the cloud 20%
Data on the cloud 40%
22%37%
Share of useful data on total
2%
10%
2013 2020
Data from embedded systems (IoT)
Source: IDC for EMC 2014
Examples of data: Big Data Market grows 6 times faster than the traditional IT market
© IDC Visit us at IDC.com and follow us on Twitter: @IDC
11
7.2
23.7
2012 2017
€ Bn
Big Data Technologies and Services Market, worldwide
Source: IDC 2014
2.3
4.3
2.7
2013 - € Bn
hardware
software
services
Vertical Market Big Data HeatmapWestern Europe
Volume Variety Velocity ValueIntensity of
Big Data Drivers
Finance
Process Manufacturing
Discrete Manufacturing
Retail/Wholesale
Telecom/Media
Utilities/Oil & Gas
Prof. Services/Transport
Government/Education
Healthcare
Total
Hot
High
Medium
Low
Based on mean scores assigned by survey respondents
El mercado de datos
Data landscape
Data market
Data holders
Gov, Personal, Scientific, Business,Sensor data
MarketplacesKnoema Quandl
DandelionEuropeana
ICT enablers: Radoop Talend Sensaris
AnalyticsTeralytics ; SAS Captain
DashDatasift ; Spaziodati
RapidMiner
Vertical appsExelate
KreditechMendeleyDoctoralia
Data Users
GovIndustryCivil society
Enabling players
Cross infrastructureAmazon MS-Azure SAP Google IBM
VC research training incubators regulatorsother services
Predecir peliculas
More data beat better algorythm
Predecir crimenes
Hasta predecir las hospitalisaciones
Data science as a service
Llegan los “datavores”
• “Firms using data-driven decisionmaking have 5-6% higher productivity” (Brynolfsson et al 2012)
• “Datavores are 25 per cent more likely to say they launch products and services before competitors” Nesta 2013
• But “The coolest thing to do with your data will be thought of by someone else” – Rufus Pollock
Trend 3: social computing
A different idea of technology
• Traditionally, computing is about automation: technology substitutes humans, humans should adapt
• Social computing is about augmentation: technology adapts to and augments human capacity (Engelbart 1962)
20
Social Machines
21
“The brilliance of social-software applications like
Flickr, Delicious, and Technorati is that they […]
devote computing resources in ways that basically
enhance communication, collaboration, and
thinking rather than trying to substitute for
them."
http://www.technologyreview.com/InfoTech/wtr_14664,258,p1.html
Enterprise 2.0: accessing micro-
expertise
22 innocentive.com
Traditional Enterprise apps Enterprise 2.0
Mission Enable pre-defined groups/teams working
closely together and/or relatively formal
collaborative relationships.
Enable individuals to act in loose, ad-hoc
collaborations with a potentially very large
number of others.
Relationship to
organisational hierarchy
Tools reflect the organizational hierarch
and roles within them.
Little link to organizational hierarchy
Control of structure Centrally imposed and generally rigid
controls
Emergent (=emerges and evolves)
Content originated by Specialists with authorisation All users - also emergent
Control over users Users/participants are fixed and their roles
pre-defined.
Roles by choice and can evolve over time
(emergent)
Control mechanisms Formal, rules Norms, examples
Change of content
timescales
Slow Rapid
Delivery model Typically on premise commercially
licensed software
Range of delivery models including on premise,
cloud, commercial, open source, stand-alone,
suites or add-ins to E1.0 systems
Range of participants Colleagues with similar or complementary
job roles
Anyone in the organization and potentially
outside (e.g. customers)
Links between
participants
Peer or hierarchical Links can be strong to non-existent (or
'potential') within the group
Typical tools Knowledge management, knowledge
repositories, decision automation
Blogs, wikis, social networking, prediction
markets
Communication patterns One-to-one Many-to-many
Effects of enterprise 2.0
• Black and Lynch estimate that changes in organizational capital may have accounted for approximately 30 percent of output growth in the manufacturing sector.
• Gant, Ichiniowski and Shaw find robust evidence of positive impact of connective capital –defined as workers’ access to the knowledge and skills of other workers-on productivity (relevance for E2.0).
24
Porque abrirse?
Source: Open Evidence / UNDP
Thematic knowledge: peer to patent
Decision rests with gov(USPTO)
Geographic coverage
User experience
IT skills
Many eyes and many hands
Networks and contacts
Trends que se refuerzan mutuamente
Big data
Social computing
Sharing economy
Una nueva manera de
innovar
Grandes empresas crecen
• internal ecosystems for accelerated innovations,
• Enterprise 2.0 platforms
• incubator/accelerator programs,
• seed-funds,
• cross-disciplinary networks,
• ‘beyond the pill’ business models
• Intrapreneurship
• coworking
• BBVA, Bohringer, Deutsche Telekom, BBC, Johnson & Johnson, Telefonica, Philips...
Fuentes: www.intrapreneurshipconference.com/cbinsights.com
Pero no es abertura total y indiscriminada!
Fuente: http://ebiinterfaces.wordpress.com/2010/11/29/ux-people-autumn-2010-talks/
Ejemplo: PeerToPatent
La Decision queda en el gobierno (USPTO)
Como abrirse
Source: Open Evidence / UNDP
No importa cuantos, importa quien
Ignoran
Leen
Comentan
1
10
100
1000
Datos abiertos
1 reutilizador puede ser suficiente
Source: www.bbc.co.uk/news/magazine-22223190
“Why investing on it until we don’t have clear ROI?”
“Why investing on it until we don’t have clear ROI?”
Kodak CEO, 2005
Lo que se necesita
Experiencia para decidir cuando y
como abrirse
Instrumentos de implementacionde alta calidad,
usabilidad y design
Metodos robustos para evaluar input, output y impacto
Gracias
dosimo@open-evidence.com
www.open-evidence.com
@osimod
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