Innovacion abierta:
endavant i seny!
David Osimo, Laia Pujol
Open Evidence
1-12-2014 - DKV

Startup y grandes
empresas: dos mundos
incompatibles?
Kodak Instagram
Created in 1888 Created in 2010
Top value: 30B $ Top value: 1B $
Top employees:
Top employees:
145.000
18
Today bankrupt Today part of
Facebook

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
! "#$%&' (
) *(
+, -. %/, (
0 "1 2, -() *(" +, -+(
5) /%#$(
3%4%&#$(
67#$) 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
4.4 ZB 44 ZB
Data from embedded systems (IoT)
© IDC Visit us at IDC.com and follow us on Twitter: @IDC 10
Data on the
cloud 20%
Data on the
cloud 40%
22%
37%
Share of useful data
on total
2%
10%
2013 2020
Source: IDC for EMC 2014

Examples of data: Big Data Market grows 6
times faster than the traditional IT market
Big Data Technologies and Services Market, worldwide
© IDC Visit us at IDC.com and follow us on
Twitter: @IDC
11
€ Bn
7.2
23.7
2012 2017
Source: IDC 2014
2.3
4.3
2.7
2013 - € Bn
hardware
software
services

Vertical Market Big Data Heatmap
Western Europe
Volume Variety Velocity Value
Intensity 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
VC research training incubators other services regulators
Data market
Data landscape
Data
holders
Gov,
Personal,
Scientific,
Business,
Sensor
data
Marketplaces
Knoema Quandl
Dandelion
Europeana
ICT enablers: Radoop Talend Sensaris
Analytics
Teralytics ; SAS Captain
Dash
Datasift ; Spaziodati
RapidMiner
Vertical apps
Exelate
Kreditech
Mendeley
Doctoralia
Data Users
Gov
Industry
Civil society
Enabling players
Cross infrastructure
Amazon MS-Azure SAP Google IBM

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
1000
100
10
1
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
implementacion
de alta calidad,
usabilidad y design
Metodos robustos
para evaluar input,
output y impacto

Gracias
dosimo@open-evidence.com
www.open-evidence.com
@osimod