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