Siemens Corporate Technology | October 2nd 2013
Open Innovation A Sustainable Approach?
Thomas Lackner
Open Innovation & Scouting
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The global R&D village
R&D spending in 2012
Battelle/R&D Magazine 2012, total $1,402 trillion
• R&D figures Siemens 2012: €4,2 billion,
29.500 researchers in 190 locations. More than
2000 university co-operations , 9000 inventions
• For every experienced and high qualified R&D
expert within Siemens you will probably find
more than 200 experts outside of Siemens
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Bill Joy, co-founder of Sun
microsystems
Joy‘s law
• No matter who you are, most of the
smartest people work for someone else
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Drivers for Open Innovation
 Shift of R&D from Corporates to SMEs (5% -> 25% in 25ys)
Globalization
 More than 2 million engineer graduates annually (CHN, IND)
 China set to surpass U.S. in R&D spending in 10 years
 Open alliances are formed to gain speed (Android, Continua)
Speed
 Fast growing internet business models (Facebook, Research
Gate, Twitter, Groupon)
 Digital data (# of web servers 62 Mio to 313 Mio in last 5 years)
Technology
 Distribution of knowledge (exponential computing power to
process flood data)
 Web 2.0 platforms for crowd sourcing
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Crowd sourcing – some examples from history
Competition – Longitude Prize
John Harrison
Marine chronometer, 1737
Collaboration – Oxford English Dictionary
James Murray, ~1880
• Measuring of longitude was very inaccurate
and caused severe accidents (18th century)
• 1857: Richard Trench, Philological society,
proposed comprehensive dictionary
• Prize by British Parliament £20.000 (equiv. to
£2.66 Mio today) for accuracy of ~50 km)
• Shortcomings: obsolete words, synonyms,
earliest usage, quotations etc.
• Financial support also for productive work on
solution, many persons benefitted
• 1879: James Murray made public call to
contribute and submit “quotation slips”
• Total spending £100.000, significant awards
to 10 participants, but no winner
• Result after 70 years: 414.825 words,
1.827.306 slips, many thousands volunteers
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Crowd sourcing – today facilitated by the internet
Competition – Netflix Prize
Collaboration - Quirky
• Improvement of own recommendation engine
by > 10%, $1 Mio award (in 2009)
• Business case (+ $90 mio revenue p.a.)
• Platform for social product development
• Ideas and design are crowd-sourced
• Revenues shared with the product inventors
and influencer
• Training data: set of 100,480,507 ratings that
480,189 users gave to 17,770 movies
• 40.000 participants, 150 countries, 3 years
• Winner: combination of 800 algorithms
developed 7 participants worldwide
• 04/2012: implementation stopped due to
complexity and shift of business strategy
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• Founded in 2009, VC funding $90 million
• 120 employees, 400.000 users
• Most successful product: Pivot Power,
invented by Jake Zien and 708 influencers,
earning Zien several $100.000
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Siemens’ path to Open Innovation
~1900
2008
Siemens Technology
Accelerator
First university
cooperation
First lead customer
workshop
Management of
employees‘ ideas
Crowdsourcing
TechnoWeb2.0
First centers of
Competence
E-Broker / Scouting
The traditional innovation rules
New options in the "Open Innovation" game:
 Focus on bilateral partnerships
 Workshops or mailboxes as frame
for ideation
 Default: Maximize IP protection





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Use unobvious sources
IT-based methodologies ("Web2.0")
New levels of scalability
Enhanced speed in the dynamics of networks
Balance between IP protection and openness
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Internal, external Idea Contests & Jams @ Siemens
Internal
contests
External
contests
2009
2010
2011
Designs for emotional LED
solutions (Osram)
Sustainable company and
portfolio ideas (Siemens)
Smart Grid Innovation
Contest (part I & II)
Products & solutions for
urban markets and city development (Siemens India)
Future Business opportunities for high-voltage
switchgears (E T HS)
Innovation
Jams
Business opportunities for
the "Future of Hubs"
(Siemens Mobility)
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Anti-Piracy issues &
technical & legal
solutions
March 2013
2013
2012
Data Driven Services
Business opportunities for
"Future of Metals" (I MT)
Disruptive ICT trends
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Smart Grid – Call for Proposals from Universities
Facts and Figures
Lessons learened
High Quality of submissions (10/2011)
Ownership
•
•
•
•
•
• Management support -> Project Lead from BU
• Early involvement of stakeholders -> PM, BD, R&D.
389 registrations
207 universities from 36 countries
172 proposals submitted
23 accepted proposals
Name:
Michael Heiss
10 contracted research
co-operations
Confidentiality
Emotions Seismograph / Timeline
Emotions: „stock-market price“
estimated Return of Invest based on your own investment

1.4.
15.6.
21.7.
15.9.
4.10.
30.11.
today
14.12.
expected future
Meet the top motivated
winners in Berlin
Motivating meeting with
Dr. Hausmann
positive
Kick-off
High quality of
submission
Decision: no cosponsering of research
via company project
negative

Idea Contest Online
13.4-15.6.2011
Recruiting of Submitters
Jury Preparation
21.7.2011
Evaluation of detailed proposals
in Wiki
Award Ceremony
Berlin 15.9.2011
CfP Online
4.10.-30.11.2011
Contracting
© Siemens AG 2011. All rights reserved.
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Dec-11
CT O OI
“Call-for-Proposals
are a great method to
indentify the best
university partner”
„I thought I knew the
best universities but
obviously didn’t“
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Timing
• Start of contest -> align with Siemens budget planning
• Proposal submissions -> “delay” accept/deny decisions
Change of security policy
on 1.9.2011 -> publish
only topic clusters
Topic Definition for CfP
Preparation
• Concrete search field description -> disclosure of
strategy vs quality of submission
• Secure data exchange -> IT-platform with ease of use
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• Target communication -> SCOPUS gives access to all
the scientists who published in the search field.
Optimization
• Pre-qualification process -> Only qualified submitters
are asked to send detailed proposal
• End to end process/workflow support -> Very high
usability required for the web tool (submitters, backend
operations)
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Siemens Social Media network TechnoWeb
Examples
 Comput. Fluid Dynamics (E, H, I, IC, CT)
 Siemens Product. System (E, H, I, IC, CT)
 Nondestructive Evaluation (E, H, I, CT)
 Technology Scouting (CT, H, I, E, IC)
 Open Innovation (CT, H, I, E, IC)
Key Figures
 > 1400 technology networks
 > 35.000 members
• Figures indicate the # of networks with at least
one member of A and B
• In 235 networks all sectors and CT participate
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 Ø 8 Replies / Urgent Request (corporate
problem solving)
 Ø 35 minutes for first response
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Complete methodological framework for ''Visioning
and Scouting''
Broad
focus
Exemplary question
Suitable methodology
Potential answers
Future industry trends
Scenario techniques
Consolidated view
Timeframe: ~10 years
 Pictures of the future
 PoF Drive Technology
Hunting field: E.g.,
''The energy internet ...''
 Trend monitoring
 PoF Mobility
 Delphi, market research
 PoF Lighting
''Visioning
& Trends''
 …
Potential business
ideas and technologies
Crowdsourcing
Cooperation partners
Timeframe: 3–5 years
 Co-ideation
 Future of hubs (I MO)
Hunting field: E.g.,
''Micro Grid stability …''
 Call for proposal
 Smart grid (I&C SG)
 Hunting Field Landscaping
(Desktop approach)
 Urban markets (IND)
Technology market place
Solution
 Request for Proposal
(Market place approach)
 ~20 RfPs with BU
and CT
 Urgent Request
(TechnoWeb, TechnoSearch)
 E.g., Thermal pumped
heat storage system
(insulated gravel)
The missing piece
of innovation
Timeframe: <2 years
Hunting field: ''Energy
storage 30 MWh…''
Narrow
focus
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''Open
Innovation
& Scouting''
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Market places for Technology Scouting
• A rising number of market places connects seekers with
idea/solution providers (this will facilitate scouting)
• Specific needs can be addressed by different OI
approaches (grand challenges, expert teams, RfP, patent &
technology commercialization, idea generation, intelligence
on emerging technologies, technology landscaping)
• A clear problem / need statement is requested (this helps
to better understand the problem)
• Confidentiality issues have to be considered (confidential
vs non-confidential, company branding, message for
competitors)
• Trust has to be developed between company experts,
intermediaries and solution providers (avoid NIH, fair play
with community)
• Expectation has to managed properly (what results would
satisfy the expert)
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Desktop approach for Technology Scouting
Proprietary Databases
Primary
source
> 50 Mio docs (Scopus,
RDDS, IPAS-BUS)
MergeFlow
TechnoWeb
> 100 databases, >100.000
offerings (SBIR, EEN, etc.)
>3GB docs p.d. (websites,
blogs, forums, rss feed.)
~ 30.000 experts (Enterprise
social media platform)
 Search term-based
screening of external
technology marketplaces
 Continuous screening of
changes in publicly
available sources
 Requests in internal
communities and informal
discussion
 Patent database
 Business-driven
information gathering
(direct contact to target)
 High-end monitoring
technologies based on
semantic technologies
 Posting of offerings in
Technology Scouting @
Siemens
Key-Experts
Technology offerings
Emerging activities
Key
 Access to publications
methodology from reputable
universities, companies
Outcome
Public Databases
Use-cases, BU contacts
Scouting
Platform
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OI Challenges to be solved in future
• Establish a culture of Open Innovation (trust, give & take, failure)
Company
• Shift from fixed to variable assets. Balance internal with external R&D
• Open Innovation & Scouting as elementary part of innovation process
Market
• New business models / incentives for commercialization of
technologies
• More open forms of R&D-alliances (universities, competitors, supplier)
• Specialization of intermediaries (offering, network, reputation)
Technology
• Improved search capabilities (semantic, technology map, syntax, entity
generation, search logic etc.)
• Trend detection technologies
• Seamless integration of tools to support workflow
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