1© Bull, 2013
Andrew Carr, CEO Bull UK& IrelandAndrew Carr, CEO Bull UK& IrelandStephen Booth, Associate IT Director, Coventry UniversityStephen Booth, Associate IT Director, Coventry University
2© Bull, 2013
Think about this…….
Who are the superstars of the future?
Why do mathematicians confuse Christmas and Halloween?
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Context to Innovation…..
http://boost.bull.co.uk/video/
4© Bull, 2013
The amount of data created by individuals is significantly less than data created about themThe Digital Universe consists of:– 1.8 trillion gigabytes– 500 quadrillion files– Nearly as many bits of data in the Digital as the Physical Universe
1 gigabyte of stored content can generate a petabyte of un-stored transient data (e.g. digital TV signals)Whilst information continues to explode, [IT] budgets/resources remain stationarySales of George Orwell’s 1984 have increased 337% since the NSA story leaked
IDC View; Extracting Value from chaos, June 2011
Why is there data everywhere?
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The role of data within innovation
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I asked you to think about…..
Who are the superstars of the future?Data Scientists……..
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I asked you to think about…..
Why do Mathematicians confuse Christmas and Halloween?I will leave you to go figure……..
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How Do We Do Data?
We don’t do ‘Big Data’ – yet……
We do do Data AnalysisWe have used this to drive our own performance up the league tablesWe are in the business of selling education to students.We have to understand not just what the students of today want, but what those currently in primary school will want in 10 years time
We do do ResearchWe specialise in ‘Applied Research’We are very interested in collaborating with industry to drive innovation
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How Do We Do Innovation?
Two basic models of driving innovation
Traditional model – Closed Innovation
New Model – Open Innovation
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Closed Innovation Model
Research Investigations
Development
New Products and Services
Science & Technology Base
The Market
• Traditional strategy based on ownership and control• Reliant solely upon internal competences• Innovation is viewed as an isolated process• Research projects launched from the science and
technology base of the firm
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Open Innovation Model
Internal Technology Base
Other Firm’s Market
New Market
Current MarketExternal Technology Base
Technology Spin-offs
Outlicensing
• Chesbrough defined open innovation as a model in which firms commercialise external ideas by deploying outside (as well as inside) pathways to the market
• Open system where the focus is on external sources of knowledge through licensing, partnerships and technology agreements
Technology Insourcing
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Open Innovation Paradigm Shift
From ‘Not Invented Here’
To ‘Proud To Be Found Elsewhere’
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Approaches to Open Innovation
Outside-inInvolves opening up a firm’s certain processes of open innovation to many kinds of external inputsDetermination to collaborate with universities, researchers, suppliers, customers, competitors etc. for creating new knowledge and ideas
Inside-outRequires organisations to allow unused and underutilised ideas to go outside the organisation for others to use in their businesses and business modelsOutsourcing or partnering is a possible route to achieving this
Coupled processCombines both of the above such that they happen simultaneouslyAchieved through partnerships, spin-offs, joint ventures and strategic alliances
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Approaches to Open Innovation
Boundaries of the firm/business unit
Locus of innovation inside the firm/business unit
Locus of innovation inside the firm/business unit
Exploitation outside
External
Knowledge
Outside-In Process
Inside-Out Process
Coupled Process
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Crowdsourcing
• Outsourcing it to an undefined, generally large group of people in the form of an open call
• An evolved form of open innovation
• Retrieves and integrates knowledge from unknown networks, improving innovation capability beyond a firm’s known connections and networks
• Broadcast search characteristics – applicable for technology and knowledge transfer. For example a firm assigns a research problem, which has been (partially) addressed internally, to an innovation community network that consists of high-skilled individuals through publishing an open request for collaboration.
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Barriers To CollaborationDifferences Challenges Academia Industry
Cultural differences Different value chains Different types of people attracted
Driven by pursuing basic science and knowledge dissemination
Driven mainly by maximizing a profit, market share and consumer acceptance
Strategic tensions Different goals and drivers Originality of knowledge and research Educating students Contributing to the world of work Publish data
Transforming knowledge to products Generate profit Exploit open innovationCreate competitive advantage
Operational tensions Goals, objectives and timelines are different
Flexible organisational structure Long-term orientation Retain IP rights
Focused on product Strict deadlines Wishes to hold IP rights – proprietary position
Learning challenges Learning may be viewed differently
Using old knowledge and background to develop new knowledge and understandings
Outsourcing complex scientific problems to external companies for creating innovations
Communication challenges Meaning of words differ and are not clearly defined
Research as producing knowledge for contributing to the wider society
Research as transferring outcomes to products and services for direct profit
Commitment Commitment to different stakeholders
Commitment to society, to colleagues and to students
Committed to society, customers and investors to create and share value
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Overcoming the Barriers
UniversitiesEnhance the process of creating collaborations with industry as well as professionalise the process of finding relevant partners through using technological tools and resources.Professionalise contract and collaboration management by efficient operational structuresSet appropriate motives and incentives (funding) for transforming research into products.Support industry’s engagement in the process of publishing outcomes to academic journals and conferences
IndustryImprove communication and define its requirements and interests clearlyImprove transparency (access to information, generation of online platforms for ideas generation) and acceleration of decision makingSet up operational structures to promote collaboration and support and provide guidance and support in publishing research findings to wider research community
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Connections
Universities connect to Industry to:
Enable technology transferCommercialise scientific outcomes
Partnerships are a core mechanism
Intellectual Property (IP) rights are fundamental for establishing solid university-industry relationships
Need appropriate disclosure mechanisms
A searchable on-line marketplace for bringing togetherinnovation communities whilst protecting IP
https://opex.coventry.ac.uk/
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https://opex.coventry.ac.uk/
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A (future) Case Study
Manufacturing Institute
To be established as part of a formal partnership with the Unipart Manufacturing GroupTwin aims of developing innovative approaches to education, training and research in engineering, and stimulating the Unipart supply chain and the wider high-value manufacturing sector across the UK.The project includes design and implementation of a new dedicated academy building on the Unipart site in Coventry, together with new courses and training developments, joint academic-industry appointments and research and development, and technology road-mapping.The project will support the ambition of the Coventry and Warwickshire Local Enterprise Partnership (LEP) for 5,000 new or up-skilled engineers by 2015, and increases in the numbers of SMEsactive in research and developmentin the area.
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Innovation can be defined as:“something original, new, and important - in whatever field –
that breaks in to (or obtains a foothold in) a market or society”
Meaning don’t constrain your thinking to what you know exists already….
Break the mould, think differently, act differently
The answer is what you need - what you know exists
In Summary…
24© Bull, 2013
[email protected]@Bull_UKBull-Information-Systems
0870 240 0040www.bull.co.ukHemel Hempstead HP2 7DZ