data, data everywhere but not a byte to eat

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

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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/

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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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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…