Data, Data Everywhere but Not a BYTE to Eat


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Turning data into actionable information in a timely manner remains a challenge for many organisations. Using information as a basis for business or academic innovation an even larger one that requires new open innovation models. Andrew Carr, Bull UK&I CEO, together with Stephen Booth, Associate IT Director for Coventry University, engaged with the audience in presenting ideas at the Bull sponsored Science & Innovation 2013 conference Westminster.

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  • Data and the opportunity of data is characterised by three traits: Insight: insight in this way is defined as the liefcycle of a single piece of data. Rather than looking in isolation, gather the collective to create valuable….. Information: information is data with value / as an asset. Information is important to customers because enables service consumption at the point of need which leads to…… Innovation: which drives socio economic prosperity and rightly places the UK at the heart of the race in the digital economy and the internet of things. Innovation should also let everyone ask: how can we empower people to use data? Serendipty:
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  • Data, Data Everywhere but Not a BYTE to Eat

    1. 1. 1© Bull, 2013 Andrew Carr, CEO Bull UK& IrelandAndrew Carr, CEO Bull UK& Ireland Stephen Booth, Associate IT Director, Coventry UniversityStephen Booth, Associate IT Director, Coventry University
    2. 2. 2© Bull, 2013 Think about this……. Who are the superstars of the future? Why do mathematicians confuse Christmas and Halloween?
    3. 3. 3© Bull, 2013 Context to Innovation…..
    4. 4. 4© Bull, 2013 The amount of data created by individuals is significantly less than data created about them The 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 stationary Sales 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?
    5. 5. 5© Bull, 2013
    6. 6. 6© Bull, 2013 The role of data within innovation
    7. 7. 7© Bull, 2013 I asked you to think about….. Who are the superstars of the future? Data Scientists……..
    8. 8. 8© Bull, 2013 I asked you to think about….. Why do Mathematicians confuse Christmas and Halloween? I will leave you to go figure……..
    9. 9. 9© Bull, 2013 How Do We Do Data? We don’t do ‘Big Data’ – yet…… We do do Data Analysis We have used this to drive our own performance up the league tables We 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 Research We specialise in ‘Applied Research’ We are very interested in collaborating with industry to drive innovation
    10. 10. 10© Bull, 2013 How Do We Do Innovation? Two basic models of driving innovation Traditional model – Closed Innovation New Model – Open Innovation
    11. 11. 11© Bull, 2013 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
    12. 12. 12© Bull, 2013 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
    13. 13. 13© Bull, 2013 Open Innovation Paradigm Shift From ‘Not Invented Here’ To ‘Proud To Be Found Elsewhere’
    14. 14. 14© Bull, 2013 Approaches to Open Innovation Outside-in Involves opening up a firm’s certain processes of open innovation to many kinds of external inputs Determination to collaborate with universities, researchers, suppliers, customers, competitors etc. for creating new knowledge and ideas Inside-out Requires organisations to allow unused and underutilised ideas to go outside the organisation for others to use in their businesses and business models Outsourcing or partnering is a possible route to achieving this Coupled process Combines both of the above such that they happen simultaneously Achieved through partnerships, spin-offs, joint ventures and strategic alliances
    15. 15. 15© Bull, 2013 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
    16. 16. 17© Bull, 2013 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.
    17. 17. 18© Bull, 2013 Barriers To Collaboration Differences 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 innovation Create 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
    18. 18. 19© Bull, 2013 Overcoming the Barriers Universities Enhance 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 structures Set 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 Industry Improve communication and define its requirements and interests clearly Improve transparency (access to information, generation of online platforms for ideas generation) and acceleration of decision making Set up operational structures to promote collaboration and support and provide guidance and support in publishing research findings to wider research community
    19. 19. 20© Bull, 2013 Connections Universities connect to Industry to: Enable technology transfer Commercialise 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 together innovation communities whilst protecting IP
    20. 20. 21© Bull, 2013
    21. 21. 22© Bull, 2013 A (future) Case Study Manufacturing Institute To be established as part of a formal partnership with the Unipart Manufacturing Group Twin 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 SMEs active in research and development in the area.
    22. 22. 23© Bull, 2013 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…
    23. 23. 24© Bull, 2013 @Bull_UK Bull-Information-Systems 0870 240 0040 Hemel Hempstead HP2 7DZ