SummaryI. Introduction   •        Background   •        Main issues in innovation management   •        Research questionI...
IntroductionHighly dynamic environments require adaptation capabilities.Innovation is a way to react efficiently and effec...
Main issues in innovation managementInnovation…• risky process• unpredictable outcomes• non-observable and non-controllabl...
Role of collaborationInnovation requires many resources: the capability tocooperate with other partners is a means to redu...
Main issues in innovation management Innovation…• risky process• unpredictable outcomes• non-observable and non-controllab...
Research questionHow to provide support to business users in themanagement of an innovation process in acollaborative, dis...
ApproachOpen innovation:   • collaboration of distributed partners in the VE   • internal skills are not enough: sharing o...
Approach > Differences/Similarities                            Scientific process:                            • aims to di...
Approach > Differences/Similarities Similarities • starting point: an open problem, a draft of an idea or a hypothesis • d...
Approach > Innovation meta-process                                   Prior    internal knowledge, data trails about       ...
Research questionHow to provide support to business users in themanagement of an innovation process in acollaborative, dis...
BI Framework > Functional requirements                            To keep track of information, to collect & store data   ...
BI Framework > Non-functional requirements• Interoperability of available distributed and heterogeneous data,  formats, bu...
ConclusionOpen and scientific approach to innovation process management:• Open approach:    • sharing of (some) resources,...
Towards an Open and Scientific Approach to Innovation Processes
Towards an Open and Scientific Approach to Innovation Processes
Towards an Open and Scientific Approach to Innovation Processes
Towards an Open and Scientific Approach to Innovation Processes
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Towards an Open and Scientific Approach to Innovation Processes

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Full paper: http://boole.diiga.univpm.it/paper/ngebis2012.pdf

Being the modern economy
constantly changing and evolving, organizations are asked to develop a more flexible, open and collaborative mindset. In particular, an attitude towards continuous product/process innovation is seen as one of the potential solutions capable to effectively address the dynamism of the market. However, Business
Innovation (BI) still lacks methodologies and best practices
capable to effectively drive business users from an innovative idea to its realization and evaluation. This work investigates the possibility to adopt a pragmatic and systematic approach to support business users in the management of an innovation process, with the aim to increase the
control over the process and reduce the risks of failure.

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Towards an Open and Scientific Approach to Innovation Processes

  1. 1. SummaryI. Introduction • Background • Main issues in innovation management • Research questionII. Approach • Open innovation • Scientific mindset • Innovation meta-processIII. BI Framework • Functional/Non –functional requirements • Main modules • Available technologies and solutionsIV. Conclusions NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  2. 2. IntroductionHighly dynamic environments require adaptation capabilities.Innovation is a way to react efficiently and effectively to changes.The process by which an invention (product/process/model) isimplemented to satisfy a specific need:• for the customer (cost-cutting side)• for the client (value-side)• for the society (environmental/social-side) Macro-activities: • invention • implementation • adaptation & diffusion NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  3. 3. Main issues in innovation managementInnovation…• risky process• unpredictable outcomes• non-observable and non-controllable variables• complex dependencies and huge amounts of information NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  4. 4. Role of collaborationInnovation requires many resources: the capability tocooperate with other partners is a means to reduce risksand increase competencies.Collaboration in distributed organizations:• research consortium to face scientificchallenges• Virtual Enterprises: connection ofSMEs into peer networks, to facecommecial challenges NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  5. 5. Main issues in innovation management Innovation…• risky process• unpredictable outcomes• non-observable and non-controllable variables• complex dependencies and huge amounts of information …in a distributed and collaborative environment (VE)• localization of and access to resources• heterogeneity• lack of control (need of coordination)Available approaches in the Literature:- lack of methodologies (suggestions, heuristics, “best-rules” lists)- lack of solutions (not-comprehensive tools) NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  6. 6. Research questionHow to provide support to business users in themanagement of an innovation process in acollaborative, distributed and heterogeneousenvironment?1. Which general principles should a framework for BI be based on?2. Which requirements? Which support functionalities should the framework offer? NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  7. 7. ApproachOpen innovation: • collaboration of distributed partners in the VE • internal skills are not enough: sharing of (some) resources in the VE • sharing of (proportional) risks and revenues • new collaborative business models and strategiesScientific mindset: • innovation process as a “process of discovery” • more rigorous/rational approach • closely tied to empirical data • better control of the process • control of information flow/dependencies NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  8. 8. Approach > Differences/Similarities Scientific process: • aims to discover how a phenomenon works • rigorous methodology, protocols for evaluation • relies on standards, practices, units of measurement Innovation Process: ● much less structured, more exceptions ● more hardly controllable variables ● lack of methodologies, standards, and background knowledge NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  9. 9. Approach > Differences/Similarities Similarities • starting point: an open problem, a draft of an idea or a hypothesis • dynamic/risky nature (output not known in advance) • high complexity (many dependencies have to be taken into account) • highly iterative/interactive (not completely automatable) • output: knowledge useful for successive iterations • constructive refinement of hypotheses/ideas NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  10. 10. Approach > Innovation meta-process Prior internal knowledge, data trails about previous IPs, BPs, external data from client/customers/partners in the VE To recognize problems/opportunities: variables to tune, flaws, weaknesses, previously unknown relations among data To experiment different solutions, to track such experiments and evaluate the feasibility of their implementation NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  11. 11. Research questionHow to provide support to business users in themanagement of an innovation process in acollaborative, distributed and heterogeneousenvironment?1. Which general principles should a framework for BI be based on?2. Which requirements? Which support functionalities should the framework offer? NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  12. 12. BI Framework > Functional requirements To keep track of information, to collect & store data from multiple sources Data manipulation, summarization, retrieval of hidden relations in data, model generation, ex-post analysis of previous innovation processes Collaborative discussion, knowledge sharing To design implementation processes, design experimental workflows, highlight dependencies among documents, control relevant KPIs during the process, log the process, test customer satisfaction, simulation NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  13. 13. BI Framework > Non-functional requirements• Interoperability of available distributed and heterogeneous data, formats, business processes: to identify and describe resources within the VE in a shared way• Usability in process innovation design and management: to codify dependencies among process activities, provide suggestions about next tasks, support in the choice of KPIs• Coordination in cooperative work• Flexibility• Modularity NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
  14. 14. ConclusionOpen and scientific approach to innovation process management:• Open approach: • sharing of (some) resources, risks and revenues • definition of shared meaning for shared resources • reuse of collaborative technologies• Scientific approach: • rigorous, rational, tied to empirical data • adaptation of available solutions for e-Science workflow managementTowards (custom) methodologies for business innovation in VEs: • extraction of common practices in past innovation processes • ex-post analysis to recognize best practices and improve the way the VE manages innovation NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
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