Towards an Open and Scientific Approach to Innovation Processes
- 2. Summary I. Introduction • Background • Main issues in innovation management • Research question II. Approach • Open innovation • Scientific mindset • Innovation meta-process III. BI Framework • Functional/Non –functional requirements • Main modules • Available technologies and solutions IV. Conclusions NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
- 3. Introduction Highly 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) is implemented 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
- 4. Main issues in innovation management Innovation… • 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
- 5. Role of collaboration Innovation requires many resources: the capability to cooperate with other partners is a means to reduce risks and increase competencies. Collaboration in distributed organizations: • research consortium to face scientific challenges • Virtual Enterprises: connection of SMEs into peer networks, to face commecial challenges NGEBIS, June 26th, 2012 Towards an Open and Scientific Approach to Innovation Processes
- 6. 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
- 7. Research question How to provide support to business users in the management of an innovation process in a collaborative, distributed and heterogeneous environment? 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
- 8. Approach Open 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 strategies Scientific 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
- 9. 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
- 10. 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
- 11. 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
- 12. Research question How to provide support to business users in the management of an innovation process in a collaborative, distributed and heterogeneous environment? 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
- 13. 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
- 14. 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
- 18. Conclusion Open 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 management Towards (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