open source innovation factory, ow2con11, nov 24-25, 2011, paris
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OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Source Innovation Factory
Paolo Ceravolo, Università degli Studi di Milano in cooperation with Engineering Group
[Our Framework equipped with Innovation Metrics can
dramatically reduce the time required to transfer an innovative project to a real environment]
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Outlook
Open Issues in Open Innovation Our Proposal Our Framework Future work
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Innovation 72% of company executives rank innovation in their
top 3 priorities (Boston Consulting Group, 2006) 80% of new product results will tend to come from only
20% R&D projects (Eduardo, 2003) successful companies cancelled as many innovation
projects as non-successful companies. However, successful companies were able to cancel unattractive projects much earlier in the process (Ogawa & Ketner, 1997)
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Innovation
The central idea behind open innovation is that in a world of widely distributed knowledge, companies cannot afford to rely entirely on their own research, but should instead buy or license processes or inventions (i.e. patents) from other companies. In addition, internal inventions not being used in a firm's business should be taken outside the company (Chesbrough, 2003).
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Innovation
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Issues in Open Innovation
Reduce time to identify unproductive projects Understand the synergy that are potentially
relating different projects
Represent Innovation Activity Measure Innovation Activity Report on Innovation Activity
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Source Innovation Factory
Mixes three complementary approaches: 1. Innovation Factory Metamodel (IFM), proposed in
the ARISTOTELE project (www.aristotele-ip.eu) 2. Open source platform SpagoBI
(www.spagobi.org), LOAP and Reporting 3. Knowbots, advanced tools for the acquisition of
concepts from internal and external knowledge sources
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Open Source Innovation Factory
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Innovation Factory Metamodel
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Innovation Metrics
• Goal 1: Innovation Level Improvement o Q1.1: Which is the level of innovative knowledge exploited in the Organization? o Q1.2: How much are innovative the new products? • Goal 2: Quality of Innovation Sources o Q2.1: Which is the quality of sources of innovation process? • Goal 3: Open Innovation Permeability o Q3.1: To what extend the customer contribution is exploited? o Q3.2: To what extend the concepts coming from competitors' sites are exploited? o Q3.3: Evaluate the level of technologies that are transferred by the analysis of
competitors o Q3.4: How much internal proposals influence innovative products? • Goal 4: Return of Innovation Investment o Q4.1: How much innovation process produces profits? o Q4.2: How much innovation process costs? o Q4.3: Indirect Advantages
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
. www.ow2.org.
Innovation Metrics
Goal 1: Innovation Level Improvement Q1.1: Which is the level of innovative knowledge exploited in the Organization?
M1.1.1: no. accesses to blog/forum marked as innovation sources M1.1.2: no. concepts transferred from innovation sources to produced documents (e.g. cut&paste)
Q1.2: How much are innovative the new products? M1.2.1: no. tags describing new functionalities / no. concepts in innovative sources tag cloud M1.2.2: no. requirements covered by new products
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Innovation Metrics
Goal 2: Quality of Innovation Sources Q2.1: Which is the quality of sources of innovation process?
M2.1.1: % of external requirements, coming from outside the organisation (e.g. analyzing innovative sources) M2.1.2: % of internal requirements, coming from inside the organisation (e.g. from internal meetings) M2.1.3: % of customer requirements, coming directly from the customer M2.1.4: % of new products implementing external requirements M2.1.5: % of new products implementing internal requirements M2.1.6: % of new products implementing customer requirements M2.1.7: % of human resources that contribute to the innovation process
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Innovation Metrics Goal 4: Return of Innovation Investment
Q4.1: How much innovation process produces profits? M4.1.1: no. new products sold per month M4.1.2: no. new products sold per week M4.1.3: no. new customers M4.1.4: % revenue from new products M4.1.5: % new product within deadline
Q4.2: How much innovation process costs? M4.2.1: time-to-market of new products M4.2.2: time-to-market of changes to existing products M4.2.3: budget spent on human resources training M4.2.4: no. competences involved in innovation process M4.2.5: no. human resources involved in innovation process M4.2.6: no. man-months spent to realize new product M4.2.7: no. man-months spent to realize changes to existing products M4.2.8: average number of training hours per human resource
Q4.3: Indirect Advantages M4.3.1: % customer satisfaction with new products M4.3.2: % of human resources reaching desired competence level after training M4.3.3: % difference in productivity before and after training
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
SpagoBI
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
SpagoBI
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
SpagoBI
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
KnowBots • KB consists of two distinct modules which interact
with each other • One module is running locally in the workspace of
the worker • A second module is a remote server module that
interrogates various database services across the network and provides the results to a user agent running in the local workspace
• This way we can track the information that are provided by the Knowbots and are used in the workspace
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Scenario: AVIO • AVIO traditionally run two separate business:
• Plant in Torino selling engines • Plant in Brindisi providing overhaul services
• AVIO has no foresight on the mid-term arrivals of engines and is unable to optimize plans and procurement processes.
• FLEET MANAGEMENT • centralizing engine monitoring and scheduling their
overhaul process • optimizing the flow of engines in arrival and
reducing congestion or underutilization
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
Lesson Learned • Access to data
• process (competences, requirements) • products (requirements, ROI)
• Define Innovation Profile based on successful story to support comparability among past and running processes
OW2Con 2011, November 23 -24, Orange Labs, Paris
www.ow2.org
This work is co-funded by the European Commission as part of the ARISTOTELE project
(FP7-ICT-2009-5 –257886)