Monitoring and Control of Concurrent Innovation (CI)

Powered by strong success visions, extremely efficient self-organised innovation processes may emerge outside of organizational boundaries and across conventional hierarchies. The more such innovation networks expand, the more pressing is the need for a shared sense of trust, reciprocity, informality and community among members. Only on this base, organizational efforts can be focused on the learning processes, the acquisition of new insights and additional knowledge. Although Concurrent Innovation is increasing chances and lowering the risks for all partners, the processes involved are complex and depend on grown experiences on the field. The crucial trust base between the partners will erode if transparency of the processes, the learning progresses, or the motivation of partners are lacking. Learning through collaboration and effective self-organization absolutely requires that the network has a window on the partners capabilities and assets, which is provided by the subsequent monitoring and control procedure.  A procedure for Monitoring and Control of Innovation in Networks is derived as follows:

• Description of the collaboration and the objectives to go for
• Decomposition and Analysis of the Innovation object attributes for market performance
• Skills/Competency profiles for market- und co-operation requirements Technologies/Competencies in line with the phases of Innovation (stage wise)
• Enumeration of the specific and total attractiveness of the collaboration object
• Check of utility / effort ratio for all partners and all phases, expressed in linkage intensities
• Initiation of corrective actions if and where needed. Issue resolution and escalation support.
• Evaluation
The information provided may be used to cover all specifics for a distinct innovation object in a COIN (Collaborative Innovation Network) and, moreover, to support benchmarking of other concurrent innovations, allowing to gain more experience in e.g. early detecting risky constellations or in reliably forecasting chances of success.   Another important step on the way to a Concurrent Innovation Base of Knowledge (CI_BoK) that had been initiated by a framework for Small and Medium Sized Extended Enterprises and ESoCEpedia http://www.ami-communities.eu/wiki/ESoCEpedia as the proper CI terminology for the CE community: http://www.esoce.net/. If innovation network members continuously evaluate their performances, monitoring and control of innovation processes will make collaborative activities more efficient and strengthen the trust bases at long term. The attributes to be monitored can be reduced to a small set of Key Innovation Indicators (KII) allowing the control of COINs. Moreover the collection, the accumulation and the systematisation of these indicators, observed in Concurrent Innovation processes, may eventually pile up considerable CI experience and result in a Base of Knowledge for the support effective and efficient CI processes. The information provided may be used to cover all specifics for a distinct innovation object in a COIN (Collaborative Innovation Network) and, moreover, to support benchmarking of other concurrent innovations, allowing to gain more experience in e.g. early detecting risky constellations or in reliably forecasting chances of success.   Another important step on the way to a Concurrent Innovation Base of Knowledge (CI_BoK) that had been initiated by a framework for Small and Medium Sized Extended Enterprises and ESoCEpedia http://www.ami-communities.eu/wiki/ESoCEpedia as the proper CI terminology for the CE community: http://www.esoce.net/. If innovation network members continuously evaluate their performances, monitoring and control of innovation processes will make collaborative activities more efficient and strengthen the trust bases at long term. The attributes to be monitored can be reduced to a small set of Key Innovation Indicators (KII) allowing the control of COINs. Moreover the collection, the accumulation and the systematisation of these indicators, observed in Concurrent Innovation processes, may eventually pile up considerable CI experience and result in a Base of Knowledge for the support effective and efficient CI processes.