Sofia, the World’s Most Advanced Expert Management System

Today, we are the 21st of September 2013, exactly 4 years after the launch the beta version of our expert management system. This was a long way! We have learnt a lot, from both our clients and our experts. Today, I am very proud to announce that we have a new kid at Presans, Sofia 2. Sofia 2 is the new version of our expert management system. Sofia is the world’s most advanced expert management system. Sofia, the world’s most advanced expert management system Sofia is composed of two main parts. The first part is called X-Search. X-search is our expertise mapping and profiling system. X-Search is organising global expertise by extracting and analysing information from various sources of information (scientific

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Presans invited to the Tuesdays of Innovation (video)

On February 26th 2013, Marc Giget invited Presans to the “Mardis de l’Innovation” to present its vision of the Open Innovation and crowdsourcing. (See video at the bottom of this post!) Les Mardis de l’Innovation (the Tuesdays of Innovation), presented by Professor Marc Giget, aim to spread the culture of innovation in various forms through open conferences and debates. Topics include: theories and key concepts of innovation, best practices in innovation around the world, innovation in areas of rapid change, important periods of the past for innovation and innovation in other countries. The theme of the evening of February 26, was the Open Innovation and crowdsouring. Marc Giget presented the recent developments in crowdsourcing with a focus on crowdfunding. Then four

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Diversity In Expert Search

Diversity in Expert Search When Web search engines deal with a broad or ambiguous search query from a user, it is often better to try to present in the results documents matching various aspects of the query to increase the user satisfaction. Is this practice specific to Web search, or can it be applied to expert search as well? When a user has a technological or scientific need and searches for experts, there are several aspects in which diversification of results can be useful. First, the need may be ambiguous or related to more than one scientific discipline. Hence, the expert search engine must ensure that the related disciplines are represented in the results. Second, a user may be searching

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One Million Experts on X-Search!

PRESANS has launched X-Search (presans.com/x-search), the first Worldwide Expert Search Engine less than 3 months ago. It took us a while to go through all the awesome comments and feedback you sent us. We read them all and today, we have great news to announce: more, more and more! Access one million of experts worldwide for free! PRESANS is proud to announce that X-Search, has recently reached 1 000 000 (one million) experts in base. This is an amazing progression since the launch of the of the tool in February 2011. The expert database behind X-Search covers most European countries, including France, England and Germany. Worldwide! We have been claiming that X-Search is worldwide, and then we put a temporary

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A Novel Approach for Open Innovation Platforms: Multistep Dynamic Expert Sourcing : Conclusion

In the first section, the main drawbacks of traditional problem solving platform were presented. These drawbacks are the difficulty to attract and engage sufficient number of qualified experts, the difficulty to efficiently match seeker problems with potential experts, the difficulty to give the seeker convincing incentives to reward all promising solutions and the difficulty to manage confidentiality and to ensure a reliable transfer of intellectual property. In the second section, we presented the disruptive approach that we have developed and implemented. The Multistep Dynamic Expert Sourcing approach relies on both an innovative Expert Search Engine technology and a three-step process for the actual problem solving phase. The Expert Search Engine ensures a relevant matching between experts and problems and avoids

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Main advantages of Multistep Dynamic Expert Sourcing

Implementing the MDES approach with the right technological and methodological assets (i.e. a powerful Expert Search Engine and a relevant methodology to enhance problem formulation) presents strong advantages for experts, seekers and Open Innovation intermediaries (problem solving platforms). For the experts Get relevant problems without having to register Ensure the protection of their intellectual property Avoid irrelevant work and frustration Get the guaranty to be paid for their work For the seekers (the client companies) Have a better control of confidentiality Get potential access to tens of millions of worldwide experts Engage more and better experts Get better solutions For the intermediaries (the platforms) Decrease cost structures Increase scalability Build a reputation of quality & trust Improve the solving rate

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A Guide to Open Innovation & Crowdsourcing

We are pleased to announce the release of the book on Open Innovation and Crowdsourcing that we have co-authored. The new book, called A Guide to Open Innovation & Crowdsourcing, edited by Paul Sloane was launched this week. Paul Sloane manage to pull together contributions from the most active players in the field of Open Innovation worldwide. Most of the contributions are really insightful and I really recommend the reading of the book. Contributors include Henry Chesbrough, Stefan Lindegaard and Andrew Gaule to name but three. If you do buy a copy, thank you and do let us know what you think. (please note that we have participated to the writing for free and that we are not earning a single

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Multistep Problem Solving Process

Multistep rather than black box The multistep approach allows to engage experts and to satisfy seekers, in a safe, secured and trustable environment. It ensures better performance for problem solving, less frustration among solvers and less disappointment among seekers. Online problem solving is often thought of as a “black-box process”: the seeker gives the input, waits a few months and finally opens the box to discover the set of submitted solutions. This process implemented by nearly all Open Innovation platforms has various drawbacks, the main ones being: motivation decrease and risk-averse behavior of solvers, inefficiency to reach quality and relevant solutions, limited incentives for seekers to be fair and pay for all valuable solutions. We propose instead a three-step “gray-box”

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Expert Sourcing and Dynamic aspect

Expert sourcing rather than crowdsourcing To solve highly critical and technological problems, a company needs experts, not random solvers. This is why MDES relies on highly skilled experts rather than solvers. Dynamic (or On-Demand) rather than subscription-based As previously explained, most Open Innovation intermediaries or network of experts rely on registration-based platforms: potential experts have to know about the platform and to register. This is not the right paradigm to address global expertise. Instead, we propose to build a worldwide automatic network of Experts that can be solicited on-demand and that allows automatic profiling of experts. In addition, this paradigm enhances confidentiality, since the visibility of the problems can be restricted to preselected experts (and not to any registered solver).

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