How E-Content is changing the way people work

How can researchers become even more efficient in finding the content that addresses their most current issues at the time they need it?

Jeff Jarvis Vice President, Business Development Invention Machine Corporation 617-305-9250 x3288 [email protected]

Association of American Publishers Professional and Scholarly Publishers Division Annual Conference February 4th-6th, 2009, Washington, DC Focus on the User: Localization, Customization, Personalization

Issues of the Organization are driving the demands on the Researcher…..

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70% of today’s revenue generating products becoming obsolete within 5 years 60% knowledge workers are retiring in 7 years Energy crisis, environmental concerns Financial meltdown

“Innovation is the best—and maybe the only —way the U.S. can get out of its economic hole.” -

BusinessWeek

, September 2008 2 Copyright © Invention Machine Corporation 2008. All Rights Reserved.

How does the Researcher efficiently support this need when…..

 Identification of relevant ideas not systematic & predictable – Assumptions & past experience block creative thinking & fresh views – No effective means to rapidly validate & objectively filter ideas  Time pressures cause problem & opportunity analysis to often be incomplete – Lack of timely, relevant insights leads to non-optimal or faulty decisions – Often symptoms treated, past errors repeated, known issues overlooked  Corporate knowledge is not effectively leveraged – Lessons-Learned not readily usable; domain expertise not captured – Yet often the answer you need already exists somewhere in the org  Poor visibility to global content – Difficult to find relevant info beyond firewall or core competencies – Yet >95% of inventions apply known solutions/methods in a new way Copyright © Invention Machine Corporation 2008. All Rights Reserved.

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Increasing strategic value of Research causing Organizations to demand…..

Common, “infrastructure” approach, to precise access to relevant E-Content requiring:

– Making internal past experience accessible more informed decisions, and avoid reinventing the wheel to empower faster & – Leveraging external knowledge beyond the firewall & industry to increase awareness of new or alternative functionality, design options, market opportunities, technology trends, and competitors’ activities – The capture & reuse of subject-matter-expertise to document innovation activities, preserve the wisdom of the graying workforce & reduce the learning curve for new employees – Natural language interface to provide greater refinement in question answering, making the user interface scalable across the organization

Semantic Technology

Extract precise concepts to address questions

“The actuator raises the door, it comprises a diaphragm and hydraulic fluid, but a fluid leak can result in abrasion and failure of the actuator.” Keyword Processing = SEARCH Conventional keyword processing creates a simple bag of noun phrases, you never know the relationships between phrases or parts of speech.

Semantic Processing = RESEARCH Extracts underlying meaning actuator raises door Subject Action Object fluid door actuator abrasion

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failure comprises actuator Whole comprises Consists of diaphragm, hydraulic fluid Parts hydraulic diaphragm result leak raises

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fluid leak Cause results in Produces actuator abrasion, actuator failure Effects

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Research applications

Find Existing Knowledge to Address a Practical Question

 Common Challenges Addressed – Info overload; traditional search ineffective – Constrained by limits of local expertise – Difficult to assemble & analyze knowledge sets needed to address complex problems

At Shell, one of the world’s largest petrochemical companies, two research projects required 1000 documents on heavy oil processing to be categorized & analyzed. One was done manually and took 6 months. The other used Goldfire Innovator, took 5 hours, and produced superior results .

Using Invention Machine’s software, Honda has dramatically cut back the information research phase for their R&D projects from an average of 22,000 hours to 1,000 hours.

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Enabling Researchers with precise access to critical E-Content on demand

Can insulin be delivered by a transdermal patch?

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Research applications

Find Existing Knowledge to Address a Practical Question

 Advantage of Semantic Access – Provides high precision concept retrieval – Results can be ranked by relevance to the question – Robust tools provide an automatic topic categorization & document summarization

Acquisition resulted in closed facilities & senior staff attrition. Northrop Grumman used Invention Machine software to index over 30,000 electronic documents enabling the capture & re-use of thousands of man years of technical know-how & corporate expertise – even though the original subject-matter experts were gone.

– Quickly leverages vast libraries of E Content, including internal corporate data plus web, deep-web and specialty data stores such as patents

Using Invention Machine software, Alcon engineers were able to circumvent two competitive patents – enabling entry into a new multi-million dollar market.

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About Invention Machine

“Invention Machine software is a leading example of creativity software, a class of programs aimed at raising the IQ of research and development in a time of global competition, brutally short product cycles, and constant cost cutting.”   

Headquartered in Boston, Massachusetts Leading provider of enterprise knowledge-enabled software Delivering greater efficiency, quality & predictability to Research and related processes

Copyright © Invention Machine Corporation 2008. All Rights Reserved.

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