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Knowledge Harvesting

Experts have implicit knowledge that is difficult to articulate, as they rely on automaticity in their decision-making. This can limit their ability to effectively convey what they know about their intuition-based learnings. As a result, capturing and codifying this implicit knowledge through Knowledge Harvesting methodologies is crucial to preserve their expertise and delivering actionable guidance for others.

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Examples of mission-critical knowledge harvesting projects:

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Knowledge Harvesting® originated in a company called LearnerFirst, which delivered technology to improve individual and team learning.

  • 1989: Driven by Englebart’s 1962 Augmenting Human Intellect, Wilson described intellectual augmentation technology in a Master's Thesis. “Digital Performance Support Application” functions were described and illustrated for engineering, business management, architecture, nursing, industrial design, ...

  • 1992: Pioneered a new genre of commercial software applications – “learning-while-doing” software. Delivered applications to over 4,000 organizations. Titles: Benchmarking, Process Management, Implementing ISO 9000, Software Engineering Risk Management, Knowledge Innovation Assessment, Work Profiling, Performance Measurement, Smart Meetings, Smart Writing, Smart Goals, ...

  • 1995-1996: Produced custom learning systems and applications for large organizations.

  • 1996: Began to extensively document how to make implicit knowledge explicit. Psycholinguistic discoveries led to the method, Knowledge Harvesting, for addressing automaticity and yielding unprecedented insights and guidance. 

  • 1997: Further discoveries yielded a means of automating rapid application development, thus fulfilling the principle of linguistic relativity. Where Whorf reasoned that the experience of a language controls thoughts expressed by a speaker of that language, Wilson proved that technology influences information processing and that influences our ability to develop solutions to complex problems. 

  • 1998: Began mentoring knowledge management professionals.

  • 2000: Globally deployed Knowledge Harvesting methodology via professional consultants.

  • 2002: Delivered Knowledge Harvesting Kits to enable business functions, departments, and teams to effectively capture and leverage vital knowledge.

  • 2003: - Method embedded in social media used to launch online communities. Designed infrastructure and initiated over 100 online communities; captured guidance about effective online collaboration practices.

  • 2004: Began integrating Knowledge Harvesting into enterprise-wide, knowledge management programs.

  • 2009: Reintroduced Work Profiling as a scalable form of “knowledge harvesting lite.”

  • 2010: - Mappings of standards and technology value propositions for interconnecting smart grids.

  • 2013: Contemplative View - Revelations of unprecedented spiritual insights.

  • 2014: Long Term Zonal Isolation - Improvements to compliance and risk mitigation of industry risks, especially oil spills

  • 2015: - Tangible, value-add interlinkages among the Sustainable Development Goals; emphasis on (14) Life Below Water, (17) Partnerships for the Goals.

  • 2016: Knowledge Harvesting Live - Demonstrated real-time knowledge capture.

  • 2018: - Delivered method for augmenting associational thinking with contextually-interoperable information.

  • 2018-2022: Neoholism - Documented principles and practices for systems thinking.

  • 2019: Spiritual Learning - Delivered workshops and guidance for skills to elucidate the dynamics of spiritual transformation.

  • 2019: - Practical method for determining if a work task is susceptible to machine learning.

  • 2021: Digital Operating Models - Applied interconnecting technology to model plant KPIs, processes, and ISO 9000 quality management standards.

  • 2022: Transition to!

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Knowledge Harvesting is a structured method and toolbox for capturing vital knowledge of systems, conditions and variations, and actionable guidance.

  1. Focus: Define critical knowledge to capture and reintegrate for improved performance.

  2. Find: Select participants and information.

  3. Elicit: Conduct elicitation sessions.

  4. Organize: Tag and utilize the information for optimal decision-making and learning

  5. Package: Select and deliver guidance derived from elicited knowledge. 

  6. Evaluate: Measure the effectiveness of guidance derived from elicited knowledge.

  7. Adapt: Update the knowledge base. 

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