The following discussion explores the continuous stream
of reinvention for best practices, business models, and strategies
that will occur between now and 2010 and beyond. It provides greater
detail on the nature of the reinventions and how practitioners will
experience such changes.
Reinventing Best Practices
What will it be like for an e-knowledge practitioner
to experience the past, present, and future all at once? To witness
cascading cycles of best practices in e-learning and knowledge management?
To hear of interesting new practices and approaches from institutions
and enterprises half way around the globe? And to try to make sense
of the many choices and options in attempting to reinvent and innovate
ones own e-knowledge initiatives?
How do companies spot and manage promising
opportunities? They do it as surfers ride waves or scientists conduct
research. They observe selected environments systematically and
scan ripples of opportunity on multiple horizons. They learn to
recognize patterns of impending change, anomalies, or promising
interactions, then monitor, reinforce, and exploit them.
James Brian Quinn, 2002
Making Innovation EasierYesterday, Today
and Tomorrow. Even today, mass systems for education and
training offer little more by way of personalization than did Henry
Fords pioneering system for mass production of vehicles: You
can have any color you like as long as its black. Fords
system, remarkable for its day, had its R&D equivalent in Thomas
Edisons laboratories at Menlo Park. Edison is famously credited
with the insight that invention was 99% perspiration and 1% inspiration.
He needed thousands of experiments before he was able to devise
a long-lasting electric light. His studies of other inventors convinced
him that sudden flashes of inspiration Eureka
moments were the exception. Most of the time, small steps
were all that was needed to make valuable advances. He isolated
the processes that were common to the mass of inventive steps, and
established the world's first production line for inventions and
What was admirable about that approach was the way
in which people who would not have considered themselves to be creative
were enabled to be creative and to come up with ideas for products
that changed their society. Today, comparable vistas are emerging.
The difference between now and Edisons time is that today
we have the technology, such as computer-supported ways
to develop personalized knowledge bases specific to our needs, which
can be combined with databases of processes that are proven to be
helpful. As an early illustration, consider the success of NASA.
They were an early user of a system for managing invention
and innovation, developed in the former Soviet Union under its Russian
acronym TRIZ. The inventor of TRIZ looked for patterns in many thousands
of patents, and determined the physical effects that were the basis
for each invention. From this, he was able to come up with generalized
processes that anyone could use to create new inventions.
In the West, the system is now available commercially
under such names as the Invention Machine. It provides a decision-support
system that incorporates links to relevant databases, covering such
areas as constraints (e.g., physical and chemical properties of
materials) and possibilities (e.g., known physical effects and phenomena).
We see it as a precursor of the kinds of tools that will become
widely available in the knowledge economy for managing knowledge
of all kinds and seeing patterns that can be put to use in new contexts.
The key to success is to bake specialized
knowledge into the jobs of highly skilled workersto make knowledge
so readily accessible that it cant be avoided.
Thomas H. Davenport and
John Glaser, July 2002
Such tools will need to be embedded into peoples
knowledge space in a highly amenable manner.
Emergent Best Practices. Two benchmarks
guide our vision of emerging best practices for e-knowledge: 1)
current e-knowledge practices that are gestating in different settings
across the globe, and 2) the impact of impending changes in standards,
technologies, marketplaces, infrastructures, and knowledge ecologies.
The leading edges of many of these best practices are evident today.