Science & Technology
Trends that will shape the subjects, methods, talent and institutions of scientific research and technological innovation.
Economy & Society
Trends that will shape the big picture for organizations and enterprises.
A Brief History of Technology-Led Economic Development
Industrial Parks & Science Cities
Incubators and Research Parks
Regional Knowledge Ecosystems
The New Global Map of Science
real estate-driven
value is in low-cost land
focus on attracting corporate branch plants
driven by technology transfer
value is in proximity to universities
focus is on new firm formation & growth
As the global economy moves from crisis to slow recovery, public investments will set the agenda and drive growth. When recovery does come, the focus will be on building more resilient economic models.

Signals
NIH: $10b in stimulus
for biomedical research
WSJ Survey: Corporate R&D spending
holding steady (but for how long?)
Developing economies continue to
make large investments 
in research infrastructure
Implications
A one-time injection of funds?
Empty innovation pipelines in the short-term as companies cut back on R&D
More pressure on tech transfer
New hubs in the developing  make rapid gains

From Free Markets to Stimulus Capitalism
Ecological Economics Comes of Age
The Group Economy
Growth of carbon markets
Signals
Personal carbon
tracking
Commercialization
of offsets
Measuring the economic value of ecological processes will be a critical tool to address global warming.
Implications
New technology sectors in environmental sensing and modelling
from carbon neutral to carbon negative as the standard
third-party monitoring and certification
reuse, renovation and recycling

As the social web evolves, forming groups around any shared interest, identity or activity will cost next to nothing. New models for wealth creation will emerge at the intersection of the social web and grassroots movements. Existing organizations will be transformed through the adoption of these tools and practices, becoming  less hierarchical, more agile and more collaborative.
Signals
Companies adopt
social software
Obama campaign
online organizing
Knowledge
commons
Implications
new metrics in innovation and economic development, that measure networks instead of institutions - what are the social networks passing through your park?
more flexible spaces
more spaces for ad hoc collaboration
collaborative infrastructure
2008: 3000+ incubators worldwide
Research Triangle Park
Sophia Antipolis
Ubiquitous Computing
Signals
Implications
The spread of computation into everything will create vast new datasets for science. These same tools will also turn everyday activities into data-generating activities. This information will create value for retailers, manufacturers, and consumers. 
Sensing everywhere,
top-down and bottom-up
New user interfaces: computing fades
into the background
Everything connected,
all the time
New industries: ubicomp technology, applications and data mining
Transformation of existing industries: logistics, retailing, etc.
Research parks need to become "living labs" for these technologies
From Artificial to Hybrid Intelligence
For decades, the goal of AI research was to copy the brain's complex reasoning. That vision is shifting, as "smart enough" AI merges with the collective intelligence of the social web. More and more of our friends will be “bots” and intelligent software agents, doing useful things on our behalf.
SIGNALS
IMPLICATIONS
Tools for finding expert knowledge in large organizations and social networks
People training computers and algorithms
"Reality mining"
Future knowledge management is about connecting people
More amateurs involved in R&D ("human intelligence tasks")
Are parks "mine"-able? Are they designed for social sensing?
Biology By Design:
Nature as Source and Code
SIGNALS
IMPLICATIONS
Syn-dustry:
Intentional Biology
Biomimicry
Biomolecular
nanotechnology
Bioscience is transdisciplinary and translational - very different place needs than IT
From park as 'grid' to park as 'tissue'
Biotech industry's structural flaws mean many opportunities to create more innovation-friendly environments

From synthetic genomics to stem cell therapy, biology will become a more important source of scientific and technological breakthroughs. Biological concepts will also inspire designs for everything from buildings to organizations to algorithms. Yet the biotech industry is structurally unsound – without change it won’t be able to fully realize the commercial potential of these new technologies.
The New Scientists
Young scientists, and scientists from emerging economies, will transform how scientists work, how they build they careers, and the sources of knowledge they draw upon and develop in their work. Online publishing and entrepreneurship will transform their career development and reputation. They will be both transdisciplinary and ultra-specialized, drawing on various disciplines to answer complex, focused questions. The role of amateurs will expand, as both independent researchers and partners of professional science.
SIGNALS
IMPLICATIONS
Student entrepreneurship
JoVE: YouTube for science
Amateur renaissance
Talent that seeks career mobility and lifelong learning
New ideas about integration of work, home and social lives
Globally mobile science and engineering talent
New non-Western science "cultures"
Institutional Transformation
The web will create new kinds of organizations that challenge institutions. Scientific publishing is already under full-scale attack. Private research funds, from Canada’s Perimeter Institute to the X-Prize will create alternative incentives for innovation. The sheer complexity of the scientific challenges of the 21st century will require massive new global research projects that span existing boundaries.
SIGNALS
IMPLICATIONS
Truly global collaborations
Open access online:
The end of science publishing?
Private benefactors
for big science
Parks need appeal as sites where new networks convene
Attracting future research institutions
What would a network that directly threatens parks look like?
Models and Places for R&D
Trends that will shape technology commercialization and the production of knowledge.
SIGNALS
IMPLICATIONS
Rise of science and technology
on the Indian Ocean Rim
Strategic shift from zero-sum competition to niches in global R&D "supply" chains
Globalization of small business
Alternative science "cultures"
Parks as global suppliers of research space and research networks?
Universities: From Ivory Tower
to Economic Engine
Universities will continue their ascendance as nations' and regions' primary research venues, as companies continue to focus on rapid, incremental innovation. 

There will be increased expectations that universities play a primary role in driving economic growth, from the United States to Islamic Asia, putting enormous pressure on technology transfer mechanisms.

Finding new paths from lab to market will be the key difference between universities that rise to this challenge and those that do not.
SIGNALS
IMPLICATIONS
Texas A&M to reward faculty
entrepreneurship in tenure review
Fixing tech transfer /
high-risk, high-reward
From university research parks to innovation zones and New Century Cities
Need for breakthrough tech transfer innovations - rewarding high-risk research
Parks moving onto campus?
Need more tools to make university talent and resources available to outsiders

From Parks to Regional Knowledge Ecosystems
Sticky Know-how
The kinds of knowledge that creates unique competitive advantage - cutting-edge scientific knowledge, new research tools, and technical practices – are kept alive in creative clusters. This tacit knowledge can remain “sticky” and stay embedded in loosely networked groups operating in the same places.

There are ways to speed and amplify the creation of sticky know-how: locating R&D alongside manufacturing, making it easy for biomedical researchers to move from bench to bedside, and hyper-specializing clusters in rapidly emerging areas of technology.
SIGNALS
IMPLICATIONS
Super-specialization @ Snowpolis
Locating R&D
with manufacturing
Translational research
in biomedicine
Copy Exact
Boutique parks,  designed to be highly specialized clusters of tacit knowledge 
Creating mixed-use parks
Knowledge-based blue collar jobs
Growing importance of industrial ecology
Lightweight Innovation
As the global economy slows down, the pressure to innovate faster and cheaper will only increase. More and more of new product and service development will happen outside of existing pipelines. Lightweight models for organizing R&D will move projects from idea to implementation without traditional incubation. As open innovation casts a wide net for ideas, it will seek solutions from everyday people.
IMPLICATIONS
SIGNALS
New investment models and tools
Open innovation
in industry
Innovation prizes
The Social Life of Small Research Spaces
1980s-style business incubators will fade away, replaced by new kinds of spaces for entrepreneurship and collaborative research. Pop-up labs, co-working hubs, mobile incubators and temporary research parks will provide flexible physical spaces while social software will provide flexible organizational structures to tie them together in local and regional networks.
SIGNALS
IMPLICATIONS
New kinds of park managers, new skills
Research places need to be "produced" like a show
Linking parks to social networks
New business models for franchising social places
Rise of co-working
Pop-up labs
Disposable parks
Future Knowledge Ecosystems
The complexity of future R&D tasks will be too great for any single organization. But the need to tap regional and global resources often conflicts with local economic development strategies. Current regional strategies are often too narrowly focused on specific industries.

Regional knowledge ecosystems are broader than a single industry. Their purpose will be developing flexible financial, human and social capital that can feed any sector. These networks will stretch far beyond the major regional institutions of today to include informal networks of entrepreneurs, investors, professionals and hackers.

They will be able to adapt faster than national innovation systems, and  can scale up successes better than isolated parks and cities. 
SIGNALS
IMPLICATIONS
Parks everywhere need to build regional partnerships with real committments - what are the shared challenges?
Need to inventory and map regional assets
Policies that allocate resources regionally
Engagement with non-traditional institutions and networks


Incubation ecosystems
Regional cluster strategies
Incremental change adds up
SkySong: ASU Scottsdale Innovation Center 
AdamsMorganWorks:
A co-working district in Washington, DC
Disruptive transformation from outside
Research parks in decline
UNLV Harry Reid Research Park
This is the low risk, low reward scenario.

Research parks are still recognizable to us, with the familiar players involved, but they have upgraded to the next “version”.

Key characteristics of this scenario:
No huge disruptions
Universities are more entrepreneurial
the transition to sustainability is expensive, but managable
Parks are not leaders in new science networks, but are participating
Real, but incremental progress in fixing biotech's structural problems
This is a high risk, high reward scenario.

Research parks are being completely transformed by networks of small-scale, pop-up labs, workshops and meeting spaces. In these research clouds, social software provides the institutional glue - successful parks basically transform themselves into networks.

Some universities leverage this, many can't understand it
Clouds are very light footprint, existing parks a high-energy legacy
Clouds are vitual communities that find places to land and convene
Clouds pioneer new, open approaches to biotech innovation
What this might
look like
In 2011, the number of research parks worldwide peaks and then begins to decline. There are many possible triggers acting alone or in combination - high energy costs, falling R&D productivity, or a protracted global recession. Yet existing parks cannot survive these challenges, and they have failed to adapt individually or band together in regional ecosystems. What remains of R&D is highly virtualized to keep up ROI.
Universities retreat from commerce and tech transfer
Virtual networks are hard to footprint, parks aren't. So who gets the blame and regulation?
Parks don't market themselves to new institutions
Without experiments and reform, the bio-industry can't reach ignition point

 
The Group Economy
Stimulus Capitalism
Ecological Economics
Ubiquitous Computing
The New Scientists
Biology
Hybrid Intelligence
Institutional Transformation
Lightweight Innovation
Sticky Know-How
The New Global Map of Science
Univeristies: From Ivory Tower to Economic Engine
The Social Life of Small Research Spaces
From Parks to Regions
CREATING THE SCENARIOS
Think about each scenario and ask yourself:

What happens to my organization in this future? Where are we? what are we doing?
If you knew today this would come true, what you do differently today to change it?



1950
1980
2010
driven by innovation in global technology niches
value is in flexibility of labor, firms and space
focus on building agile, tech-based creative knowlege clusterst

The Next Twenty Years of
Technology-Led Economic Development
Main Findings
1. The Economy
innovation at the top down and the bottom up, driven by global economic and ecological challenges

2. Science & Technology
institutional upheaval as new talent pushes the envelope at the intersection of existing fields

3. Places for Innovation
greater focus on spaces for collaboration, and an expanding commercial role for universities
But this will happen at different rates, and local actions will matter.

Three plausible scenarios are:

Incremental change - old research parks adapt, new parks evolve
Disruptive transformation - pop-up networks of small spaces rewrite R&D
Fail! - places dont add much to R&D productivity, so everything virtualizes

A new global map of science is emerging, where world-class science is no longer limited to a handful of  industrial powers. The new map is a network of centers of excellence that combine targeted investment in basic science with local industrial and cultural resources.
biofuels
wireless
regenerative medicine
Need for deeper, larger, more diverse local investor networksMore innovation from startupsFrom protecting IP to encouraging openness
TRENDS
SCENARIOS
What are the areas of greatest uncertainty?
Research Parks 3.0
HISTORY
Research Clouds
Future Fail!
From Research Parks to...
What this might
look like
What this might
look like
biotech cloud in the MIT area
STRATEGIC IMPLICATIONS
What does this all mean for me?
Rolls-Royce aerospace
(Derby, England)