Overview

What is the Complexity in Action Network (CANet)?

The Complexity in Action Network (CANet), a division of Northwestern Institute on Complex Systems (NICO), connects leaders from research, business and government to understand and solve complex business problems through innovation.Collaborative research, design and education occurs between researchers from across Northwestern University and innovators from across industries who see opportunities & necessity in addressing business issues from interdisciplinary, multi-industry perspectives and in making complexity science practical. These collaborative relationships occur through CANet memberships, research engagements and education.

Sample Map of the Network

network

Vision & Strategy

NICO-CANet strives to be the global "go-to" place for applications of complexity science, across disciplines and across industries, by the year 2010. Our strategy for realizing this vision is to:

Use the network to build the network
- Building relationships, trust, and natural extensions of the network.
Demonstrate the value of complexity science
- Educating and sharing of complexity concepts and common language.
- Putting complexity tools and methods to work on real time, real world issues via research and design.
- Co-developing applications and sharing results across industries and disciplines through cases, publications, conference forums, while respecting proprietary arrangements.
- Creating synergies between complexity approaches with the best of what’s known in current disciplines and practices.
Cultivate excellence in knowledge brokering and translation between members, faculty and resources through use of the concepts, tools and complexity practices that we provide to each other.

What is the value of complexity in action?

"The ideas of emergent phenomena and finding the 'simple rules' that define the complex system has direct application to the burning issues I'm facing."
-- Launch Event Attendee

Complexity lenses and tools are developed through interdisciplinary collaboration for and with our members, using complexity science as a common language and method that crosses disciplines and industries. Examples of business issues understood and addressed using complexity concepts and tools include:


.	Sample Issue	Capabilities Needed	Complexity Application	Results
Growth & Innovation	How can we speed the flow of information and depth of insights across a distributed global innovation network?	. Working across boundaries . Leveraging networks . Enabling knowledge workers to reuse information across projects	. Network Analysis . Non-linear Dynamics	. Produce a viral spreading of ideas through informal channels . More transparent and accessible information . Reduce cost of unintentional redundancy
Uncertainty & Risk	How can we anticipate and guard against threats to our brand?	. Discerning the right info . Strategic decision making	. Complex Statistics . Pattern Recognition . Network Analysis	. Recognize emerging patterns of issues surrounding products and operations . Shift strategies & tactics before emerging trends become crises . Influence market directions
Cost Optimization	How do we leverage a shrinking talent pool without having to build in redundancies or pay the price of whipsaw staffing accelerations and lay-offs?	. Determining what to outsource . Anticipating & filling gaps resulting from turnover & retirement . Identifying pockets of excess capacity	. Agent-based Modeling . Network Analysis	. Model scenarios of hiring, placement, replacement and cross-training . Model supply and demand . Shape/reshape talent network to address market fluctuations & increase worker capacity
Inter- & Intra- Organizational Collaboration	How do we optimize the potential for strategic collaboration with our customers and suppliers by sharing product development and marketing initiatives?	. Operating in different cultures under different rules . Speeding adaptation . Developing consultative vs. transactional relationships	. Analysis of non-linear interactions . Agent-based modeling . Economic experiments	. Identify synergistic opportunities across stakeholders . Uncover working assumptions about the business environment . Visualize & weigh idea impact