Complexity Space Landscape

The Complexity Space Landscape is derived from the original concept of a fitness landscape or adaptive landscape in evolutionary biology. It was further developed by Ralph Stacey to represent potential states of a complex adaptive system based on the degree of certainty and level of agreement on a particular issue.

LSThe Complexity Space Landscape offers a visualization of how organizations define the current and desired states of their operational, product or strategic patterns:

The “status quo” state is a system’s “business as usual” space, where everyone involved knows what to do, what results to expect, and what behaviors will support these patterns.

The “mutation” state of the landscape is where little agreement and certainty exists about what or how things are happening. We like to explain this state as one of “mutational opportunity.”  It is in this space that diverse and varied information, networks, and engagements can provide significant value by “driving” intuition toward understanding.

In the “innovation” state, the organization seeks to “do what it already does better.” It engages in a continuum of controlled experimentation, engagement and self-organization.  This is the space of continuous improvement and evolutionary change.

CSLandscape_no diruptionNotice that although the  diagram to the right shows the three states in a “linear” progression, “status quo,” “innovation,” and “mutation”  exist simultaneously across the system. For example: at any given point in time, Payroll may be perfectly content in the “status quo”; research and development may be  exploring  the “mutation” space; and manufacturing operations may be engaging in an agile development improve efficiency through innovative trials.



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