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.
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.
Notice that although the above diagram 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 wanting to further explore the “mutation” space; and manufacturing operations may be engaging in a Lean Six Sigma process to improve efficiency.