Saying what we think and thinking what we say.
Hidden in our language is a basic story about the way we think things work. Often, the words we use do not accurately represent this hidden story, while people who use the same general systems terms may be implicitly thinking of a totally different kind of story. Particularly, when people are collaborating, it becomes crucial to be aware of the range of narratives implicitly held in the “field of study.” Then, there is the question of how to organize the set of narratives across the group process.
What if it is the case that, when the team is supposedly looking at “one object” of inquiry, such as “climate change,” they are actually dealing with a multitude of objects, or as Sean Hargens calls it a multiple object? What if, upon investigation, these multiple objects are also complex, hybrid objects, comprised of human and non-human “actants” with diverse kinds of agency? How is it possible for the team to sort out a collaborative approach?
One method has been to work toward the highest meta-systemic view that will transcend and include all the sub-systems held implicitly within the group. This approach is synthetic, but even if such a view is attainable, it often leads to a level of complexity that is impossible to support through action-able inquiry.
Generative Process Analytics™ is an alternative approach to dealing with multiple hybrid objects. By analyzing the generative process dynamics from which they are derived, GPA identifies classes of objects associated with five generative processes and their implicitly held narrative structures. This disambiguates the epistemological component of the inquiry and allows it to be de-coupled from the objects without eliminating the diversity of narratives from the ontological complexity that is being studied.
Inherently, humans are systems thinkers—although the systems they build in their implicit world-views differ over a significant range of scale and complexity. Each and every systems level view is necessary to include since each is also ontologically real, although no one narrative alone is sufficient – even at the meta-to-the-nth highest re-vision. GPA offers a methodology to navigate complex fields of inquiry through multiple process streams by defining and attending to the classes of hybrid objects they generate. As a result, action-able strategies can be designed to optimize the configurations within individual process streams—and valuable feedback can be accessed from the hybrid objects that are discretely associated with them.
2 thoughts on “Generative Process Analytics”