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Map-makers, Explorers, and Tricksters:
New Roles for Planning and Prediction in Nonlinear, Complex Systems

 

Decreasing Our Ignorance in Nonlinear Systems:
Recognizing the Identity of an Organization

The unpredictability found in nonlinear, complex systems has a seldom discussed property that can actually lead to a decrease of our ignorance of them. Exploiting this property on the part of leader/planners can help facilitate their shift from thinking of planning as a linear to a nonlinear activity. Instead of being linear prognosticators, leader/planners can be facilitators of a greater recognition of an organization's identity, i.e., its core competencies, strengths and limitations, and unique perspective on the goods or services it makes or delivers. This property has to do with approaching the ongoing measurement of a chaotic or complex system in terms of a gain in experimental information (Abraham & Shaw, 1984; Shaw, 1981). This gain in experimental information, or in other words, decrease in ignorance, derives from an ongoing comparison of current measurements with ones conducted in the past, i.e., each new assessment of initial conditions is compared with previous assessments of past initial conditions.

The gain in experimental information comes about by continually remeasuring the system - we conduct the same assessment at a later time (see Appendix A, Figure 3). We then compare the new measurement at the new time with what believed to be the future state of the system based on projections from our previous measurement at the initial time. But remember that our projection into the future based on the initial measurement had to be extremely general and unable to pinpoint future states of the system since SIC in the chaotic system "blew-up" the small ignorance or missing information we had at the initial measurement. But notice that the ignorance of our new measurement or its missing information has not yet "blown-up" and is, therefore, much more precise than the projection based on the past measurements. This means that the new measurement has decreased the ignorance expressed in our earlier projection into the future. That is, we know more about the system at this current time than was available at the earlier time when we projected into the future.

We can then take this current decrease in ignorance or gain in experimental information flowing it backwards to the earlier imprecision, ignorance, or missing information (see Appendix A, Figure 4). This backward flow, in turn, shrinks the earlier imprecision, the degree of our earlier ignorance about the future by increasing the amount of the amount of information available to the system even at the earlier time. What's going on here is that by an ongoing measurement process and the comparison of these ongoing measurements with earlier ones, the system is yielding more knowledge or information about itself, no matter how much the nonlinear amplification in the system is making future states unpredictable. In such a way, a system, its observers and planners, can know more about itself, in terms of where it was before than it could have possibly known at the earlier time. Accordingly, a more precise knowledge of where it is now, i.e., its identity, yields potential greater knowledge of where it is heading.

A planner by conducting ongoing present assessments and comparing them with earlier projections of the future gains information and decreases ignorance about what the system really is at its core, i.e., its core competencies (what specific operations, tendencies, propensities, and directions, practices, and skills form the essential identity and capacity of the organization). This shifts the role of planning, though, into a process of map-making, comparing temporal regions of a company's evolution to engender greater knowledge of the geography of an organization's identity. This role for planning is different than merely searching for trends since the focus is not on looking for trends occurring now and continuing into the future as much as it is in gaining information about where the organization was, and then continues to be, and will continue to be into the future. The planner here makes maps that connect past and present in feedback loops of information, opening up vistas into the future. It may be that this gain of information on a chaotic attractor is one of the bases for the "intuitive" insights that leaders use to guide a business or institution into the uncharted regions of the future. This gain of information about an organization s identity is related to another feature of predictability of nonlinear systems to which we now turn.

 

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