Past/Future, Research/Practice, Science/Metaphor
Does Research Add Value to Management Practice?
The Complexity Perspective

All Academy Session
Academy of Management Meeting
August 6-9, 2000, Toronto

Panelists:

Bernard Avishai (KPMG)
Max Boisot (Cambridge)
Michael Cohen (Michigan)
Kevin Dooley (ASU)
Alan Kantrow (Monitor)
Michael Lissack (Emergence)
Bill McKelvey (UCLA)
Tom Petzinger (WSJ)
Jan Rivkin (Harvard)

Initial Questions/Perspectives
Suggested Readings
 

This session will explore, via a panel discussion, the questions of "what about historical observation is meaningful to the practicing manager?" "what can research contribute to practice?" and "what is the role of 'scientific methods' in dealing with these questions?."  Much of the work of management academics centers on historical observation and in theorizing therefrom.  It is thus oriented about the past.  By contrast, most of the focus of the practicing manager is on the future, be it the immediate tactical next steps to take or the more long range future of positioning and strategy.  This contrast echoes throughout the Academy.

Amongst researchers examining the relationships between complexity and management a divergence has broken out between those who are of the "science" persuasion and those of the "metaphor" persuasion.  The former believe that hard data and mathematical approaches are what create valid inferences from a complexity perspective.  The latter believe that metaphor creates new insight and altered mindsets from which a practicing manager can find alternative paths of action. In general adherents of the first school decry adherents of the latter as "not doing science."  At the same time, adherents of the second school often extol members of the first for generating metaphors and then go on to criticize these same scholars' studies as failing a "so what?" test.

This split echoes in an explicit manner an often-implicit split within management science.  Research is directed at generating and examining historical data, is seldom subjected to the "replication and falsification" tests of other scientific fields, yet inferences are held out as "theory" which should be capable of "informing" if not "guiding" the practicing manager.  The practicing manager is often regarded as an unformed creature too easily swayed by books of the "one minute manager" variety and too seldom engaged in the implications of "scientific research." At the same time, many practicing managers ask of the academics "so what?" and fail to find what they regard as meaningful answers.

This split can perhaps be meaningfully understood when one factors in the effects of time, of history, of the perceived need for prediction, and of uncertainty.  Complexity science suggests that perspective on the problem can be gained by explicitly contrasting the temporal nature of the issues being investigated with their spatial nature.  The vehicle for doing this is a concept known as "state space".

In qualitative dynamics, one describes the instantaneous configuration of a system as a list of numbers; each number denoting the value of some property of the system. In the case of a simple pendulum, the instantaneous configuration is completely described by two numbers---the position of the pendulum bob and its velocity. This list of numbers is called the system's state. The collection of all possible configurations of a system is called the state space. The temporal behavior of a system is then viewed as the succession of states in the system's state space. One can imagine a line being traced out as a system moves from one state to the next. These lines and the rules that take a system in a given state to its next state over time are collected together in the "dynamics" of a system.

Much of management research is a look at the past to gather a sufficient quantity of data (whether in the form of numbers or of narratives) so as to be able to form theories of these lines and rules.  Thus the research is an effort at model creation where the thing modeled is the dynamics of one or more management science objects   a company, a team, and industry, leaders etc. If the management object being modeled is indeed governed by the rules and dynamics so modeled, managers would be able to derive enormous value from the predictive quality of such models.  Alas, the lack of such predictive capability suggests a problem in this modeling approach.

Many critics of managerial research take this lack of predictive capability to be justification for an attack on the types of research being done, the models being created, the objects being examined, and sometimes the very purpose of engaging in backward looking research itself.  Indeed, periodically the Academy goes through a bout of self-examination regarding the poor relationship between the research and scholarship undertaken by its members and the desires of managerial practitioners.  The key stumbling block seems to be prediction itself   the relationship between observed past and anticipated future.

Complexity science offers another view.  Perhaps the problem is not with the managerial objects or theories but with the temporal nature of the models themselves.  The same data need not be viewed as the tracing of a dynamic, but rather as the scatter readings of an attractor in state-space. An attractor is the space described by the list of states a system can occupy. Attractor models do not predict what happens next, but instead outline the rough boundaries of a space of action.  Models of time become instead models of space.  The task of managerial research becomes that of helping to identity relevant attractors (their boundaries and conditions) and to probe the dynamics of moving from one attractor to another.  Questions of prediction no longer take center stage, but instead are replaced by questions of identity, values, boundaries, environments, pressures, and spaces for action. 

Initial Questions/Perspectives Asked of the Panelists:

Bernard Avishai (KPMG) - Where does management research enter into the knowledge management practices of successful firms?

Max Boisot (Cambridge) - How does the relation between practice and research get codified, abstracted, and diffused?

Michael Cohen (Michigan) - How can research based on models have an effect on practice?

Kevin Dooley (ASU) - What is the relation between the models researchers use and the language and mental models which practitioners use?

Alan Kantrow (Monitor) - Where does management research enter into the knowledge management practices of successful firms?

Michael Lissack (Emergence) - How can a complex systems perspective alter the ongoing dialogue between research and practice?

Bill McKelvey (UCLA) - How can complex systems models provide a meaningful direction for research where meaningful is defined as useful for practice?

Tom Petzinger (WSJ) - Do managers have any use for research?  In what form can research be made useful?

Jan Rivkin (Harvard) - Can simulations bridge part of the gap between research and practice?

Suggested Readings:

Dynamics in Action : Intentional Behavior As a Complex System

Networks of Meaning

Cultural Software : A Theory of Ideology

Conquest of Abundance : A Tale of Abstraction Versus the Richness of Being

The Non-Aristotelian Systemic Thinking about "Causation" in Complex Systems