May 18-19, 1995
Gus A. Koehler, PhD.
The question addressed by the conference was: Does chaos theory provide useful management insights for disaster organizations responding to a major disaster over an extended geographical area such as a city, county or region? Major disasters have a low probability of occurring but when they do they have devastating consequences. Designing response structures for such events is a difficult task, particularly when public resources are low.1 Generally, a disaster occurs when the local emergency response system's means for managing and coordinating a response are overwhelmed and require outside intervention to succeed.2 For example, a medical disaster occurs when the local emergency medical services system's means for managing and coordinating the medical response, normal triage standards, transport, medical care and local mutual aid resources are overwhelmed by a multitude of victims with differing injuries (crushing vs. toxic gas inhalation for example), who are usually distributed over multiple locations.3 In short, the normal ways of providing emergency medical care cannot be expanded to deal with the problem. State, federal, local government and private response agencies must become involved in the relief effort.
Major disasters involve a multitude of different organizations that provide a broad range of resources and services. To help set the stage, we will focus on just one of these; the emergency medical services system. The Emergency Medical Services System (EMS) responds to day-to-day emergencies such as automobile accidents and plays a critical role in any casualty producing disaster. In both cases the overriding goal of the state and local EMS response is to save lives and to reduce morbidity.
For day-to-day EMS the performance standard is called the "Golden Hour." EMS systems must be able to rescue, triage, stabilize and transport a victim to a hospital where they receive appropriate care all within one hour. The Golden Hour standard can be met because the type, severity, and likely geographic distribution of the injured and the distribution of injuries is relatively well known and predictable. The EMS response system can be organized to meet this profile.
A medical disaster severely disrupts this day-to-day EMS system as well as it's ability to form an emergency medical disaster response system. A new structure must emerge to respond to these needs. While the response is organizing, the majority of earthquake victims, often numbering in the hundreds if not thousands, are being rescued and awaiting care. For an earthquake, most victims are rescued within the first 24 to 72 hours. This 48 hour time period defines the performance window for EMS action. People begin dying and their morbidity increases with every passing hour. Clearly, the faster the EMS disaster response can organize itself, the better it is for the victims.
Unfortunately, the effort to organize a disaster response structure involving multiple public, private, and non-profit agencies is disrupted in a number of unpredictable ways. One or more of these characteristics probably apply to almost all response organizations following a disaster.4
The type of disaster that could occur at any time is unpredictable. Earthquakes, hazardous materials releases are inherently unpredictable. Hurricanes, tornadoes, civil disturbances, and floods are more predictable but the exact time when for example, casualties will occur or when they will need transport is unknown.
Where a disaster will occur is often unpredictable. The exact location of a disaster can not be predicted (earthquake or hazardous materials release for example), or the way that it will geographically progress is unknown. For example, the path of a tornado or of a civil disturbance can not be precisely predicated. This can cause considerable variation in the number and severity of injuries.
How a disaster will unfold in geographic space over time is often unknown. The rate that a disaster extends itself geographically over time can effect the generation of injuries and deaths.
The type and distribution of injuries in space and time is often unknown. Particular types of disaster do have injury profiles. For example, an earthquake produces lacerations and crush injuries. A hazardous materials incident can produce inhalation injuries. But lacking knowledge of the space-time distribution of where the disaster occurred and the rate it is proceeding at, it is difficult to predict the profile of injuries particularly if, for example, an earthquake and a hazardous materials release occur simultaneously.
Which elements of the EMS system or of supporting organizations (law enforcement for example) will be damaged, how they are damaged, and the resulting delay in their response is unpredictable. Medical resources such as personnel, medical supplies, ambulances, hospital beds, and communication links can be overwhelmed, damaged or distorted. Their location, distribution of response units, and availability is often not congruent with the type, volume, and distribution of injuries. The initial starting conditions of any one agency affects the way its own structure emerges and how it relates to other agencies.
Self-organizing efforts by citizens, responders in the field, and other emergency organizations at the state, federal level, non-profit and private sector level will create unexpected communications paths and response structures. Following a disaster, people in the area organize themselves to rescue neighbors and perform other immediate disaster response activities. EMS responders, hospital staff, fire personnel, and others will be repairing their disrupted and damaged systems, and creating new and often unplanned organizations for delivering. Volunteer organizations and other private response groups may suddenly appear and demand that their needs be immediately met.
Information about the entire emergent disaster response structure or even parts of response (including how it extends across the community, city, operational area, the status and organization of the regional response, state response, and federal response) is incomplete. A disaster response structure is "emergent" because it did not exist at a time prior to the disaster. It involves the birth of new units or the restructuring of old ones at the work group, organizational, interorganizational, community, or regional level that are more or less adaptive to a particular circumstance within the disaster.5 It is difficult to not only identify what and where the new structures are or how old ones have changed, but also to identify the form of inter-group and interagency connections.
Existing strains between organizations may be exacerbated. Existing strains between organizations due to competition with other organizations, organizational placement (fire service or police for example), under funding and under staffing due to disaster preparedness being given a low priority in comparison with immediately pressing needs, and other factors may come forward or be revealed making inter organization coordination more difficult.6
Because of initial starting conditions, and varying resource demands, critical activity rates within and between organizations drive each other and the overall response in unpredictable and complex ways. The EMS disaster response depends on tight and effective coordination between many different public and private organizations including, for example: citizen self-organizing rescue efforts, ambulance companies, law enforcement, hospitals, pharmaceutical supply houses, surface and air transport, military forces, and federal, state, and local government agencies. The rate of victim rescue affects how quickly transport vehicles must be identified and dispatched which in turn affects how many injured people are waiting for care in a hospital emergency department, emergency department staffing, etc.7 These factors are driven by the availability of communications, of health care personnel and supplies, and by whether transport can move necessary resources to where they are needed.
Barbara Adam in her analysis of the Chernobyl reactor accident, provides an excellent example of how such problems can lead to a catastrophic response:
The difficulty of appreciating and handling complexity, I want to suggest, is tied to the tendency to think in terms of one-dimensional, linear event chains associated with aims, thus neglecting to take account of feedback and amplification, of side-effects and exponentially accumulating processes. To achieve the urgently required cooling down and thus renewed stability of the reactor, the operators activated all eight pumps instead of the allowed maximum of six. Whilst the operators acted in accordance with their one-dimensional safety goal, the reactor went into a series of predetermined interconnected safety measures which proceeded along a very different rationale and lay outside the operator's control: operators and system functioned according to different underlying theories, assumptions, principles, time scales, implicit rules and mechanisms. They were on a collision course that ended in catastrophe.8The various ways that a disaster disrupts individual organizations and efforts to develop a disaster wide response system leads to several management issues for EMS and probably for other organizations as well:9
These management problems are serious. Can chaos theory provide any insight as to why these organizational phenomena occur and, assuming that such an understanding exists, are there strategies that management can adopt that may improve the response? This paper addresses these questions by first looking at how chaos theory and the concept of social time help to understand the process that causes organizations to become disordered. Second, it answers this question by showing how self-organizing processes, percolation theory, and N-K theory helps to explain the reemergence of response organizations and large scale response structures.
What Is Chaos Theory?
There are many events that we can predict in organizational life, the arrival of our pay check is an example. Month after month we know the exact date that we will paid on. The pay system cycle is predictable; we can know that so many days from today a pay check will arrive.
Other organizational systems, such as the amount of time involved in handling service orders is not predictable. One service order can take a great deal of time, another no time at all, leading to wide variations as time passes.10 The time it takes to complete the next order cannot be predicted because different processing rules may apply and/or the complexity of the order itself can not be predicted. In this case, and in other similar systems that are aperiodic and sensitive to small changes, researchers use chaos theory to investigate its long term behavior, and its dynamic of change.
"As a qualitative study, chaos theory investigates a system by asking about the general character of its long-term behavior, rather than seeking to arrive a numerical predictions about its exact future state. ...[I]t typically asks such questions as, what characteristics will all solutions of this system ultimately exhibit? And how does this system change from exhibiting one kind of behavior to another kind?"11The results of individual measurements can not be predicted but a large number of measurements taken over an extended period of time reveal a hidden pattern. Responding to service orders exhibits such a deep pattern. Merry provides a useful definition of chaos: "Chaos is the irregular, uncertain, discontinuous aspect of change within the confines of a patterned whole."12 Given our discussion of how unpredictable a disaster response is, chaos theory may be a useful way to understand this complex phenomena.
Workplace Rules, Fields Of Action, And Organizational Morphogenesis
Disaster workers are in constant motion at various locations through space and time as they simultaneously apply the Incident Command System (ICS) or other management systems and develop tactics to organize and implement their response. Generally, they are applying policies, work process, work behaviors and attitudes, or "workplace rules" within a "field of action." which influences it.13 The field of action is defined as the physical workplace and the external environment. The field of action is multidimensional and highly complex. In the case of a disaster, the field of action is influenced by the initial conditions that an organization finds itself in following the often abrupt on-set of the disaster. Kiel tells us that:14
It is the interaction of the [workplace] rules of motion with the field of action that determines the direction and result of motion in the workplace. The dynamic created by the interaction of the `rules' and the `field of action' lead to agency outputs and performance.We will extend this concept to interorganizational activities across the entire area of the disaster, including organizations playing support roles outside of the area. In this context workplace rules refer to rules for interorganizational coordination and communication such as with an emergency operations center (EOC). The field of action would refer to coordinated activities, disputes, etc., between organizations and the environment that influences them.
The abruptly initiated process of transition from one type of organizational pattern--day-to-day response or planning and practice--to another organizational pattern requires a change in workplace rules within a unique, disaster created field of action.
A change process links the emergent organizational and system wide response structure with the earlier one. As the field of action changes, so changes the organization's functions and accompanying work rules, which in turn change its' structure. Organizational survival and the emergence of the response system is related to these self-organized adaptive activities.15 The emergent structure stabilizes long enough to provide some range and level of services before changing back to its pre-response form.16
Having said this, we still have no idea about what the process is that links environmental changes to the organization's response. Our earlier discussion of what happens to an organization following a disaster, efforts to form a disaster response system, its sensitivity to initial conditions, and the limits of rational management could be interpreted to mean that there are no rules or characteristic stages that define the origin of such changes, or how or what new structures will emerge, how stable they will be, or how this process happens. We also don't know how interagency structures emerge.17 There is a large literature that carefully describes and characterizes organizations at various points in this process, and on interorganizational behavior, but there is no general theoretical explanation for the process of disaster organization emergence, structure, stability, reintegration into the day-to-day system, and cross-system interaction.18 In what follows, we hope to show that chaos theory may throw some light on the processes associated with the first three, and last element.
Such a time based, continuous process oriented map of how organizations change under extreme conditions would provide an analysis of a deeper level than organizational workplace rules and the field of action does. Workplace rules and the field of action would create unique variations that emerge from these deeper processes.19 In a way the problem is analogues to how an individual organism grows. While each individual is different, they are also a member of a particular species, and exhibit a general body plan. Their individual growth process ("morphogenesis") obeys very specific rules that guide growth from an egg to an adult and on through death. 20 These deeper rules guide the formation of organs, bones, etc., so that functioning but different and adaptable individual organisms emerge. Is there an analogues set of organizational morphogenic rules that map the process of how an organization is disorganized then reorganized? Can we look below the surface features of a disaster and find more general principles that can be used to speed the response along?21 Are there similar rules that apply to the "morphogenesis" of large scale response systems? The term "morphogenesis" will be used to refer to this deeper set of organization, response system dissolution/reforming rules. We will assert for the sake of discussion that such morphogenic rules exist and present some preliminary empirical evidence of how they might work.
In summary, our hypothesis is that successful disaster response management involves the creative application of morphogenic and workplace rules within the disaster field of action such that an effective response pattern is emergent (self-organizes to a significant degree) in space and time to meet a qualitative objective such as saving lives.
Chaos Theory, The Rules Of Organizational Morphogenesis, And Social Time
Disaster response organizations and response systems are dynamic systems. A dynamical system consists of two parts: a rule or 'dynamic,' which specifies how a system evolves, and an initial condition or 'state' from which the system starts." Some dynamical systems such as those being discussed here, evolve in exceedingly complex ways, being irregular and initially appearing to defy any rule. The next state of the system can not be predicted from the previous one. Henri Poincare discovered that the reason for this did not lie in the rules for how the system evolves but rather in specifying the initial conditions that the rules start from in their application. More exactly, chaotic dynamical systems are characterized by "sensitive dependence on initial conditions".22 Chaos theory is a way to analyze such systems.
It turns out that in mathematical theory the change from order and predictability into unpredictability or chaos for dynamic systems is governed by a single law, and that the 'route' between the two conditions is a universal one. According to Pietgen and his colleges: "Route means that there are abrupt qualitative changes--called bifurcations--which mark the transition from order into chaos like a schedule, and `universal' means that these bifurcations can be found in many natural systems both qualitatively and quantitatively." 23 Put another way, chaos is a type of non-linear behavior emerging along a universal route. At a certain point along this route ("close to the edge of chaos") organizations become highly sensitive to initial conditions and may abruptly change.
Our earlier description of the effect of a disaster on organizations and response systems shows that the form they take appears to be influenced by the initial conditions they experience following the disaster. Having said this, we still do not know if such organizations or systems move from a relatively stable state into a chaotic one or if they are simple adjusting their behavior within a given and predictable set of possibilities consistent with each organization's work rules.24 The two conditions are very different and require different management strategies; in the earlier case the existing management strategy is useful; in the latter, a new one is necessary to deal with an emergent process and accompanying structure. The application of chaos theory to other social phenomenon has been helpful in clarifying this issue.25 If it cannot be empirically shown that at least some disaster response organizations and response systems come close to or enter into chaos, then disaster management has little to learn from chaos theory. More to the point, does the "single law" and "universal route" apply to a disaster response? The Disaster Response Is At The Edge Of Chaos
By applying the logistic equation to the appropriate disaster response data it is possible to determine if a disaster organization or response system traces the universal route to chaos.26 The logistic equation is particularly useful for showing the relationship between various competing but interdependent forces, such as that between an animal population's growth and some limiting factor in the environment (chickens, foxes, and chicken feed for example). Priesmeyer provides a detailed discussion of how the formula is applied to a large number of phenomena to produce what is called a logistic map (see page 60). The level of activity of a particular organization or system is displayed on the X or vertical axis, and the stability of the environment on the k (horizontal axis) ranging from stable and calm (1.0) to highly energetic or disturbed (4.0). Each point on the Logistic map represents an organizational or system state at a particular moment in time. It is important to keep in mind that this point is not a random point. The logistic map shows that as the level of activity increases and the environment becomes more turbulent, the organization moves from a relatively steady state (single line) through a bifurcation point (split into two lines) and on to the edge of chaos. Before turning to a more detailed discussion of these three states, does the logistic equation when applied to disaster response data fit this pattern of behavior ?
Priesmeyer's and Cole's conference paper, "Nonlinear Analysis of Disaster Response Data," applies the logistic equation to a time series data set representing 146 valid responses from interviews with 257 key participants (EMS, fire, police, and other personnel) in 106 organized disaster responses.27 The behavior of these individuals is assumed to characterize the progress of the response to a disaster generally. The time series was derived by determining the number of hours from initial impact before the individual became involved in the response and the time they terminated their response. According to Priesmeyer28:
The resulting data set was ..."sliced" in one hour intervals to create a frequency distribution of the activity levels. Specifically, the data set was searched to count the number of individuals involved within the first hour after impact, then searched again to identify the number of individuals involved after one hour but before two hours after impact. Twenty four of these searches provided a time series indicating the number of individuals involved in disaster response during each hour for each of the first 24 hours.
[The logistic equation Xn+1 = kXn(1-Xn) was applied.]...In this particular case, the variable X can be taken as the level of activity of all respondents at the initial condition and during each subsequent hour. The constant k is a parameter defining the level of disorder in the environment. The value of k can be computed from the data to indicate the level of stability or chaos in the system.
Chart 1 shows the statistically significant results of this analysis. The data indicate that the level of disorder among responders occurring during the first twenty-four hours following this group of disasters is at the edge of chaos.29
An important caveat is that the data are for a heterogeneous collection of disasters with varying levels of activity. Aggregating them together might create a chaotic time series. This approach of aggregating cases across disasters and disciplines has been used to arrive at generalized findings about disaster management.30 Additional efforts need to be made to collect similar time series data for individual disasters to see if the logistic equation fits as well. Using The Logistic Map To Track Disaster Organizational Morphogenesis
Recall that the organizational states depicted by the logistic diagram take place during a twenty-four hour period. Also, different organizations and different systems will move to different points along this line depending on resources available, social time/space, and the level of disorder being introduced by the disaster.31 In what follows, the characteristics of a how an organization is affected by a disaster appear to be predicted by the logistic graph, giving it face validity. This conclusion was supported by conference participants, all of whom were experienced disaster responders. They saw the event as a non-linear process and consistent with the progression of effects described by the logistic equation. Further research is necessary to develop and support these suggestions.
Examining the logistic map, we see that a single line curves from the origin up to a point where it divides or bifurcates into two lines. Regardless of the initial conditions of the system (x) the result will always fall on this line so long as the stability of the environment (k) is between 1 and 3. This means that so long as the level of disturbance in the environment remains below 3, the organization or system in the environment will be more or less stable.32 The points on this line seem to "attract" the organization or system into a particular, stable, orderly state. Management is able to absorb the disturbances that are disrupting the field of action within the existing rules of work because:33
"Out of the major stem we see two branches bifurcating, and out of these branches we see two branches bifurcating again, and then two branches bifurcating out of each of these again, and so on. This is the period-doubling regime of the scenario.
Let us explain very crudely what period-doubling means. Where we see just one branch the long-term behavior of the system tends toward a fixed final state... This final state will be reached no matter where...we start. When we see two branches this just means that the long term behavior of the system is now alternating between two different states, a lower one and an upper one. This is called periodic behavior. Since there are two states now, we say that the period is two. Now, when we see four branches all that has happened is that the period of the final state behavior has increased from two to four.... Beyond this period-doubling cascade at the right end of the figure we see a structure with a lot of detailed and remarkable designs. Chaos has set in, and eventually...chaos governs the whole interval.... 34
The bifurcation point, and the periodic behavior that begins there is important. Organizations can no longer occupy one point on the line; only two distinct organizational states are available.35 Which state will be occupied cannot be predicted. During this process the organization seems to "choose" one of two paths; one that might lead to an improved ability to deal with its environment or a second that does not.36 An organization can get "locked" into one of the two possible states and be unable to shift to the alternate state. As time goes by and the environment becomes more disturbed and more resources are committed the organization may oscillate between these two points.
If the environment becomes even more disordered requiring the commitment of even more resources or their exhaustion the organization is forced to occupy any one of four structural states, then eight, until chaos sets in. Prediction of the next organizational structure becomes progressively more difficult. Rephrasing this in terms of individual or interorganizational interactions, a series of ever increasing self-reinforcing "errors" are made by participants, deviating from established workforce rules and their relationship to the disaster's field of action.37 These continously repeated errors become amplified and redefine the functions of the organization which in turn redefines its structure. The errors increase the organization's sensitivity to small changes in the environment (sensitivity to initial conditions) which in turn cause large changes in the organizations structure. Thus "...process and structure become complementary aspects of the same over-all order of process, or evolution. As interacting processes define temporary structures...so structures define new processes, which in turn give rise to new temporary structures."38
To summarize what happens to management efforts at and following a bifurcation point:
When chaos occurs a...system does not retrace prior identifiable sequences of behavior and does not evidence obvious patterns in its behavior. Chaotic behavior thus appears extremely disorderly since patterns over time, a symbol of orderliness, do not appear to exist. Chaotic behavior simply skips from one identifiable point to the next, yet never extends outside clear and distinct boundaries.40Returning to Priesmeyer's and Cole's data, we find that disaster systems do not enter the region of chaos. They exist at the edge of chaos.41
The logistic map shows that the opportunity for true system change is built into the [disaster response] system, but is only possible when the system is operating in or near the chaotic region (when k exceeds 3.7). One will note that the derived value for k of 3.66 is very near but does not exceed the edge of the chaos domain of 3.7. [Italics in the original.]The important point is that at or near the boundary of chaos it appears that the ordered structure of the disaster response agency loosens, potentially making new behavior possible. The response structures are no longer oscillating between two or more states. It is at the edge of chaos that sufficient fluidity is achieved by continuous "error" making for new work rules and a redefined field of action to emerge and be absorbed into a new but not necessarily more adaptive organizational structure.42 Organizational changes traced by the logistic diagram do not necessarily lead to a rational emergent process or structure; they simply undergo certain characteristic changes at certain points which workers and managers must respond to. Interestingly, such changes often can lead to structures with an increased level of organization, that are more complex, and are capable of doing more work, than the previous state. Kiel suggests that "this is due to its increased capacity to attract, utilize, and organize available energy for its creation and maintenance."43 Recent work in evolutionary theory and simulation studies supports the view that organisms at the edge of chaos tend to be highly adaptive.44
Research by Kreps seems to support our finding that a multitude of different and often complex organizational forms can emerge. According to Kreps, 423 different short-lived organizational systems can emerge during the response phase. Less than half exhibit a rational structure in how they go about doing things.45 Ikijiru Nonaka suggests that: "Chaos widens the spectrum of options and forces the organization to seek new points of view. For an organization to renew itself, it must keep itself in a non-equilibrium state at all times."46
Here, the response organization is renewing itself to respond to a particular type of disaster with its own timing.
It may be that this new or adaptive response structure emerges from a "phase transition" at the edge of chaos. There are two types of phase transitions: first order and second-order.47 A first-order phase transition involves a sharp change from one physical state to another. An example is the rapid transformation of water to ice. The change is very abrupt and well defined. A second-order phase transition takes more time to accomplish and is less precise. Once a second order phase transition starts, no clear cut structure remains or immediately emerges but there are lots of little structures coming into and going out of existence. Efforts to establish a "better" order or to "select" a particular organizational structure among many possible ones is management's task. This structure is reinforced by what is called a path-dependent process; that is, once the structure begins to aggregate, there is a tendency to direct resources towards that aggregation rather than to other alternative ones.48 Both of these concepts--phase transition and path dependent processes--are important to understand how large, geographically extended structures may emerge and are more fully developed below.
Drawing together what has been said about the edge of chaos:
Generally, the map of disaster organization morphogenesis defines where an organization or response system is on the logistic diagram. Specific levels and types of organizational structure emerge following a specific sequence depending on available resources and on how disordered the environment is. Work force rules and the field of action ride upon this deeper processes as does structural stability. Even the manner in which the new organization forms through a second order phase transition appears to have its own deep defining process (organizational fragments forming into the new structure). The location of disaster response on the logistic map appears to be exactly what we are looking for. It helps to understand the origin or emergence of disaster response structures and why they take the form they do.
Social Time And The Logistic Map
The ability to collect time-series data is critical to developing the logistic diagram. Time-series data is linear, has a specific duration (second, minute, hour, etc.), is tied to clock time, and must be quantitative. Time series data is used when applying the logistic equation to show how certain structural changes occur according to a quantitative relationship between environmental disorder and the commitment of resources. However, people do not experience time as uniform segments. They experience it qualitatively. Phrases like "will this day never end" or " I never have enough time" reveal time's qualitative aspects. If different people and organizations experience social time in qualitatively different ways, then problems with communications, entertainment, defining and meeting MBO objectives, intra- and inter-organizational coordination, defining and taking action, etc., may occur particularly if social time changes in its qualitative structure following a disaster. Further, it may be that the phenomenon described along the logistic graph reinforces or are themselves reinforced by such changes, possibly in unpredictable ways. The point is that, from the actor's perspective the logistic graph is embedded in social time. Evan's paper, "Disaster Responder's Perception of Time" explores the relationship between social time and disasters.49 After developing what is meant by "social time" the concept will be used to deepen our understanding of the logistic map and its application to disaster management.
Social time is an ordering principle that coordinates, orients, and regulates interactions between people and groups.50 Everyone develops temporal models based on individual or group relationships that matter to them. These models are not "ideal" in the sense of being defined by an external universal standard such as a clock. Individuals create time models of how time is patterned and how it flows. For example, temporal patterns can be circular based on the round of the seasons or linear and extending indefinitely into the future. How quickly change occurs and its constancy and uniformity are example of the social construction of time's flow. Concepts of causation, prediction, personal ability to influence the future, readiness to act (all culturally defined) as well as to whether a person feels that they can create their own future (fatalism vs. self-determinism) are related to this temporal constructing process.
For example, collectively remembered disaster experiences affect what individual group member responds to during and following a disaster. Following the Loma Pareta earthquake, some Nicaraguans refused to enter shelters fearing an after shock. This behavior is consistent with their earlier experiences of after shocks and when injuries occured.51 The affects of some disasters extend forward in time in that they continue to affect the mental and physical health of victims and responders. The victims develop their own qualitiative definition of time based on such events.
"Temporal perspective" is an important element of social time and is particularly important for disaster response:52
This subject...covers the relative importance of the past, present and future as well as planning density [how much can be done] for each of these modalities, differentiation or `realness', extension or distance to events, and evaluation of feeling and assessments about the past, present, and future.All of these temporal model creating factors are largely unconscious and "taken-for-granted". They are tied together into what Evan's calls the "temporal signature".53
Pattern and flow and various aspects of future perspective are always present, always affecting each other, and always reflecting and shaping the way individuals relate to their various environments. So to understand these things you have to consider the whole temporal network--at least with respect to future time horizons and attitudes toward the process of change....Temporal signatures vary from individual to individual by education, social class, and other factors.54
Generally, a person's sense of identity depends on "continuity in temporal perspective, especially future time perspective. ...[P]erspectives on the future are more permanent than other elements of time...If the continuity of the future perspective is disrupted one becomes estranged from one's self leaving an uneasy feeling of strangeness and unfamiliarity." 55 Personality shapes and is shaped by individual and social time signatures.
For the purposes of this paper, we will speculate that disaster response agencies have characteristic temporal signatures, just as individuals do, and that these concepts also apply to interorganizational relationships. All schemes of periodization of individual and organizational life are authoritatively defined in the sense that they reflect management's view, tempered by the employees, about what is "good" or "right" for its operation. Studies of Western organizational culture note that most managers view time as "monochronic" or extending like a line that can be divided into equal segments into the future. "Time is a valuable commodity that can be spent, wasted, or made good use of...."56 In contrast, "polychronic" time is defined more by social relationships and what can be accomplished than by a clock. "Relationships may be more important than efficiency; therefore, rapid completion of a task or punctuality may not be valued as highly...."57 Generally, the organization's temporal signature defines a sort of dance that people engage in as they collectively create organizational life. Managers and staff define the pattern and flow of time, and thus the rhythm of this dance.58 The ability to plan for and control one's future varies by organizational rank; those higher in rank have longer time horizons than those lower in rank. Different agencies vary in their capacity to mobilize their personnel, to organize their response, to rhythmically entrain with other organizations, to perform tasks, and to meet time deadlines.59 Different groups and individuals within the organization may be either future or past oriented making it difficult to coordinate to achieve common goals. From this perspective, temporal continuity, particularly future time perspective, appears to be important to the cohesion and internal functioning of the group, to the interaction between the multiple groups that make up a complex organization, and probably to inter-group relations.
Exactly how responders and victims are affected by or adapt their temporal signature following a disaster and the disruption of their future perspective is not fully known. Evans theorizes that a person's ability to act may depend on their belief in whether or not they have a future. The sudden occurrence of a disaster severely qualifies prior concepts of the present and the future; the future no longer unfolds in an orderly, predictable way that can be influenced. The sudden onset of a disaster "brings one crashing to the present." It is like a temporal signature phase transition. One of three possible temporal positions can result:
Reinterpreting Disaster Management Problems Using The Logistic Map And Social Time
Taken together, the morphogenic rules of the logistic map and social time suggest some interesting ways to interpret why various disaster management problems take the form they do.
Disaster initiated changes in social time may be related to and reinforce organizational states on the logistic map. Looked at from the viewpoint of social time, the logistic map appears to trace varying organizational timings; a single timing leading up to the bifurcation point, a discrete number of timings depending on the number of periods following this point, and a very large number of possible timings in the chaotic region. Interestingly, the logistic map suggests that the collapse of a group's future orientation into the present will occur at the threshold of chaos. The resulting organizational phase transition could take a number of paths depending on whether responders attempt a "restoration of flexibility", experience a "permanent loss of flexibility", or are caught up in "presentism".64 If responders feel involved in meeting immediate needs, they may be more likely to engage in the creation of a new organizational form. Each of the three social time responses represent a different foundation for error making which, when combined with other factors like availability of resources, and personnel, may lead to a different organizational form.
What EOC disaster managers know about a disaster is mediated by response personnel, media, and various scientific disciplines (weathermen, seismologists, etc.) all of whom have differing time signatures, are not temporally calibrated with each other, and whose organizations occupy different positions on the logistic map. A complex disaster temporality emerges from the experience and interpretations of multiple groups; for example, there is a victim's time, a responder's time, a watching public's time, and politician's time. Making the disaster knowable and thereby understandable to themselves and others implicates the biases and experiences of the interpreter and their measurement method, be it qualitative ("what's taking them so long?") or quantitative ("we are two hours into the response"). The convergence of all of these perspectives makes it difficult to define problems and to develop solutions, particularly if there is little congruence between planning time (monotonic) and that of the victims ("presentism"), the public, media, and politicians.
The effectiveness of MBO and other clock time oriented management tools depend on the ability of an organization to define future objectives. This activity could be limited by where an organization is on the logistic curve and by its related social time. Relatively short term planning is probably characteristic of an organization at the edge of chaos. This means that organizational solutions might solve the immediate problem but be less inclined to address longer term ones. There are also serious problems for long term strategic planning. If we cannot predict individual organizational forms or structures following a bifurcation or at the edge of chaos following a disaster, then the effort to specify longer term organizational relationships may be impossible. Our efforts may be limited to the supporting processes that permit the rapid emergence of self-organizing structures.
According to the logistic diagram, sensitivity to initial conditions increases as an organization moves up to and through a bifurcation point and on to the edge of chaos. Causality becomes much more complex, particularly within the context of social time. This may explain why changes in simple rules or applying new ones, and what are seen as relatively minor changes in the rates of interactions between organizations can have substantial and unpredicted consequences. Each of these factors ride upon these deeper morphogenic rules and related time signature.
Organizations with differing organizational time-signatures and occupying differing places on the logistic map could disrupt intra- and inter-organizational coordination and the emergence of a disaster wide response system. The disaster area has a social time and logistic map geography that varies from point to point. For example, organizations exhibit different social time states according to how badly they were impacted by the disaster. These, and other factors mentioned by Koehler and Comfort below, may condition how quickly a disaster wide response system emerges.65
The Emergence Of Geographically Distributed Large Scale Response Systems
Up to this point the discussion has focused on how organizations and systems are disrupted by changes in their environment. Morphogenic rules imbedded in social time were discovered that underlay the deeper organizational emergent process. The papers presented by Koehler, and Comfort suggest that similar rules might apply to the way large scale, geographically extended disaster response structures emerge from the disconnected fragments that occur during a phase transition.
Immediately following a disaster organizations occupy different places on the logistic map. Some are connected with each other, others are not. EMS system fragments include: sites where the injured are concentrated, hospitals, city, county, state or private EOCs, ambulance dispatch centers, communications centers, supply or staging areas, etc. These elements need to be connected and coordinated to constitute an EMS disaster response system. Percolation theory,66 and the concept of an N-K system may help to understand how this connecting-up process occurs.
According to Peitgen, Jurgens, and Saupe: "When a structure changes from a collection of many disconnected parts into basically one big conglomeration, we say that percolation occurs."67 Percolation can occur very rapidly across a large number of disconnected elements. Such an event happens when the probability of one elements connecting with another passes the percolation threshold. Using this concept, Koehler suggests that:68
"This probability has been measured experimentally using a simulation of probabalistically determined points. It is approximately 0.59...This suggests that each cluster throughout the disaster area must have almost a 60% chance of being connected to another for a percolation [structure] (EMS disaster response system) covering the entire area of the disaster to emerge. ...[T]he time it takes to get to this point will be longer for a large number of [organizations], in fact exponentially longer...."It would seem that when the information processing capacity of the various components of a systems as measured by the probability of being connected with other elements reaches the percolation threshold there is a sudden change, a phase transition, with connections extending across the entire disaster area.69 The stability of the system is probably related to maintaining the probability of connectedness, the number of connections between organizations, and the degree to which organizational maneuvering and competition disrupts the network.70
Comfort uses the concept of the N-K system to analyze how disaster systems reallocate their resources and reorganize their actions to respond to changing needs. Her work helps to clarify how various connectedness related factors condition the emergence of large scale structures. Drawing on work by Kaufman, Comfort identifies six variables that she uses to trace this multi-layered self organizing process: "...number of organizations participating in disaster response; ...estimated number of interactions among participating organizations; ...shared goal of organizations, or `bias for choice' in actions; ...boundaries of the system; ...duration of interactions among organizations; [and]... types of transactions performed by organizations."71 The number of connections per organization turns out to be one of the most important defining characteristics. Depending on the number of connections, a network can be in an ordered regime, a chaotic regime, or in a phase transition between the two called "on the edge of chaos." If the network is "sparsely connected", that is each organization has only one or two connections with others, then the system tends to be orderly. But if each organization is controlled by many connections (four or five for example) with other organizations, the system tends to be chaotic. "So, `tuning' the connectivity of a network tunes whether one finds order or chaos."72
The second important factor determining whether a network is ordered or chaotic is the degree that organizations share goals or a bias to make similar choices. For example, both public and private organizations are strongly oriented toward relieving public suffering and saving lives and are willing to drop their day-to-day commitments to accomplish this end. It turns out that a strong bias to make similar choices in more densely connected networks can move the network from a chaotic regime to an ordered one.
Using a simplified version of the N-K approach, Comfort compared the disaster response systems that evolved following the 1993 Marthwada, India and 1995 Hanshin, Japan earthquakes. Her paper is published in this proceeding and will not be reviewed in detail here. Generally, Comfort found that unlike the Japanese response, the Indian response was able to quickly self organize because:
First, disaster creates a `symmetry-shattering event' that disrupts established patterns of thought and action and creates the opportunity to redesign an emergency response system that `fits' the environment more effectively. Second, the critical function of aggregating units from different levels of intergovernmental disaster response system easily into a wider system or response underscores both the difficulty of this task under linear models of organization and the interdependence of the units in a massive, large-scale disaster. This function and its capacity to mobilize resources...requires a mechanism of information exchanges to achieve a shared system-wide goal: protection of life and property. This function appears to be performed more effectively in rapidly changing disaster environments by a nonlinear, dynamic system that is able to coordinate diverse resources, materials and personnel across previously established organizational and jurisdictional boundaries through means of information exchanges guided by a clear `internal model' or goal for action and prompt feedback. Such a system uses processes of self organization in which informed participants initiate action, but adjust that action to that of others operating toward the same goal to achieve a timely, efficient response. It is essentially an organizational system operating in parallel, supported by a strong, distributed information system. Third, the goal of the disaster response system serves as an `internal model' or `mental compass' for self organizing processes. This goal allows participants from diverse perspectives, experience, and resources to adjust their actions and contributions to that of other participants in the system. "Finally, an `epistemic community'... of knowledgeable people form diverse backgrounds, experience, and organizations that focuses on the shared problem is vital to the articulation of a common goal for reduction of risk and formulation of strategies for action....Percolation theory and N-K analysis begin to address many disaster network management factors. Clearly to the degree that adequate communication connections are not available, and a common and sustained goal orientation is not developed an extended efficient disaster response network will not arise. In this case, a second type of "map" emerges of the limits of percolation; one that shows the stress and strains between organizations which may "fracture" the response structure into large less coordinated pieces.75
Computer simulations well be necessary to further validate these models. If demonstrated, it would appear that there is a morphogenic rule stating that: the emergence of large scale, geographically extended response systems with elements operating in parallel is directly related to the probability of their connectedness. When this probability passes a certain threshold, the system will emerge very rapidly across the entire area.
Steering The Disaster Response
How can we go about steering a disaster response such that the right self-organizing process are given the nudge they need, problems anticipated, and the response improved? Tracking Organizational Self Organizing Processes
By knowing and tracking critical response organizating processes called for by a disaster response plan it may be possible to influence the form that the disaster response structure takes. The first step is "process mapping" or which examines how information flows and work is done within the emergent response structure.76 A process mapping could be developed and tested during disaster exercises.
Quantification of critical elements of the response process map could be used to assess the response's evolving state. Priesmeyer and Cole suggest that "phase plane geometry" can be used to trace the level of activity for such critically related processes like the acquisition of equipment and its transport to where it is needed.77 The paper does an excellent job of explaining the author's PC program so we will not review it here.78 Generally, changes in two measures of closely related processes (volume of water vs. water trucks to ship it in) are plotted against each other. A graph of the "evolving state of the system" using four quadrants is created. This is a very useful display because:79
Rather than having to evaluate a series of one-dimensional variables, the phase plane image focuses attention on relative changes which might otherwise escape notice. It graphically depicts the changes in the two measures exposing subtle transitions in the data which are masked by the sheer size of the actual measures. Most often there is obvious structure and pattern to the changes and that structure is dramatically displayed in the trajectories of interactive changes as they are plotted.By noting which quadrant the data are moving in or to, the manager can decide whether one or the other resource should be increased, if increases in both resources are needed, or if less of each is required. The evolving event is thereby presented as a trajectory traced through the quadrants over time. Priesmeyer and Cole also provide a technique for displaying and analyzing changes in several inter-related processes over time.80 This might be helpful for determining why a response structure is taking the form that it is. Effective implementation of the system requires that all relevant information be provided in real time and sent to a central location where it is processed and displayed or distributed to groups addressing specific needs. Emergency dispatch centers, supply dumps, personnel staging areas, hospitals, search and rescue groups, etc., could provide critical process activity/need data. Forecasting Response Bifurcation Points And The Emergence Of Large Scale Disaster Response Systems
We have shown that we cannot predict what the disaster response structure will look like no matter how much information we collect. One way to address this limitation is to use what Cartwright calls an "ensemble of forecasts". Numerous simulations are run to determine which response processes are particularly sensitive to initial conditions. These conditions are then varied to determine the range of their affect on emergent structures. According to Cartwright:
If the best we can do is make approximate predictions, then we should be trying to make `parallel' predictions of similar or `surrounding' events. ...What is required is a kind of sensitivity analysis applied not so much to the parameters of the model as to its initial state. ..We are all accustomed to testing our models with different assumptions about future conditions, in order to see how this affects the results. What we do not so often do is to run models from different starting points.81
It may be possible to identify a particular set of conditions that lead to particular range of structures. Such ensemble forecasts should be kept simple and understandable but useful.82 If these conditions can be defined, a simulation could be run immediately following a disaster and compared to earlier results as a way to stimulate organizational response planning options.
The orderliness of the progression along the logistic map, and the percolation threshold means that actions can be taken to mediate disaster consequences. For example, it turns out that the ratio of the length of two succeeding bifurcation branches is a universal constant that is applicable to all systems that exhibit this behavior. "One possible and very useful interpretation of the universality of [this ratio] would be by using it for predictions. For example, by just measuring two successive bifurcations we would be able to predict the bifurcations thereafter and also predict where the threshold [to chaos] would be."83 This is an important point, since it may be possible to reduce the level of disorder being experienced by changing the communications structure or its content, or by increasing the availability of resources thereby keeping it at the edge of chaos.
Chaotic Systems Management Theory
Management techniques appropriate for organizations prior to a bifurcation point do not work well once an organization reaches this point or moves to the edge of chaos. Prior to this point the variations occurring in the environment fall within the organization's change capabilities. The management task at the bifurcation point is to dampen the disrupting structural oscillations with its accompanying social time. The challenge at the edge of chaos is how to creatively interpret the options and choose among a multitude of possibilities that will, via a second order phase transition, effectively recouple the organization to other organizations and its environment. Kiel tells us that:84
"Most importantly, during times of high instability such as disasters and occasions when emergency services reach peak levels of activity it is essential to recognize that stability can only be regained by developing strategies that are themselves unstable. In short, we must match the instability of these environments with management practices and organizational strategies that are dynamic and fluid."According to Kiel, there are three ways to control chaos85:
...[A]s with variation beyond the control limits in quality measurement systems, that variation should not be considered a problem in management systems but rather an opportunity to learn why the variation occurred. It is the peaks and valleys in quality measurement data that may provide the best source to improve administrative systems. Managers must learn to ask why output, problems, or performance peaked at one point and then reached a valley at another.In this case, the disaster response manager is looking for those variations driving the self-organizing process--the fluctuations--in a direction that appears to meet his/her immediate goals. Such a fluctuation can be either positive--something is being built--or negative, there is a silent area that has not reported. This phase transition or evolution of a response organization or extended response structure to a more adaptive one is a learning process. Good information about variations in the environment and the capacity to learn and visualize based on that information are key manager attributes. These skills include the capacity to "see" beyond the immediate present and construct a longer term future horizon that may serve to reduce resource waste through continuous short term adjustments. This requires an awareness of organizational social time frames and how they fit into the interactive social time frames of other organizations. Such skills are necessary to build in variation and to construct and adjust work rules relative to the field of action for optimal performance under changing environmental conditions.90
Kiel suggests that "we practice variation by perhaps using diverse teams to try diverse methods on essentially the same disaster or emergency problem."91 Relatively autonomous "messy" or multi-discipline work teams in the field are able to identify and use relatively large amounts of data to do problem solving and create individual or extended response structures that respond to the immediate needs of their clients be they victims or other response organizations. In this case they are creating the local response fluctuations that overall EOC management is looking for. Teams should be "messy" or unstable in the sense that their membership is drawn from across functional areas constituted to solve a service delivery problem. "This suggests less of a focus on traditional structuring by functional area and instead consideration of where functional units converge to create outputs and services."92 Teams drawn from a single functional area (medical but not transportation for example) may tend to too narrowly define the issue and have an overly rigid view on how to address it.93
The new members of unstable teams appear to serve as `devil's advocates' that promote alternative decisions and thus divergent outcomes. This further suggests that unstable teams represent a more readily adaptive response to changing situations. ...The value of instability, then, in work teams is that these `messy' teams serve the role of creating emerging structures consistent with the nonlinear notion of process structures. The team structure when thus viewed as a shifting and dynamic structure of human interaction generates an increased number of decision inputs and thus the likelihood of expanded alternatives and solutions.Sensitivity to initial conditions and the inability to predict exactly what form an organization will take at the edge of chaos suggests that it is impossible to predict which pattern for organizing the response is best. Provocative research cited by Loye finds that groups do a better than average job of predicting future events.94 The research suggests that groups are able to create a chaos "gestalt" that is able to predict a likely outcome. Messy groups, particularly since they are composed of individuals drawn from each element of a problem, seem particularly well suited for developing and implementing options beyond the edge of chaos. 95
The creation of relatively autonomous, "messy" groups to solve problems in the field suggests a very flat, decentralized disaster management structure. A multi-layered, hierarchical structure will tend to restrict information flow at each point as it climbs upward, concentrate and restrict decision making away from the field, and reduce innovation and flexibility. A flat structure allows for the fluid and rapid flow of information, particularly if multiple information linkages are possible such as was the case in Mahashastra, India.96 Experiments by Hershey and colleges, demonstrate that a flat organization tends to produce the least disorder in information flow resulting in higher efficiencies than hierarchical organizations.97
By providing unique solutions to local problems across the disaster area, it may be possible to minimize the effect of the idiosyncratic collapse of local social time into the present and other logistic map related social time divergence. Local, "messy" groups, if supported, would feel a sense of involvement in resolving their problems rather than being caught up in presentism. Better entrainment as a parallel process with the overall response might be possible. A flat management organization and highly networked communications system could reduce the effects of differing time signatures, and varying locations on the logistic map. It is the connectedness among the parts of the system, not their hierarchical management, that should allow an improved overall response, particularly if groups are able to share risks. According to Comfort:98
"...discovering weaknesses in one part of the system enables other parts to respond in ways that either reinforce the weak areas or adjust their performance to dissipate the weakness throughout the larger system. The overall performance of the system improves through the interaction of its parts, even though individual components remain weak."These suggestions appear consistent with the four factors that increase the resilience and adaptiveness of the complex system that extends across the disaster:99
"They are [: 1.] a capacity for creative innovation among organizational units that interact as a system to achieve a common goal; [2.] flexibility in relationships between the parts of a system and the whole; [3.]interactive exchange between the system and its environment; and [4.] a crucial role for information in increasing either order or chaos, regularity or random behavior within the system."
Key Lessons For Disaster Managers
Several key management lessons for public disaster response managers emerge from the conference papers and following day's discussion:
Limitations Of Chaos Theory For Disaster Management
The application of chaos theory to disaster management has a number of significant limitations:
While not necessarily recommendations of the author, the California Research Bureau or the Emergency Medical Services Authority, the following are potential options for action. The options are meant to serve as a basis for dialogue.
Research And Evaluation
Communications And Steering
The California Legislature has attempted to deal with the disruptive effects of disasters on response organizations. EMS, and other state and local government response agencies are required by statute (Section 8607 of the Government Code) to use the Standardized Emergency Management System (SEMS) , when responding to emergencies involving multiple jurisdictions or multiple agencies. Local governments must use SEMS to be eligible for state reimbursement of response related personnel costs. This legislation was passed to address interagency coordination and other response management problems occurring during the 1991 East Bay Hills Fire in Oakland. Generally, law enforcement, fire, and other response organizations had problems organizing themselves in a compatible way, making it difficult to identify or coordinate similar functions and resources. These problems were exacerbated by effects of the disaster itself.
SEMS seeks to address interagency coordination problems by providing a five level hierarchical emergency response organization (field, local government, Operational Area,115 region, and state) that facilitates:116
The papers presented at the conference did not use chaos theory to examine California's disaster response plans, ICS, SEMS, emergency communications systems, training, or other elements of the planned response or of past responses. However, a number of state related management options could be evaluated to determine their response utility for ICS and SEMS using the suggested simulation or during large scale exercises that involve multiple departments, different layers of government, and a significant field component.
Next Chapter: ACKNOWLEDGEMENTS - DISASTER IN AISLE 13 REVISITED
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