Lawless et al. - Organizational Uncertainty And Planning Tradeoffs

The Structure of Concern Project compares many theoretical models from many disciplines to the Adizes PAEI model, arguing that they must all be reflecting the same underlying phenomenon. One concern structure model is described below.

According to Lawless et al. (Lawless, 2005; Lawless & Grayson, 2004a; Lawless & Grayson 2004b; Lawless et al., 2000a; Lawless et al. 2000b), there are two contrasting models of uncertainty in organizational theory. One derives from game theory and embraces methodological individualism. On this view, organizations are equal to the sum of contributions from the individuals who comprise them. Since the basic unit of analysis is the individual, the way to decrease uncertainty in organizations is to increase communication and coordination between its members.

Lawless et al. also describe a second model of organizational uncertainty, presenting it as a derivative of mathematical physics. On this view, the organization itself can be uncertain, independently of the individuals in it. That is, individuals in an organization might profess complete certainty, but the organization as a whole might be in an extremely uncertain position. Only perturbations of this system expose information about its actual state and the veridicalilty/reliability of its explicit and tacit knowledge.

Cooperation cannot be the solution to this kind of uncertainty. It is actually the problem. When cooperation is easy and routines are undisrupted, minor perturbations can be filtered out of the organization. Internal relationships mutually reinforce each other. The organization can thus drift towards a more uncertain state without realizing it. Information that they are “off course” disappears when cooperation is smooth and easy, buffered from major external disruptions or perturbations. Organizations become insulated by their own prior successes. Lawless writes:

Lawless relates this to the military tactic of "intelligence strikes", forays against the enemy designed specifically to disrupt them in various ways to see how they respond, in order to gain an understanding of the organization of their defence. He also relates it to basic contingency forecasting, where considering problems and conflicts can expose organizational information. His domain of application is defensive military operations, although the same framework is applied to offensive and commercial uncertainty in other papers (Lawless et al., 2000a; Lawless et al., 2000b; Lawless & Grayson, 2004a; Lawless & Grayson, 2004b). In this context, he introduces two paired sources of uncertainty that together make up a fairly significant concern structure model.

Starting from the observations that planning occurs under time pressure and uncertainty, Lawless introduces the Energy/Time uncertainty pairing. Where one is uncertain, we want to be certain about the other. Lawless also posits a Knowledge/Implementation uncertainty pair. We can be uncertain about the adequacy of our plan and the information we are basing it on (Knowledge uncertainty), and we can also be uncertain about our capacity to martial and direct adequate forces in the required manner to actualize those plans (Implementation uncertainty). Again, the less certain we are of one of these factors, the more certain we want to be about the other.
Each of these four types of uncertainty grows in its own distinctive way when systems are left unperturbed. Each one also takes a different kind of perturbation to release it.

P - Execution Uncertainty: When this type of organizational uncertainty grows as a result of effective cooperation, organizational information about effective capacities will only be exposed through conflicts and problems during the execution of plans.

A - Energy Uncertainty: Organizational uncertainty about the accumulation, storage, distribution and burn rate of key or limiting resources can increase under conditions of routine operations. That uncertainty can only be resolved through actual burn rates during the planned operations.

E - Knowledge Uncertainty: Organizational uncertainty can develop regarding the completeness of strategic information and the reliability of intelligence sources. This uncertainty can only be reduced during forays into the field.

I - Time Uncertainty: There may be organizational uncertainty about time dependencies (i.e. who will be where when, and whether that will happen in time to let something else happen, and what everybody else has to do to make that happen, whether all of the parts can come together within critical timeframes or not). This uncertainty can only be reduced by putting the team to the test of an actual performance or exercise.

For the Knowledge/Execution uncertainties, the more time and effort you spend perfecting your knowledge, the smaller your window of opportunity gets for accomplishing urgent goals in the field. The converse of this is "look before you leap". Rushing to implementation too soon with inadequate knowledge will result in extremely costly lessons, exposing the organization's planning and intelligence deficiencies. Around Time/Energy uncertainties, with unlimited energy, the time needed to reach a goal can be lessened dramatically. Conversely, protecting energy stores and restrictively limiting distribution can stretch out the duration of operations, increasing the coordination load and the complexity of distribution activities. There is an effectiveness/efficiency trade-off where effectiveness consumes energy ahead of time and efficiency consumes time ahead of energy.

1. Lawless, W. F. (2005). “Organizations, perturbations, and generating information.” 10th International Command and Control Research and Technology Symposium - The Future of C2. McLean, VA, Department of Defense Command and Control Research Program.
2. Lawless, W. F., Castelao, T., & Abubucker, C. P. (2000a). “Conflict as a heuristic in the development of an interaction mechanics.” In C. Tessier, L. Chaudron, & H. J. Muller (Editors), Conflicting agents: Conflict management in multi-agent systems (pp. 279-302). Boston: Kluwer.
3. Lawless, W. F., Castelao, T., & Ballas, J. A. (2000b). “Virtual knowledge: Bistable reality and the solution of ill-defined problems.” IEEE Systems, Man and Cybernetics, 30(1), 119-126.
4. Lawless, W. F., & Grayson, J. M. (2004a). “A conjugate model of organizations, autonomy, and control.” AAAI Technical Report SS-04-03. Stanford University.
5. Lawless, W. F., & Grayson, J. M. (2004b). “A quantum perturbation model (QPM) of knowledge and organizational mergers.” In L. Van Elst, & V. Dignum (Editors), Agent Mediated Knowledge Management (pp. 143-161). Berlin: Springer.
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