Decision Making / 4 / 4.9 / 4.9.4

4.9.4 Tame Vs. Wicked Problems—Finality

Tame problems have closure—a clear solution and ending point. The end can be determined by means of a test. There is no stopping rule for wicked problems. Like a Faustian bargain, they require eternal vigilance. There is always room for improvement. Moreover, since there is neither an immediate or ultimate test for the solution to the problem, one never knows when one’s work is done. As a result, the potential consequences of the problem are played out indefinitely.

Chapter 2 demonstrated that preconditions for the Black Hawk crash developed in the early 1990s or perhaps before that time. Parliament was sufficiently concerned about serviceability of aircraft in the mid-1990s that the Chief of the Defence Force (CDF) was asked what he was doing about it. Despite some corrective action by the CDF, the problems continued largely unabated. A number of forces militated against corrective action being effective. These included the existence of varying but generally long lead-times for acquisition of critical spares. These spares had to be sourced from the United States where Australia remained low on the list of priorities for resupply of spares. Aircraft availability remained unacceptably low for many years.

Systemic delays, of variable and often unknown duration, can make the creation of effective strategies difficult, particularly when there are consequential ‘knock-on’ effects. The morale of pilots declined when training was affected by lack of serviceable aircraft. Strategies, including payment of flying bonuses did little to ensure retention of pilots.

There is no clearly defined end point when seeking a solution to a problem:

‘… it is natural that a … model should go through multiple rounds of revision and evaluation … the iterative process may, in theory, continue as long as the model fails to satisfy some evaluative criterion (Randers, 1980). However, there is always some further refinement that may be made … opportunities for model improvement are not always apparent or obvious and … scientific modeling is not about minimizing the need for model revision … but rather about recognizing model shortcomings and following through with solid improvements (Homer, 1996: 3).’

Modelling, including qualitative modelling, and scenario planning are important in building understanding and learning about what causes the behaviour of complex, systemic problems. Understanding is an essential precursor to strategy development and the process of seeking a solution can involve repeated evaluation of models against observed behaviour, review of strategies, and adjustment (Coyle, 1977; Eden and Ackerman, 1998a; Morecroft and Sterman, 1994; Richardson and Pugh, 1981; Sterman, 2000, and Vennix, 1996).

‘… models are always in a continuous state of evolution … we should stress the process of modeling as a companion to, and tool for, the improvement of judgement and human decision making (Forrester, 1985: 134.)’

Understanding and learning through modelling should enable development of effective strategies for addressing wicked problems. This should limit potential consequences of the problem that might otherwise be played out indefinitely.