Managing Multiple and Conflicting Goals in Dynamic and Complex Situations: Exploring the Practical Field of Maritime Pilots

* Corresponding author. Safety researcher, Dutch Railways, Laan van Puntenburg 100, 3511 ER Utrecht, The Netherlands. Email: [email protected], Tel. +31886712995, Fax.+31886712381. 1 Associate Professor, Pontifical Catholic University, Av. Ipiranga, 6681, Building 10/106, 90619-000 Porto Alegre, Brazil. Email: [email protected], Tel. +555133023542. 2 Professor, Griffith University, 176 Messines Ridge Road, 4122 QLD Mt Gravatt, Australia. Email: [email protected], Tel. (07) 37355761. JOURNAL OF MARITIME RESEARCH ISSN: 1697-4040, www.jmr.unican.es Vol. IX. No. 2 (2012), pp. 13 18 laxed more often so there is more time for contemplating consequences of the decision in terms of safety). Hollnagel (2009b) investigated trade-off decisions in more depth – especially with regards to decision making -, in his book ‘The ETTO Principle: Efficiency – Thoroughness Tradeoff ’. Hollnagel defined the ETTO principle as: In their daily activities, at work or at leisure, people routinely make a choice between being effective and thorough, since it rarely is possible to be both at the same time. If demands for productivity or performance are high, thoroughness is reduced until the productivity goals are met. If demands for safety are high, efficiency is reduced until the safety goals are met (p. 15). The ETTO-principle suggests a binary approach of efficiency (productivity) and thoroughness (safety). It proposes that efficiency and thoroughness rarely can be reached at the same time. In a complex world all kinds of opposing goals exist, driven by all kinds of pressures and reducing this to efficiency and thoroughness has its limitations. Besides that, relaxing productivity (which means being less efficient) in order to be thorough, can introduce new (probably unknown) risks. 1.2. Trade-off decisions, complexity and coupling Many trade-off decisions, and often the more critical operational (sharp end) ones, must be made in complex and tightly coupled settings (Perrow, 1984), under conditions of uncertainty (Orasanu, 2001). Complexity, as understood here, means a lack of transparency and predictability in how parts in a system interact and can produce novel system behaviors. Sequences of events, in complex situations, are unfamiliar, unplanned or unexpected, and either not visible or not immediately comprehensible. Tight coupling exacerbates operational difficulties. It means that, because system parts and events are closely interconnected, sequences of interactions can spread and escalate rapidly and that possibilities for meaningful intervention degrade, and margins for recovery shrink (Perrow, 1984). In tightly coupled situations, delays in taking action may not be possible, things have to be done in an invariant order, there is only one method to achieve a goal, and there is no opportunity to recruit additional expertise other than that which is already in the operation at that moment (Hoven, 2001). Operational settings are not complex or tightly coupled in a fixed sense, of course (Snook, 2000). Complexity can increase, and couplings between different parts of the operation can tighten with changes in context (weather, equipment functioning, available expertise, procedural learning and adaptation, etc.). Coupling and complexity thus wax and wane during an operational workday (Rosness, Guttormsen, Steiro, Tinmannsvik, & Herrera, 2004), changing not only the sheer number of trade-off decisions, but exerting different pressures, criticalities and uncertainties on the trade-off decisions that operators need to make. The dynamics of different operational states (simple to complex, loosely to tightly coupled) in which a system can function at different times, demands operational adaption but also preparation (Hollnagel, Nemeth, & Dekker, 2008, 2009), as uncertainty can increase and cognitive resources for decision making diminish (Orasanu & Connolly, 1993).