Learning About Ambiguity

Journal of Contingencies and Crisis Management Volume 23 Number 2 June 2015 Learning About Ambiguity Robert Bea University of California, 212 McLaughlin Hall, Berkeley 94720, CA, USA. E-mail: bea@ce.berkeley.edu This paper proposes a classification system for definition, analysis and management of the primary ambiguities influencing the performance of engineered systems. One cat- egory of ambiguities (Intrinsic) is addressed with ‘hardware and structure’ approach that is intended to develop and maintain ‘robust’ damage and defect-tolerant systems. The other category of ambiguities (Extrinsic) is addressed with ‘human and organizational’ approach intended to develop and maintain high reliability organizations having high reliability management with high reliability systems. Proactive (performed before activi- ties are conducted), Reactive (performed after activities are conducted) and Interactive (performed while activities are conducted) risk management approaches and strategies are described to help develop and maintain systems having desirable performance char- acteristics, including acceptable ‘safety’. Results from a study of seven organizations that worked for more than 10 years to implement these approaches and strategies to assess and manage ambiguities are summarized. 1. Introduction A s a young engineer, I did not receive training in how to understand, evaluate and manage different types of ambiguities; to understand and successfully cope with the uncertainties influencing how different types of systems were engineered, constructed, operated and maintained. Frequently, factors-of-safety (FoS; ratio of capacity to demand) appeared magically in the engineer- ing processes. Safety of the systems engineers designed was discussed; it was emphasized that engineers should hold public safety as a priority, but there was no instruc- tion in how to determine if a system was safe or not safe. In many cases, it was assumed that something was safe if it was designed according to some generally accepted engineering code or guideline. 2. Types of uncertainties I have learned that there are different types of ambigui- ties – things that are doubtful or uncertain. These different types of ambiguities must be assessed and managed in different ways. There is not a ‘one size fits all’ approach to either characterize or manage uncertainties. To provide organization and structure for classifica- tion, description and analyses of the different types of © 2015 John Wiley & Sons Ltd ambiguities, they have been organized here into two fundamental categories (Table 1): (1) Intrinsic – belong- ing to the essential nature, and (2) Extrinsic – what comes from outside of something. There are two types of Intrinsic uncertainties:Type 1 – natural, inherent, information (data) insensitive, and Type 2 – analytical modelling (qualitative and quantita- tive), parametric, state, information sensitive. Knowl- edge and data can be used effectively to reduce Type 2 uncertainties. Other means like FoS can be used to cope with Type 1 uncertainties. There are two types of Extrinsic uncertainties:Type 3 – human and organizational task performance, and Type 4 – human and organizational information development and utilization. Results from Extrinsic uncertainties fre- quently are identified as ‘human errors’. Experience has amply demonstrated that such errors are results from human and organizational processes and are not the ‘root causes’ of accidents and failures (Dekker, 2006; Reason, 1990; Woods, 1990). Human errors are results, not causes. Type 4 uncertainties have been divided into two subcategories: (1) Unknown Knowables – ‘Predictable Surprises’ (Bazerman & Watkins, 2004) or ‘Black Swans’ (Taleb, 2007), and (2) Unknown Unknowables (Bea, 2002) – not predictable or knowable before something is done. In the case of Unknown Knowables, DOI: 10.1111/1468-5973.12085