An Action-Oriented Taxonomy of Errors

In situating examination of errors within organisational psychology, a cluster of studies authored by researchers in Germany likewise adopted a conceptualisation of action that situates the concept of intention in terms of goals (Zapf, Maier, Rappensperger, & Irmer, 1994). Like Reason, Frese and Zapf acknowledge that in general, goals are preceded by needs, by “wishes” and “wants” (1994, p. 274), that translate into intentions that can guide action when an urgency or importance arises. However, Zapf and Frese mark a difference between personal actions and those taken at work.

Actions at work are linked to tasks, actions that must be performed according to rules in order to help meet organisational goals. In order to perform an organisational or external task, a worker must redefine it into internal tasks, and then to goals that can be met through action. The process of redefinition is described as one of interpretation, conducted based on professional and organisational knowledge, and prior experience.

The interplay between work tasks and personal goals influences aspects of the models of regulation and error. Hofmann and Frese present a recent synthesis of the German studies (2011), describing a four-level taxonomy of performance. Three of the levels correspond to those of the SRK, and by extension to slips of action.

Skill-level or sensori-motor activities, as in the descriptions given by Norman and

by Rasmussen, are those which are performed automatically, and which are monitored and adjusted based on feedback from the environment.

Flexible action patterns are likened by Hofmann and Frese to schemata within

Norman’s action theory and rules in Rasmussen’s SRK framework. The interpreta- tion given to flexible action patterns in the German sense signifies a “ready-made” action sequence, that can be flexibly applied to meet organisational rules. It applies to situations in which a work task may require a set of established tasks that are routine, but not automatic. In this case, the rules are organisationally conceived and

followed, as in a set of documented procedures or checklists for performing maintenance tasks.

Conscious or intellectually regulated performance involves active reasoning.

Goals must be considered, actions and sub-actions defined. It is undertaken in novel, unfamiliar situations. Action is conscious and effortful.

The fourth level is described as meta-cognitive, describing how individuals formulate and undertake tasks to meet goals. This is a heuristic level of control that overarches action at all levels of conscious regulation. Heuristics guide how reasoning is performed: what kinds of plans are developed, which information search strategies are used, and how feedback from the environment is used. Heuristics are individual, and the Germans write that an individual may show a particular preference for a reasoning style, for example, always relying on their “gut” or by conducting a detailed search for information before taking action.

The interpretation of flexible action patterns is based on a narrow reading of both concepts. Schemata as used by Norman is only intended to represent how well-learned sensory or motor actions are stored in memory. He does not use this cognitive structure to explain how patterns of higher-level reasoning are cognitively managed.

Rasmussen’s description from 1985 suggests that an individual may apply a “recipe” or a procedure to a situation, but the recipe has been developed through personal experience. The suggestion is given that the rule may be cultural, know-how that is provided to a person by a colleague, but it is not something that has been codified into a set of mandated procedures. It is not a rule that is followed, but rather one that is applied as in a “rule of thumb”. The process of selecting the rule is described in terms of matching information from the state of the environment to memories of analogous situations.

The German researchers include several variations of an error taxonomy in their studies. The kinds of errors are correlated to the levels of regulation. In the most developed version of the taxonomy, movement errors accompany sensori-motor actions, while errors of habit,

variants at the conscious or intellectually regulated level of performance (Frese & Zapf, 1994; Hofmann & Frese, 2011).

Goal setting errors and thought errors relate to goal formation and execution.

Goals may not be adequately developed or improperly decomposed into smaller goals. As noted by others (Sellen, 1994), the criteria for setting or assessing achievement may be vaguely specified. Thought errors occur when actions are “blinkered” and side effects and effects of time are not considered when plans are carried out.

Mapping errors relate to the collection, synthesis and actions taken upon informa-

tion that is used in the course of action, while prognosis errors relate to the inability to adequately predict future system states.

Memory errors occur when a plan or part of a plan is forgotten in the midst of

action.

Errors of judgement occur when a person does not understand or interpret informa- tion that is presented in the course of action.

2.3 Summary

Dependability is an old, multivalent concern in software engineering. A dependable service can be trusted, but the trust must be justifiable. It must avoid failures that are more frequent and more severe than are acceptable to the user. Dependability is also assessed in terms of correctness, an attribute that is gauged in relation to service and specification (Avižienis, Laprie, Randell & Jacquart, 2004). Correctness may be proven, but a system does not need to be correct to be dependable. It may also exhibit fitness, an emergent, dynamic quality that develops in response to the needs of the environment and culture in which it is created.

Root-cause analysis studies improve software dependability by looking for the sources of faults in software. These studies use a simplified definition of error in order to produce measurable improvement. The simplification has limitations; it is difficult to adequately

explain why some errors occur, or to account for qualitative factors such as the effects of time and of human judgement.

At their simplest, actions can be performed automatically, with little or no attention paid to them. Actions that are well-learned or frequently performed form patterns that are stored in memory and can be re-used in the future. Actions that are simple or become routine may be performed with only periodic attentional checks. These checks ensure that intentions are being met by the actions that are being performed.

More complex intentions require that several actions unfold simultaneously and may require planning, analysis or decision making. By their nature, they require that conscious attention be paid to the tasks at hand. Such actions may also be novel, ill-learned, and the nature of the intention may preclude full understanding beforehand of outcomes. The acts taken to meet complex intentions are performed consciously, by paying “close and labored” attention (Reason, 1984, p. 516).

Error is a “generic term” encompassing occasions when planned sequences of mental or physical activities fail to achieve intended outcomes. Errors do not arise by chance, people commit them (Reason, 1990, p. 9). They may manifest at low levels, as in physical actions, or at higher levels, as in mistakes made in problem-solving (Norman, 1981; Reason, 1990). Error detection and recovery are more difficult in high-level problem-solving than in motor or skill-based activities because the process is subjective, it relies on goals that have been set for an undetermined future (Reason, 1990).

Error occurrences are often ephemeral, they are imperfectly represented in the world after recovery. This type of error is experienced, and must be managed using intrinsic and extrinsic sources of information. Conditions are likely novel, new or new again. As a consequence, the experience of managing an error is immediate and immersive, pulling

Errors are sometimes “caught” in the act, but they may also be recognised after a delay in time.

In everyday error, the human is engaged in an action when something goes wrong, spurring an error handling process. In software development research, error handling is often described as being part of a managed process, triggered by a separate outcome-based detection and reporting process. Empirical studies of software engineering that examine aspects of bug fixing or maintenance, for example, generally describe the process as one of developers beginning from a reported outcome of faulty behaviour, working to establish a root cause for the error, and then determining how best to fix it (Ko & Myers, 2005).

The next chapter argues that human errors are a natural consequence of performance on the job (Rasmussen, 1990). They should be examined in terms of actions rather than of causes.

Front-line operators, managers and designers commit errors. Sometimes these errors result in critical failure. Moving from forming these conclusions to making suggestions for improvement is difficult (Rasmussen, Nixon, & Warner, 1990). The analysis, performed retrospectively, depends upon causal explanation and a correspondingly narrow definition of human error.

Causal analyses must establish a chain of significant events “upstream” from a negative outcome. The establishment of events depends on a subjective determination of stop-rules, pragmatically defined by analysts to determine how far back in time analysis must go. Conditions will therefore be explained by "abnormal, but familiar" events and acts, and causes will tend to reflect concerns relevant to a discipline at the time the analysis is made. Causal analysis assumes that the sequence in which an error is analysed can be “taken for granted” (Rasmussen, 1990, p. 1186).