Hammond (1996) argues that there are two fundamental distinctions when theorising about decision making: that between cognitive and analytic rationality and that between coherence and correspondence theories of truth. Hammond defines analytic thought as “a step-by-step, conscious, logically defensible process” (p.60) whereas intuition is a process that produces an answer without going through the step-by-step logic of analysis but by utilising experiential and tacit knowledge, imagination and metaphorical thinking – forms of cognition that may be difficult or impossible to verbalise.
Coherence theories are primarily concerned with the logical process of proceeding from a particular premise. The key criterion is whether or not the process of thinking is consistent and logical. Correspondence theories are more concerned with empirical accuracy: whether the judgement fits the facts as they are known.
Hammond suggests that analytic and coherence modes of thinking are more likely to be used by the producers of knowledge who are concerned with creating logically consistent theories whereas intuition and correspondence are more relevant to the users and applicators of knowledge who must make decisions in complex real-world situations. These modes of cognition, he argues, are often seen as opposites but in reality they exist at the extreme ends of a cognitive continuum and humans move between the two depending on circumstances and the task in hand.
In analytical decision theory or decision analysis (Munro, 2008; O'Sullivan, 2011; Taylor, 2012) all possible options in a situation will be considered usually by constructing a decision tree (Munro, 2008, p.106; O’Sullivan, 2011, p.142; Thompson & Dowding, 2009, p.177). As Munro’s example shows these trees can be extremely complex and present the decision-
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maker with an enormous range of choices that take a long time to go through. Even then, it may not be possible to identify every option. Options are assigned utility values in which the likelihood and the desirability of each are numerically weighted (O’Sullivan, 2011). Many decisions will require subjective values, such as stakeholders’ wishes, to be assigned a value. Thompson & Dowding (2009), writing about nursing, suggest that patients can be asked to rate the outcomes desirable to them but this may be more difficult in social work where possible outcomes may be much more contested and the variables ambiguous (White & Stancombe, 2003) and there is evidence that different professionals evaluate cases and possible outcomes very differently (Taylor & Donnelly, 2006). In child abuse work many decisions, as we have seen, are based on moral reasoning. Even if outcomes appear relatively straightforward the assigning of utility values has an intuitive element to it and in decisions in health and social care there will be a degree of uncertainty which is not calculable (Thompson & Dowding, 2009). The strength of a decision tree is that it is a way of setting out all the options in a systematic way that can help break down complex decisions into smaller steps (O’Sullivan, 2011) but it can never be a purely logical, mathematical process: human judgement, intuition and emotion play a role (Munro, 2008). Decision trees are poor at accounting for complexity, context and unpredictability (White & Stancombe, 2003; Thompson & Dowding, 2009). Atkinson (1995) argues that such orderly models are based on single decisions made single-handedly whereas in reality a series of decisions may be made, separated in time and place, and will be made by different actors interacting with each other in different ways. In social work decisions are often dependent on the knowledge and actions of other professionals. Decisions are rarely couched in the language of objective neutrality: cases have to be “formulated” and “sold” to managers (White, 2003) according to an agency- preferred “tacit hierarchy of credible accounts” (White, 2003, p.181). Atkinson calls this an “ecology of knowledge” (1995, p.54): who you are in an organisation influences the knowledge you have, the knowledge you share and how that knowledge is treated. Decisions then may be enmeshed in social processes in a way that cannot be represented by classical decision analysis.
Because intuition does not follow a logical step-by-step process does not mean it is a mystery: it is based on a rationality, a set of heuristic devices, that can be articulated (Munro, 2008). Intuition is both a way of thinking and a type of knowledge (Thompson & Dowding, 2009): intuition tends to be heavily based on tacit, experiential knowledge or what in terms of professional decision making is called practice wisdom (O’Sullivan, 2005). As a way of
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thinking it is characterised by “fast and frugal” reasoning (Gigerenzer & Goldstein, 1996). Instead of working sequentially through all the options as in a decision tree this involves drawing inferences from a small number of options and making a decision quickly, based on an unconscious processing of data. O’Sullivan defines it as “decisions without deliberation (involving)... the rapid identification of relevant cues and the making of connections and associations...it involves sensing rather than deliberative thinking” (O’Sullivan, 2011, p.90). Even critics of this kind of reasoning accept that in many situations this produces decisions that are as successful as reasoning in a more deliberative way and because it happens much more quickly it is better suited to real-world situations (Tversky & Kahneman, 1974; Gigerenzer & Goldstein, 1996; Thompson & Dowding, 2009). However, it is recognised that such thinking, simplifying problems as it does for the sake of speed, involves a number of biases irrespective of the decision-maker’s expertise. Tversky & Kahnemann (1974) suggest the most common are: representativeness bias (thinking that an outcome is caused by a factor that seems related to the outcome but is in fact un-related so alternative causal factors are overlooked), availability bias (estimating the likelihood of an outcome based on outcomes we are aware of or which can be brought vividly to mind whereas factors that we are less familiar with or are less vivid are overlooked: in other words we think something is risky because of hazards we can easily imagine so we overlook factors that may be more likely to occur but which we can’t imagine) and adjustment or anchoring bias (we predict an outcome based on what our experience tells us is the most likely outcome. The cause-and-effect we predict tends to be simple and linear so more complex, unfamiliar patterns of cause-and-effect are overlooked). These biases (and there are many others: Taylor, 2013, p.70; Thompson & Dowding, 2009, ch.7; Gambrill, 2005) suggest that in a search for heuristic short cuts to quick decisions we pick out the familiar, the vivid, the “obvious” and overlook the unfamiliar, the complex, the less predictable. A lot of the time “these heuristics are highly economical and usually effective” but they give rise to “systematic and predictable errors” (Kahneman, 2011, p.431 both quotes). In child abuse work, where children may be at risk because of complex interactions of factors which are presented in the form of ambiguous and uncertain information, the possibility of making mistakes is significant. Yet such heuristics are essential: we have to make decisions quickly and avoid the risk of simply being overwhelmed by more information and complexity than we can process manageably. The dilemma is that:
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The very mechanisms that enable us to learn and to take complex decisions are the same mechanisms by which we may be open to bias (Taylor, 2013, p.71)
Intuitive and analytical thinking both have their strengths and weaknesses and rather than seeking some “perfect” form of rationality it is important to be aware of how errors will occur and how different ways of thinking can complement each other in order to minimise mistakes. More analytic models are useful for telling us how things “ought” to be and for systematically setting out the known options (Taylor, 2012; Munro, 2008; O’Sullivan, 2011) but they do not represent the ways in which professionals actually think and make decisions in practice. Neither do they account for uncertainty and it is the irreducible uncertainty of the world that forms the context for decision-making. Thompson & Dowding (2009) argue that the world is “probabilistic” (p.121) – it cannot be known completely or with certainty. For Hammond (1996) the world is full of multiple fallible indicators – cues whose meanings are uncertain and need to be evaluated alongside other, equally fallible, cues to arrive at a best possible understanding but one which will not be perfect. Taylor (2012) argues that compared to areas such as medicine and psychology there is a lack of research into social work decision-making and there should be a much more conscious understanding of the models of decision-making practitioners use so that the limitations of each can be made explicit. A number of authors (Schwalbe, 2004; Thompson & Dowding, 2009; van de Luitgaarden, 2009; Taylor, 2013) have suggested that Klein’s Recognition Primed Decision Making and Brunswik’s “Lens” theory are especially useful models of more naturalistic real-world decision making.
Klein (Klein & Klinger, 1991; Klein, 1993; 1999) argues that intuitive or naturalistic decision- making is best suited to complex and rapidly changing situations where information is incomplete and fallible but decisions have to be made quickly. He suggests that in such situations people opt for a good-enough solution based not on a logical examination of every option but on the creation of a coherent story or mental representation of the situation based on prior experience that tells them what the typical response to this kind of situation is. This may be amended to another typical response if the first choice does not work. Conscious deliberation is minimised and this allows the decision maker more flexible and rapid responses. Researching how fire fighters make decisions Klein (1999) argues that mental representations and metaphors create a link with experience and make that experience available for decision making in situations of uncertainty. However, as Munro (2008) suggests, professionals who lack experience or have not learnt from their experiences would struggle to construct adequate representations to assist them.
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Brunswik (Hammond, 1993; 1996; Thompson & Dowding, 2009) argued that, faced with multiple fallible cues we create a sense-making representation of what we think these cues mean. This cognitive process is likened to a “lens” through which we see the cues in our environment and are thus able to create a holistic picture. The lens is our representation of the world and will be made up of the knowledge, values, experiences and beliefs that we use to make sense of our environment. So in a child abuse investigation or assessment the many fallible and uncertain indicators will be seen by the social worker through a lens made of a mix of personal and professional knowledge, beliefs and experience. This provides a quick way of intuitively making sense of a situation. The lens determines which cues are seen as more or less significant (or relevant) so there is a danger that the lens will distort the importance of some indicators introducing the possibility of error (Thompson & Dowding, 2009). O’Sullivan (2011), for example, suggests that social workers’ preoccupation with risk can skew their sense-making so that clients’ weaknesses are highlighted and their strengths overlooked These models of cognition map the ways that in real-world situations people intuitively build pictures or mental representations that make sense of situations holistically and do not rely on deliberative atomised choices between options. Another way of thinking about this, using the pictorial metaphor, is framing. O’Sullivan (2005) uses this metaphor to describe a process where people select information from indicators in the environment to construct a frame or picture within which they make a decision. Such thinking is intuitive because this representation-construction does not follow a step-by-step process (Hammond, 1996) but moves quickly to decisions based on a small number of cues identified as the most relevant in a mental process that is not explicit. It is not a fool-proof process but if the thinking processes are made explicit then the errors and biases can, ideally, be openly acknowledged and strategies developed to minimise them.
Another approach to considering errors is to take a more systems-based approach: that is, one where “poor case outcomes are likely due to multiple causes even though the most immediate cause may be the error of an individual” (Rzepnicki & Johnson, 2005, p.395). Gambrill (2005) suggests that any consideration of child protection situations where mistakes have occurred must consider “local rationality...the unique context in which a decision is made” (p.349). It was suggested in the previous chapter that systemic changes to “improve” practice can have unexpected consequences and create latent conditions for error. These can remain dormant for long periods until a combination of pressures such as heavy workloads, high performance targets, rushed assessments and poor supervision can result in an active
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failure (Reason, 2000). Munro (2005b) and Broadhurst et al. (2010a) identify technical, bureaucratic procedures that rigidly prescribe individuals’ practice yet are poorly suited to the ways in which humans actually think and to the ambiguous nature of the work. Munro (2005a; 2005b, 2008) singles out prescriptive assessment schedules, new technology and IT systems as particularly problematic in this respect. Organisations that are more successful at learning from disasters, as in engineering and aviation, build an awareness of human flexibility and adaptability into their solutions (Munro, 2008; Reason, 2000). Rather than trying to eradicate all error such organisations expect them to occur and place a high priority on recognising and addressing them. It is argued that health and social care organisations should be built not around efficiency and procedure but around creating strategies for minimising inevitable or unavoidable errors through good supervision, the facilitation of thoughtful reflective practice and mechanisms for encouraging team discussions (Taylor, 2013; Thompson & Dowding, 2009; Munro, 2008). These strategies are designed to create good “practice reasoning” (Munro, 2008, p.137) within a “culture of safety” (Thompson & Dowding, 2009, pp.128-130). The concept of the “learning organisation” which creates a context for critical reflection and learning is also relevant here (Gould & Baldwin, 2004). A good example is the use of skilfully managed supervision in using the strengths of more analytical decision theory to revisit decisions made heuristically so that, ideally, those decisions can be reviewed and any errors or oversights inherent in heuristic reasoning can be addressed (Helm, 2011).
As decisions have a significant emotional and moral element (White & Stancombe, 2003) a culture that serves to minimise error requires that its practitioners are supported emotionally in coping with the demands of the work as well as cognitively (Munro, 2008). The ways in which workers judgements can be frozen or distorted were discussed in the previous chapter. Taylor (2013) emphasises the importance of developing practitioners’ skills in retrieving, understanding and appraising research so that this kind of evidence can be used as well as more experiential sources. Social work has a diverse knowledge base and the ways in which social workers construct and use knowledge in practice is discussed later.
3.2.1 Summary
This section has examined a body of literature that makes explicit the ways in which people think and make decisions. A distinction may be made between prescriptive and descriptive models: the former based on logical, rational, deliberative analysis of the available options and the latter on the intuitive, heuristic processes followed by people making real life decisions in an uncertain world full of fallible indicators (Taylor, 2013). While classical models
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of decision making can be helpful in considering all the options (or all those that can be identified) systematically (provided there is enough time) they are not useful in reproducing the uncertainties and contexts of the real world or the realities of sequential and collaborative decision making across time and space and involving several actors (Atkinson, 1995). Intuition is, by definition, not an explicit process (Hammond, 1996) but its rationalities have been examined and persuasive models created which make clear the ways in which people make sense of uncertain, fast-moving situations and come to quick, good-enough decisions which are often very accurate but which can contain errors and biases. Decision making rationalities are best seen as existing on a cognitive continuum (Hammond, 1996) with actors moving between different modes of thinking depending on the task in hand and the local conditions. Given that people have only a limited ability to understand complexity – what has been called bounded rationality (Gigerenzer & Goldstein, 1996) – all forms of human rationality will contain the possibility of error.
It is suggested that being aware of the models of rationality professionals use and the strengths and limitations of their reasoning is more useful than trying to create fool-proof procedures that will somehow prevent any mistakes occurring. Such procedures, as we have seen, have become widely used in social work. They are invariably highly technical, rational and orderly, as bureaucratic procedures are by definition, so there may be a fundamental mismatch between the models of thinking they represent and the ways in which practitioners actually think: they represent prescriptive models of how professionals ought to think in perfect and logical conditions rather than the ways in which practitioners really think given the nature of their work and the ways in which humans reason about the real and irreducibly uncertain world. By forcing practitioners into certain ways of working they may actually increase the possibility of error and may do little or nothing to improve the ways in which practitioners think and make decisions.
Taking a systems approach to error means examining such latent systemic conditions for error and assessing the degree to which individual mistakes are a result of wider systemic dysfunctions. A systems approach also means taking steps to create a culture and a set of strategies that encourage more critical and reflective practice so that errors are to be expected and decisions can be revisited to minimise mistakes rather than creating rigid procedures in an attempt to eliminate all error. Good supervision and team discussions are often seen as vital in creating such a culture (Gould & Baldwin, 2004) and these aspects of the work were a focus of the empirical phase of this study.
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3.3 Decision making in social work: making decisions in conditions of extreme