How to develop qualities of attention to foster resilience: continuous vs. deliberate learning

Despite criticized for being fragmented, resilience is a very promising concept in organization studies (Linnenluecke, 2017; Williams et al. 2017; Hillmann & Guenther, 2020). From the previous fragmented conceptualizations of resilience, Williams et al. (2017: 742) offer an inclusive definition: resilience is "the process by which an actor (i.e., individual, organization, or community) builds and uses its capability endowments to interact with the environment in a way that positively adjusts and maintains functioning prior to, during, and following adversity". This definition is inclusive of pre and post adversity capability (ibid.); it both incorporates reference to resilience achieved ex post disturbances and that of precursor resilience, which proactively prevents major system failures from occurring (Macrae, 2019) and relates to the adaptive capacity component of resilience when adaptation means anticipation of disturbances before they occur (Woltjer, 2019). This definition is also inclusive of different kinds of adversity (Linnenluecke, 2017), especially that reflecting unexpected events and/or emerging challenges which transpire in complex environments (Williams et al., 2017; Woltier, 2019; Hillmann & Guenther, 2020). Moreover, functioning can be seen as seeking the balance between multiple goals, i.e. safety but also productivity, efficiency etc. (Woltjer, 2019; Anderson et al., 2019) to reach a higher level of performance (Hollnagel et al., 2009; Kyriakidis & Dang, 2019). From this inclusive definition, one may thus approach resilience in a particular manner, namely, as a process by which actors interact with their complex environment in a way that adjusts a multiple goals functioning, by proactively face unexpected events and emerging challenges. This particular way to approach resilience puts the emphasis on how people are able to deal with subtle changes (Woltjer, 2019), by noticing and responding relevant weak signals (Gould, 2019) and switching between stability and flexibility of their responses (Williams et al., 2017; Grote, 2019; Macrae & Wiig, 2019). It thus puts the emphasis on some particular micro-processes that fuel resilience: that of sensemaking of what is happening (Lengnick-Hall & Beck, 2005; Vogus & Sutcliffe, 2007; Berg & Aase, 2019), that of decision-making for appropriate customized responses (Lengnick-Hall & Beck, 2005; Vogus & Sutcliffe, 2007; Williams et al., 2017), and those related (Hillmann & Guenther, 2020) like that of allocation of attention for navigating the altered environment (Lengnick-Hall & Beck, 2005; Weick & Sutcliffe, 2006; Williams et al., 2017). These processes underlie mindfulness which in turn fuel resilience (Williams et al., 2017). In this line, resilience has to be conceptualized in relation with other existing concepts (Hillmann & Guenther, 2020), especially that of mindfulness and qualities of attention (Weick & Sutcliffe, 2006; Dane, 2011; 2013). Qualities of attention refer to the various qualities that attention may take on and by which attention can be characterized and described, regardless of where it is directed and of how individuals interpret cues in order to achieve efficiencies of operation. They refer to how people direct their attention toward certain cues and not others (i.e., perform certain patterns of attentional focus) and to how people make sense in order to make decisions and take actions (i.e., perform certain patterns of interpretation) (Dane, 2013). Studying resilience through this particular theoretical lens needs a multilevel analysis. The micro landscape of resilience, so-called situated resilience (Macrae, 2019; Macrae & Wiig, 2019), is one to explore: resilience is built at the level of people who are working on the operational frontline (Macrae, 2019; Kyriakidis & Dang, 2019); it refers to the micro-level adaptation, adjustment and intelligence performed to handle unexpected and non-routine events in front-line work (Macrae, 2019; Macrae & Wiig, 2019). But, because the collective level of actions, and not solely the individual one, makes up the resilient response (Gittell et al., 2006; Powley 2013; Sutcliffe & Vogus, 2003; Salanova et al. 2012), how and through what mechanisms individual resilience can potentially be scaled up to become more collective becomes an interesting question to respond (Wiig & Fahlbruch, 2019). This question expects insights and needs for research in the resilience field (ibid., Linnenluecke, 2017) and it echoes a similar question in the field of attention: how qualities of attention attained and maintained by single experienced mindful individuals must be able to induce more collective ones performed by mindful teams or groups (i.e., are able to translate from experienced mindful individuals to others) (Sutcliffe et al., 2016). Research on attention points out continuous learning as a core mechanism for the attention translation process (Weick et al., 1999; Weick & Sutcliffe, 2001; Krieger, 2005; Rerup, 2009; Ocasio et al., 2018). Yet, while approached as a self-evident mechanism that activates without difficulty, continuous learning, as its resulting attention translation process, deserve to receive further theoretical and empirical developments (Sutcliffe et al., 2016), especially in dynamic work settings still underexplored (ibid.). From the above, we thus ask the following research question: how the translation of qualities of attention from experienced mindful individuals to others can foster a more collective resilience in a medium-risks industry? To explore this question, we adopt a grounded theory approach (Glaser & Strauss, 1967; Strauss & Corbin, 1998; Charmaz, 2006) using a single exploratory case study in a dynamic work setting. The study is conducted in a cement plant manufacturing department where people have to manage complexity and uncertainty in a less risky context than nuclear or aviation. Ultimately, people have to monitor a complex combustion process by attending to a continuous stream of unexpected and unusual events, which means continuously processing numerous heterogeneous cues provided by a computer system put in a control room. Since the cement production runtime is 24 hours a day and 7 days a week, individuals rotate on 8-hour work shifts and the attention translation is expected to operate during handoffs. Note that people, divided in 5 shift teams we called A, B, C, D and E, seek multiple goals, i.e., staff safety and equipment safety but also productivity, compliance with various customers' requirements and compliance with strict environmental standards. Data were collected from multiple sources: 22 semi-structured interviews, 17 informal conversations, 13 observations, and external and internal documents. They were analysed using the conventional coding process of grounded theory as methodology (e.g., Glaser & Strauss, 1967, Strauss & Corbin, 1998; Charmaz, 2014; Gioia et al., 2013; Gehman et al., 2018). Our findings (1) identify different individual qualities of attention at work: normative attention performed by individuals of teams C, D and E, and elastic attention performed by individuals of teams A and B; they provide an in-depth analysis of their constitutive patterns of attentional focus and interpretation. (2) They highlight that elastic attention which equals a form of present-center attention is the most effective; note that elastic attention is also effective because conducive to multiple goals cross fertilization vs. balancing. (3) Mostly, our findings highlight that, although more effective, elastic attention does not spread from individuals of A and B to those of C, D and E during handoffs; designed to provide conditions for the attention translation from extensive, frequent and tightly coupled interactions, handoffs do not give rise to dialogical exchange, knowledge sharing and continuous learning; they do not translate elastic attention from A or B to C, D or E; put another way, individual resilience cannot be scaled up to become more collective. From our findings, we provide some theoretical contributions. First, by focusing on how occurs the translation from individual situated resilience to a more collective one, our study offers a novel way to address the topic by centering on the dark side of resilience, which is required by recent literature (Williams et al., 2017). Herein, the dark side investigated is learning, in particular the difficulties to learn qualities of attention which are expected to fuel situated resilience in dynamic work settings. Learning is assumed to support adaptive resilience (e.g., Meyer et al., 1982; Wildavsky, 1988). As a backdrop, authors defend the idea that people learn from experience, their own, through experiential learning (e.g., Wildavsky, 1988; Williams et al. 2017), and that of others, through cross-learning (e.g., Grote, 2019). Some authors points that learning may be difficult to accomplish (Baumard & Starbuck, 2005; Cannon & Edmondson, 2001, 2005; Edmondson, 2004). We complement by shedding in light at what extent cross-learning or learn from experiences of others through dialogue (i.e. continuous learning), is far from self-evident in dynamic work settings. In line with the literature on learning and complexity (Zollo & Winter, 2002; Zollo, 2009), we highlight that in dynamic work settings, learning cannot be continuous and therefore must be deliberate. We pursue by noting that, insofar as qualities of attention and their underlying patterns are primarily related to mental frames used by individuals to notice and interpret their environment (Langer & Moldeveanu, 2000; Sternberg, 2000; Kudesia, 2017), deliberate learning is expected to affect mental models. It thus becomes synonymous with double loop learning defined by Argyris and Schön (1978) as a radical change redefining frameworks and hypotheses underlying actions. Yet, such a learning is very difficult to promote because of requiring metacognitive practices (Kudesia, 2019), i.e., to get individuals to think about "how they think" and how they relate to the knowledge structures they use for acting and facing changing situations. Up to now, the literature on resilience has not enough emphasized or anticipated the cross-learning difficulty. It has not pointed out at what extent deliberate vs. continuous learning is pivotal for the attention translation process and the resulting collective resilience. This is our first main theoretical contribution. Our second one, closely related to the first, echoes a recent call to look at cross-level associations between different levels of resilience (Williams et al., 2017). In particular, by identifying deliberate learning on mental models as the key one to promote, we highlight another way to investigate cross-level associations between situated resilience and structured resilience (Macrae, 2019; Macrae & Wiig, 2019): the association investigated is not the usual one, from the micro to the meso level of resilience, but that of the meso to the micro level. Based on our findings, we also provide an additional contribution. As suggested in literature on resilience (Linnenluecke, 2017; Wiliams et al., 2017), we explore a still under-researched context, namely a less risky context than the ones generally investigated in the resilience field. In doing that, we provide insights on how situated resilience is actually performed to comply simultaneously multiple goals such as safety, productivity, product quality and compliance with environmental standards. Therefore and contrary to previous empirical studies (e.g., Berg & Aase, 2019), we relate situated resilience to cross-fertilization rather than balancing or trading-off goals achievement. Performance attained through resilience is addressed in its entirety, which is expected (Hollnagel et al., 2009; Williams et al., 2017; Kyriakidis & Dang, 2019; Anderson et al., 2019).