Interview analysis

Our research attempts to combine two main approaches in the social sciences. The first of these is to analyze interview data as qualitative data; that is, a transcription of the actual words used by the interviewee, through the technique of cognitive mapping. This verisimilitude is the key attraction of qualitative analysis (Wallace et al., 2003, p. 589). However, this advantage could also be seen as a disadvantage, in that the (comparatively) unstructured data produced are so resistant to procedural, ordered analysis. The quantitative approach, on the other hand, has the overwhelming advantage of producing data that are amenable to statistical analysis, something that is particularly important in a safety context (Wallace et al., 2003, p. 589). Therefore, we take a double approach to interview analysis. We first describe cognitive mapping (5.4.1), subsequently we depict what we have come to call the ‘diabolo’ technique (5.4.2).

5.4.1 Cognitive mapping

The recorded interviews were transcribed in the form of cognitive maps. Eden (2004) defines a cognitive map as: *…+ the representation of thinking about a problem that follows from the process of mapping. The maps are a network of nodes and arrows as links [...]. Cognitive maps form a tool for researchers to visualize how humans within organizations make sense of their environment and thus are helpful in the process of problem structuring in general (Montazemi &

Conrath, 1986). Cognitive mapping is a set of techniques for studying and recording people’s

perceptions about their environment. These perceptions were recorded graphically in the form of a mental map that shows concepts and relationships between concepts. Each individual interview has been transformed in an individual cognitive map, and if desirable all individual cognitive maps could be combined into one aggregated cognitive map representing the way operational risk concerning Incident Management is perceived. Such structuring of data is essential in the process of gaining understanding of the incident management (Bank) and the Maintenance & Repair (NPP) process within its complex environment (Eden, 2004). This general methodology was previously used in similar research (Rutkowski et al., 2005).

Working with cognitive mapping has the advantage that it can bridge the perception of the individual interviewee and the perception of the unit of analysis as a whole. The appropriate composition model for organizational culture is the referent-shift consensus model (Glisson &

James, 2002, p. 771). It uses individual responses to measure culture in work-units (e.g. in teams, divisions, departments or organizations). The respondents are asked to describe the behavioral expectations and normative beliefs of people in the respondent’s organizational work unit (Glisson & James, 2002, p. 771). Noteworthy is that “the focus is on what the individual believes are the expectations and norms for the people in the respondent’s work unit rather than on what the individual respondent thinks is expected of him or her personally. Within-group consensus is then required to justify the aggregation of the individuals’ beliefs about the behavioral expectations and norms within the work unit as a representation of the unit-level construct, i.e., culture. In the absence of within-group consensus, the individual responses cannot be ‘composed’

to the unit-level construct because a lack of consensus suggests that common expectations and norms have not been identified” (Glisson & James, 2002, p. 771). Whenever in this dissertation we are interested in finding out how the culture or structure of the organizations under study is contributing to high reliability – and even though we are examining the perception of individuals – we should not focus on the appreciation of the individuals personally, but on their idea about what their team members might think. Therefore, this calls for the application of the referent shift consensus model (Knight, 2004, p. 9).

In order to create the cognitive maps, the interviews with the employees were tape-recorded, to be transformed into cognitive maps afterwards, using Decision Explorer™ from Banxia™

(www.banxia.com). This approach allowed the researchers to capture the interviews in full detail without the disadvantage of having to take notes during the actual interviews.

Figure 3.7 - Example excerpt of a cognitive map with categorized nodes

The nodes in the cognitive maps were categorized by coloring them in order to allow for easier analysis of the information stored in them (Figure 3.7). An important category is that of threats to the Maintenance & Repair process or the entire organization that can be recognized in the maps. Nodes directly indicating such a threat were colored red. All the ‘red nodes’ from the maps were then assembled into an extensive list, from which double entries were removed, while the remaining threats were categorized in order to create an orderly list.

Once completed, the cognitive maps were sent back to the interviewees, giving each of them the opportunity to comment on their personal map and to indicate if they thought the map reflected the conversation as it had taken place. In about eight cases, minor changes to the maps were proposed, adding nuance to certain points. None of the interviewees suggested major changes in the structure of their map. It can therefore be concluded that the cognitive maps accurately represented the course of the interviews.

5.4.2 Diabolo technique

The systems view we take in this dissertation is an alternative for analysis. The accompanying risk is that by breaking things down into smaller pieces to simplify the study, the researcher might lose the oversight and will be developing a less than complete understanding (Bellinger, 2008b). However, we believe that ‘anasynthesis’, the combination of both techniques, i.e.

analysis and systems thinking, is useful. This is exactly what we have tried to do in our research.

To this end, this first research phase wished to determine how HRT – through the characteristics of HROs – could be applied in the particular organizational context of an important economic sector like Banking. Based on the outcomes of semi-structured interviews and workshops with process stakeholders/participants, the researchers gathered a list of operational risks concerning the IM process (Van Den Eede & Van de Walle, 2005). This outcome had to be formulated as an advice – for which there is a shared ownership – to senior management on how to manage risks

concerning Incident Management. The approach is not to do this on an operational one-by-one basis, but from a tactical or strategic management, more high-level perspective. Worthwhile mentioning is that it was the Bank’s management itself that chose to use HRT as a framework of analysis. Their interest for HRT was inspired by presentations and proposals the authors provided and – more importantly – by accepting the importance of culture, communication, structure, decision making and leadership as a complement to their IT governance frameworks and procedures (De Haes & Van Grembergen, 2005;De Haes & Van Grembergen, 2006).

The analysis is based on a systematic approach that aims at drawing qualitative conclusions from the data. By regrouping and looking for relevance, recommendations for the management of the risks could be formulated. Also has been possible to formulate questions for future research.

In a first phase we have been diverging (risk identification), followed by converging (complexity

& tight coupling) to end up again with diverging (tools). We have labeled this the ‘Diabolo‘

technique (Figure 3.8) and distinguish between the Converging and Diverging capacity.

The diabolo model starts from the assumption that interactive complexity (C in Figure 3.8) (complex vs. linear) and tight-coupling (T in Figure 3.8) (tight vs. loose coupling) constitute the two major determinants of reliability. For the underpinning thereof, we refer to Chapter 1 – Introduction). In the converging (left hand) part of the diabolo, all the individually identified risks (from the individual interviews) are first aggregated and categorized. With the collaboration of the IM process owner the data have been cleaned (removal of double entries, irrelevant information) and categorized. From the original list of 384 entries, a list of 219 remained. The categorization helped the researchers to gain a better insight into the data and to see the threads in the results. Next, this categorization was used to regroup the 219 records into 42 summarized risks in a meaningful way. Notably these 42 aggregated risks form the basis of the present investigation, which consisted in mapping them on the HRT framework.

Figure 3.8 - Diabolo Technique

In the diverging (right hand) part of the diabolo, the exercise was performed to come up with tools that are typical of an HRO’s pursuit of reliability. As a next step, we therefore have mapped the issues to the HRT principles. Subsequently, we have transposed these findings to HRT techniques that are suggested by HRO literature to be proficient in managing risk.