Engineers and Managers, A Multi-perspective Analysis of Conflict

Leeds University
Business School
Managers and Engineers, a Multi-perspective Analysis of Conflict
Stephen Peacock
Dissertation supervisor: Professor John Maule
Month and year of submission: September 2014
Word count: 12,000
This dissertation is submitted in part fulfilment of the requirements for the degree of Master of
Business Administration

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Table of Contents
Chapter 1: Introduction ............................................................................................................................................... 3
1.1 The Author’s Interest ............................................................................................................................................3
1.2 Research Background ...........................................................................................................................................3
1.3 The Research Question ........................................................................................................................................4
1.4 Dissertation Structure ..........................................................................................................................................4
Chapter 2: Literature Review ................................................................................................................................... 5
2.1 RQ 1 NoD .....................................................................................................................................................................5
2.2 RQ 2 Risk .....................................................................................................................................................................6
2.3 RQ 3 Rationality .......................................................................................................................................................6
2.4 RQ 4 Procedure Model ..........................................................................................................................................9
2.5 RQ 5 Organisation Types .....................................................................................................................................9
Chapter 3: Methodology ........................................................................................................................................... 12
3.1 Primary Data Collection Development ....................................................................................................... 14
3.2 Survey Sample Selection ................................................................................................................................... 14
3.3 Survey Questions Development ..................................................................................................................... 15
3.4 Sample Selection................................................................................................................................................... 16
3.5 Participant Interface Process .......................................................................................................................... 17
3.6 Data Extraction...................................................................................................................................................... 20
Chapter 4: Results & Analysis ............................................................................................................................... 22
4.1 RQ 1 NoD .................................................................................................................................................................. 23
4.2 RQ 2 Risk .................................................................................................................................................................. 24
4.3 RQ 3 Rationality .................................................................................................................................................... 25
4.4 RQ 4 Procedure Model ....................................................................................................................................... 28
4.5 RQ 5 Organisation Types .................................................................................................................................. 30
Chapter 5: Discussion ................................................................................................................................................ 32
5.1 NoD ............................................................................................................................................................................. 32
5.2 Risk ............................................................................................................................................................................. 32
5.3 Inequitable Distribution of Responsibility................................................................................................ 33
5.4 ‘Great Rationality Debate’................................................................................................................................. 34
Chapter 6: Conclusion & Recommendations ................................................................................................ 37
6.1 Conclusion ............................................................................................................................................................... 37
6.2 Recommendations ............................................................................................................................................... 37
6.3 Reflection on Learning ....................................................................................................................................... 38
Reference List ................................................................................................................................................................. 39

Appendices ...................................................................................................................................................................... 41
1. Survey Final Draft ................................................................................................................................................... 41
2. SSPS Data Analysis ................................................................................................................................................. 51
3. Example Interview Transcript .......................................................................................................................... 55
4. Unitised Data............................................................................................................................................................. 58
5. Interviewer Reflection .......................................................................................................................................... 62
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Chapter 1: Introduction
This chapter introduces the problem that has prompted the research and justifies the
Challenger Disaster’s relevance as a case study to gain a better understanding of the problem.
The general research question is developed, and the role of the subsequent chapters outlined.
1.1 The Author’s Interest
In 1986, the Challenger Space Shuttle tragically exploded shortly after launch; the launch
decision had been previously ratified by NASA managers overcoming the final element of
resistance from an engineer who was advised to; “take off your Engineers hat and put on your
Managers hat…” (Vaughan, 1996). This powerful metaphor demonstrated that a decision’s
outcome can be influenced by framing a question from a management perspective, at the
expense of professional obligations.
In this case, the values of the organisation were apparently emphasised and weighted higher
than the engineer’s professional values, and the decision resulted in disaster. The decision was
therefore certainly erroneous with respect to any universal notion of rationality. It would be
useful to know how prevalent these kinds of decision error are in the wider engineering
industry, and how knowledge of the circumstances that uphold them can inform their contest or
prevention. This meets the author’s organisation’s corporate level strategy aims to work
abreast engineering industries.
This is not a critique of managers. The author appreciates both perspectives from his own
experience; engineering staff in the author’s own organisation were reluctant to compromise
standards where it could be reasoned to have no consequence, for example, illustrating how
engineering staff may be excessively risk-averse. Conversely, clients use pressure to impose
shortcuts that result in residual risk, reflecting either their own risk preferences, or the fact that
they are not ultimately accountable. This subjects the management to pressure to meet the
client’s informal requests.
This research seeks further clarification on how the tension between engineers and managers is
managed, and what value hybrid manager-engineers bring.
1.2 Research Background
A major issue for the research is to identify whether similar decision errors manifest in the
Challenger Disaster continue to prevail in the engineering industries. The Normalisation of
Deviance (Vaughan, 1996), a sociological concept developed from the Challenger case, was
linked to the erroneous decision to launch, so it would be worth identifying if this still occurs in
organisations, and why. The Challenger case has raised the question of decisions being
contingent on values and the way they are rationalised. Whether the decisions are intuitive or
not is also relevant, because the decisions that upheld the Normalisation of Deviance must have
been intuitive to escape capture by the complex explicit procedures intended to isolate and

eliminate such errors. Naturally, the organisational context provoking erroneous decisions
cannot be ignored either; for example, how does culture influence such decisions? It will be
interesting to identify how ‘hybrid’ manager-engineers perform in all these respects, as they are
expected to reconcile the tension internally.
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By tracing the aetiology of the decision errors that underlie larger sociological issues in
organisations over a range of industries, the author will consider how to add value to
management processes without compromising the quality of an engineering solution.
1.3 The Research Question
The Challenger case comprises issues that can be identified from psychological and sociological
perspectives; the case will be examined, focusing on the engineer/manager relationship,
identifying some relevant theory that relate to these domains. Research questions that are
testable within the means of researcher will be developed, that identify issues applicable to
multiple engineering industries. How can examination of cases in engineering organisations
provide new insight into the psychological and sociological underpinnings of NoD?
1.4 Dissertation Structure
Chapter 2 - Literature Review: This chapter will clarify the research question by presenting
theories applied in the Challenger case that can be used to develop the primary data collection.
Development of the research question into focused elements will consider contemporary issues,
such as conflict between the theories identified and relationships between engineering
industries.
Chapter 3 - Methodology: This Chapter will explain how the survey and interview method
were developed from the research questions.
Chapter 4 - Results and Analysis: The significant results from the survey and interviews are
presented and analysed, using appropriate quantitative and qualitative analyses.
Chapter 5 - Discussion: The results and analysis are integrated with the literature, tensions
identified and discussed, and any findings that may contribute to contemporary knowledge
developed.
Chapter 6 - Conclusion: A summary of the findings is presented followed by a reflection on
how effective the research was and recommendations for stakeholders.

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Chapter 2: Literature Review
The objective of the review was to determine how adequate the existing research was at
facilitating analysis of the psychological, sociological and organisational domains in the context
of Normalisation of Deviance. This Chapter begins by outlining Vaughan’s (1996) research,
followed by a discussion of contemporary research on rationality, risk tolerance, normative
models, decision models and culture. These issues were isolated and arranged into a total five
sections representing individual Research Questions.
2.1 Research Question 1: Does Normalisation of Deviance occur in contemporary organisations?
The review of the Challenger disaster revealed that this event was not an isolated case.
Vaughan states that in both the fateful Challenger and Columbia disasters, Normalisation of
Deviance (NoD) had occurred. NoD is concisely defined as, “…a history of early warning signs
that were misinterpreted or ignored until it was too late” (Villeret, 2008).
For clarity, the term deviance refers to the movement of a safety reference point (Bazerman,
2009) beyond a margin that was previously deemed acceptable. In the Challenger case, the
degree of redundancy in a safety critical system was the reference. The normalisation refers to
the informal acceptance of the deviance by stakeholders within the organisation. NoD is a
function of the sociological domain, because the process is upheld in a broad organisational
context rather than due to the actions of an individual (Vaughan, 1996).
An important observation was NASA’s treatment of space flight as an operational, as opposed to
experimental enterprise (Villeret, 2008). Operational assumes that a system is in established
routine use and maybe available on the open market, for example. Experimental, by contrast, is
the status of a system that is not ready for the open market, as it has not been adequately tested
in diverse situations. The Challenger had made numerous incident-free flights before the
disaster, and was apparently taken for granted by managers as an operational system (Vaughan,
1996); not by the engineers, however.
Kline and Lynch (2000) make implicit evaluative judgements of the role of engineers. They
describe somewhat emotively the tyrannical leadership that imposes amoral calculation upon
them, i.e. engineers are victims of decisions that eschew their rights in favour of managers’
objectives. The state of Engineers in “dissent” and the “normalisation of deviance” are allegedly
typical states. Amoral calculation raises further questions of rationality that will be addressed
as a psychological concern.
It has been suggested that engineers are generally politically naïve; (engineer) “refuses to
consider…pathologies of cultural practices” (Kline and Lynch, 2000). However, the same paper
states that all the managers involved in the fateful decision to launch the Challenger were also
trained engineers by trade; “there aren’t any ‘pure management people’ in the whole stack”
(Vaughan, 1996). This suggests the difference between engineers and managers may be a
function of role rather than professional background. This important observation will be
considered in when developing the research methodology.

The conclusion of the Challenger case review is that the NoD may endure as an issue in
organisations, and it is as good a place to start as any to explore conflict between engineers and
managers.
2.2 Research Question 2: Can managers and engineers be distinguished by their attitude to risk?
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This element of the review contemplates whether managers and engineers risk attitude can be
differentiated and what factors might uphold this.
Kline and Lynch (2000) cite numerous instances preceding the Challenger disaster where
engineers’ recommendations were overturned. If engineers’ judgements could not be
overturned, no risks would be taken, and that is said to be naïve to the nature of the enterprise
of launching a space shuttle. Attitude to risk may be governed by other factors, such as
stakeholder perspective (Hayes, 2010). Engineers and managers could be argued to hold
contrasting stakeholder perspectives linked to their respective professional obligations and
exposure to risk.
A basic assumption in Slovic’s (2006) research is that risk is subjective; risk perception is based
on cultural and social factors, values that are socially communicated, the sociological
perspective of culture will be addressed in RQ4, RQ2 will use the psychological perspective.
Bazerman (2009) links rationality to both values and risk preferences, the latter will be
addressed in RQ2, rationality in RQ3.
“Change is bad” - this generally-held view in the engineering profession (Vaughan, 1996) is due
to the unintended consequences that may occur as a result of deviation, and justifies the
distinction between operational and experimental technology. For operational systems,
residual risks will have been declared as a matter of course, unless a stakeholder prematurely
defines the system as operational, as occurred in the Challenger disaster. The confusion of
operational and experimental technologies may be unintentional or intentional, the latter
suggesting a higher tolerance to risk.
Since there are assumptions that require resolution here, the research reported later will
investigate whether managers and engineers can be differentiated by their risk tolerance. The
underlying factors requiring a different approach to analysis are located in RQ3.
2.3 Research Question 3: Can engineers and managers be distinguished by their employment of
values and rationality?
Rationality emerging as an important but theoretically unresolved issue
Rationality has been raised numerous times in the Challenger case. The concept of amoral
calculation is related to the “logic of rational choice”, where the values that underlie the
rationality are largely self-serving and result in maleficence (Vaughan, 1996). We note here the
distinction of rationality from optimality of decisions, because the former includes values
(Stanovich, 2011) which are intangible. This suggests valus underpin the divergence in
rationality between engineer and manager – an issue explored later in the research.

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Noting bounded rationality as the reality in organisations, Vaughan (1996) raises the
contemporary ‘great rationality debate’ (Stanovich, 2011). Bounded rationality recognises the
constraints on decision-makers’ rationality; comprehensive information to fully inform the
decision may be missing. Vaughan’s discourse highlights a dichotomy between managers and
engineers without resolving it due to the dominantly sociological approach. This issue is
explored in greater detail next.
The concept of normative in dispute
In the great rationality debate, the concept of normative is bi-stable. This bi-stability describes
the definition of the meliorist and panglossian positions (Stanovich, 2011). The meliorist model
of normative views human judgement as typically sub-optimal and subject to errors and biases;
optimal decisions are qualified by freedom from heuristic-based errors and biases. Klein (2009)
criticises the meliorist approach, and the associated terminology, on moral and methodological
grounds; errors and biases, in particular, are claimed to be negatively connotative. Klein adopts
the contrasting panglossian position, asserting the descriptive model of human decision-making
as normative; which includes value judgements, which although less observable, are very
relevant. An implicit criticism of the meliorist position’s lack of differentiation is made;
Stanovich (2011) acknowledges that the meliorist position has followed the impetus of its high
emphasis on testability, given how easy and convenient it is to prove that axioms of rational
choice are violated. The meliorist approach then, has an emphasis on testability because
rigorous testing and results are relatively easy to observe and apply. The panglossian theory is
apt to differentiation at the expense of testability (Sapsford, 2001), i.e. ‘values’ allow highly
nuanced distinctions between behaviour and experience, but are somewhat less obsevable and
inferential. Indeed, the meliorist position may be ignorant of the full range of value-based
notions of rationality subjects exhibit in the organisational context.
Stanovich (2011)* has articulated the potentially nefarious implications of a meliorist approach
that assumes decision-makers are often unwitting victims to internal errors elicited by external
cues. We can apply a similar concept in the workplace, where decision makers may be
channelled into decision-making that is not necessarily aligned with their own values or utility.
The Panglossian position’s questionable compatibility with sustainable competitive advantage
(Henry, 2011) will be discussed, in view of the limitations inferred by decision makers not
following a repeatable procedure.
* Stanovich refers to an article in the economist (1998) that articulates the difference between the meliorist and
panglossian models, the former assumes humans are bad decision makers, the latter assumes they are good decision
makers.
The concept of epistemic - or the more self-explanatory definition, evidential - rationality
pertains to the evaluation of evidence and beliefs, believed to be a natural feature of the
engineer (Kline and Lynch, 2000). Instrumental rationality is defined most elegantly as
“optimisation of individual’s goal fulfilment” (Stanovich, 2011), out of which extends the “notion
of expected utility”; this could be argued to be a feature of the manager. The key distinction
between them, is instrumental rationality’s gravity of a goal (Brossel et al. 2013), the
significance of which will emerge later. This is relevant to the issue of NoD, because the
deviance must represent some form of instrumental rationalisation; of course, it cannot be
based on epistemic rationality, because the epistemic ideal would prove deviation irrational
from the engineering value point of view.

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Kahneman (2011) refers to the definition of rationality in the decision theory context as being
based on whether a person’s beliefs and preferences are internally consistent. Irrationality, at
the extreme then, is the situation arising from internally inconsistent values. As “logical
coherence”, meliorist rationality is also distinguished from reasonability, because although a
person’s actions may be rational in terms of their personal values, they may not be reasonable
in a wider social context. From this perspective, engineers and managers may be distinguished
due to the engineer’s inextricable link with the physical environment and their obligation to
non-negotiable values – objectively, at least. This may reflect in engineers’ negativity and
pessimism in the context of a project schedule, conflicting with the manager’s goal-based
attitude to risk that may be in a continuous flux dependent on the circumstances, subjective or
otherwise. Importantly, here we have distinguished between the rationality employed in
individuals and groups.
Economics based theories of rationality are somewhat ignorant of the values that make holders
of less tangible values appear irrational, hence the distinction of Econs and Humans (Thaler,
cited in Kahneman, 2011). The assumptions underlying utility may suggest that engineers serve
a vocational or professional utility, in contrast to managers who may serve an economic or
alternative professional utility. This may be used to highlight the identification of managers
with an organisation and engineers with the profession, for example.
Steare and Stamboulides (2014) state that managers “may fail to consider the impact of their
choices on the wellbeing and interests of groups like customers, stakeholders and staff.” They
conclude, “that leaders and managers need to become more aware of their MoralDNA™ and their
biases in decision-making”. The conclusion invites debate about the nature of managers in
terms of their rationalism – or altruism, as the case may be. The juxtaposition of these latter
two terms is itself an evaluative judgement that implies instrumental rationalisation – each
serving an internal goal.
In the Chartered Management Institute’s quarterly, Professional Manager, Howes (2014) reports
on how “lying has become second nature to managers”. This text raises pertinent issues.
Two subtle but noteworthy distinctions exist between the Codes/Rules of Conduct/Practice
(CoP) for the Institute of Engineering & Technology (IET), Institution of Gas Engineers and
Managers (IGEM), Engineering Council UK (EcUK) and CMI:
 The IET and IGEM require notification by members “…in writing of any conflict or
potential conflict…between their personal interests and the interests of their employer”
(IET, 2012), in contrast to the CMI (2014), professional managers are expected to;
“Disclose any personal interest which may affect my managerial decisions”.
 Explicit in the EcUK Code (Seddon, 2014), is the requirement to, “Notify the Institution if
convicted of a criminal offence or upon becoming bankrupt or disqualified as a Company
Director.” This requirement is mandated in the IGEM and IET Codes (under a broader
requirement), but is absent from the CMI Code.
This section contains a range of concepts that are difficult to separate. Therefore RQ3 will
distinguish between instrumental and epistemic rationality, and consider values included in the
rationality. The important distinction between meliorist and panglossian models will be carried
over into RQ4.

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2.4 Research Question 4: How do the meliorist and panglossian approaches manifest in
organisations’ decision management?
NoD may occur for a number of reasons, and may be intentional or unintentional. In either case,
what type of decisions lead to it?
Klein (2009), citing Damasio (1994) suggests that intuition and analytic judgement are mutually
dependent for the sound judgement taken for granted even in basic decisions. Either engineers
or managers may be more susceptible to decision errors in decision-making, not an
unreasonable assumption, given the epistemic rationality expected of a trained engineer.
Kahneman (2011), representing the meliorist position, citing Simon (1982), points out that
engineers are less likely to rely on intuition in their technical decisions; they, “rely on look-up
tables”, or base decisions on success in previous experience and explicit analysis. In contrast,
Klein (2009) criticises decision-support systems - the typical meliorist tool - claiming they can
be detrimental to the decision process, justifying why they are often rejected. Gigerenzer’s
(2008) panglossian argument; the Take the Best heuristic was found to be superior to ‘Bayes’
rule, the “goliath of rational strategies”. Applying such an approach in an engineering setting
may yield blind-spots, however. Engineers are more likely to be subject to a meliorist approach,
perhaps limiting intuitive judgement, as was the formal arrangement in the Challenger case and
as Kahneman advocates. Such procedures may require the engineer to calculate a value before
progress is permitted, for example. The manager, perhaps using instrumental rationality, is not
constrained. This distinction is a reasonable point for for exploring manager/engineer
distinctions.
This research question has taken a psychological angle in terms of how engineers and managers
make decisions, and considers the role of intuition and whether it is valued or not in the
organisational context; its value will be signalled by the incidence of meliorist or panglossian
decision procedures.
2.5 Research Question 5: Does organisational structure, size or culture have any bearing on how
effective the organisation is at avoiding errors?
In view of the brinkmanship that was imposed on engineers by managers during the Challenger
launch decision, the concept of functional and dysfunctional conflict should be considered.
Functional conflict is that which “enhances and benefits the organisation’s performance”
(Gibson et al. 2012) whereas dysfunctional conflict detracts. It appears that conflict in these
terms is defined by the perception of those who broker political power. The Challenger pro-launch
managers assumed the conflict with engineers to be functional, until the disaster
occurred, where it may be retrospectively accepted as dysfunctional. This social construction of
conflict is curious because the structure or size of an organisation may influence the informal
classification of a risk.
The tension manifest between the Engineer and Manager is well researched. However, Kline
and Lynch, (2000) concluded that engineering ethicists have neglected the environmental
influences. Additionally, Kahneman (2011) states, “organisations are better than individuals

when it comes to avoiding errors”, justifying this statement by claiming procedures are likely to
isolate errors that might occur in individuals. This is the logical theoretical conclusion of the
meliorist position, but is loaded with untested assumptions. Also of concern is that large
organisations are loosely-coupled (Orton & Weick, 1990), i.e. not very responsive to
environmental changes. A small organisation, by comparison, may be more open to impromptu
modification, particularly where centralised decision-making is the norm.
Vaughan (1996), suggests that risk in the Challenger case was socially constructed by the
organisational culture. A strong meliorist position was dominant; “Engineers were empowered
or disempowered to take formal action by their data…the subjective, intuitive, the concern not
affirmed by data analysis were not grounds for formal action” (Vaughan, 1996). The
possibility that risk was rationalised, perhaps by a manager, is suggested, because the absence
of data to support a possible issue with the ‘joints’ determined that no action was necessary; “To
proceed with the flight, to correct rather than redesign, was not a deviant action within the
workgroup culture” (Vaughan, 1996). This smacks of cultural influence upon rationality and
could be argued to be an entrepreneurial culture (Gibson et al., 2012). Ironically, the errors that
the meliorist procedures have been designed to mitigate, have been displaced by other errors
manifest in an increased and erroneous tolerance to risk. We should also maintain sensitivity to
the type of structure that might uphold the confusion of experimental and operational
technologies.
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This element of the review shows that there are social constructions of conflict, organisation
size, and culture to consider in the influence of behaviours that lead to NoD.
Conclusion
Some inconsistencies and omissions were identified in the literature, such as the rationality
concept, the role of intuitive judgement, and scarcity of current research on the Normalisation
of Deviance.
Vaughan’s findings and hypotheses in the Challenger case chimed with the current research
intentions. It appears little has been learned by NASA about the NoD between the Challenger
and Columbia disasters, therefore NoD remains a contemporary issue. The review unearthed
precious few applications of the NoD concept beyond Challenger, and in entirely different
contexts, so new research is warranted, hence RQ1.
The concepts unearthed in the review are difficult to analyse in isolation. For example,
rationality is linked to psychological concerns of risk-attitude, intuition, and sociological
concerns of organisational culture, size, procedure philosophy etc. Direction of causality is the
most obvious concern here. RQ2 will focus on the risk attitude distinction between engineers
and managers.
Vaughan’s review of the psychological perspective was not comprehensive, yet progress in this
area suggests that the psychological issues are of importance. The Great Rationality Debate has
progressed considerably since Vaughan’s research, and tensions exist which may benefit from
testing in context of the contemporary workplace. The NoD appears to be initiated from the
sociological domain, but the collective individual behaviour on which it is based, is non-

normative from a psychological perspective. This appears to question the panglossian position
as a continuously viable position in the context of sound engineering decisions. Therefore, two
objectives will be made within RQ3, to identify epistemic and instrumental rationality and
value-inclusion as a means of distinguishing engineers and managers. The examination of the
role of meliorist and panglossian decision approaches in organisations as a means to
determining how NoD might be caused by decision errors will be examined in RQ4. RQ5 will
link with all RQ’s, where the decision strategies are associated with particular organisation
structures, focussing critically on Kahneman’s (2011) claim that errors are typically reduced in
large organisations.
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Chapter 3: Methodology
Introduction
This Chapter is concerned with how the Methodology was developed to meet each RQ’s
objectives, and will cover major issues of which Figure 3.1 provides an overview.

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3.1 Primary Data Collection Development
Figure 3.1: Methodology Stages
3.2 Survey Sample Selection
3.3 Survey Questions Development
3.4 Sample Selection
3.5 Participant Interface Process (PIP)
Refer to Figure 3.2 for detail
3.6 Data Extraction

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3.1 Primary Data Collection Development
RQ1 required identification of NoD in organisations, for which purpose a critical incidence
technique was selected; eligible participants would describe their experience in detail. The
required detail suggesting the need for in-depth interviews, for which active responses -
responses whose critical incidents were genuine - were identified by a preliminary survey
(Saunders et al., 2009).
RQ’s 2, 3 and 4 were concerned with differentiating managers and engineers in terms illustrated
in table 3.1. Survey-collected quantitative data was cross-tabulated using situation-neutral
questions to identify differences between managers and engineers.
RQ5 required the identification of organisational characteristics. These were collected in the
Demographic Data - Section 5 of the survey, and expanded in the interviews, drawing on
organisational culture theories.
3.2 Survey Sample Selection
A non-probability, self-selection sampling approach (Saunders et al., 2009) was used to recruit
respondents to the survey. The self-selection method was instrumental to obtain a high level of
co-operation from respondents, in turn to obtain genuine insight into controversies inherent in
the issues and situations covered. All RQs required the following sample:
Heterogeneity in:
 Role experience
 Industry
 Organisation structure and size
 Duration of experience
 Engineering and/or management seniority
Homogeneity in:
 Training formalisation
 Degree of industry experience
 Codes of Practice conversance
The survey structure sorted the respondents into heterogeneous categories. These categories,
indicated in figure 3.2, are justified in table 3.1, in recognition that three of the RQ’s required a
distinction between roles and a key finding from the Challenger case study that pure Engineers
behave distinctly from those with manager experience. There was no evidence available for
‘hybrid’ manager-engineers with synchronised responsibilities, but this distinction is relevant to
the research as some engineers may be self-employed or Directors, and therefore managers.

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Range of roles and assumptions relationship with Research Questions -
derived from Challenger case study at Literature Review Stage
Research
Question
variables
Engineer Manager
Previously
Engineer
Manager and
Engineer
Manager
Category Descriptor Engineer formally
trained, may also
include technicians
A Manager who
has previously held
engineer role
A Manager who is
also an engineer –
the ‘hybrid’;
distinguished by
resolving tensions
internally?
Manager who held
no previous
engineering role
RQ2
Risk Tolerance
Expected to be
Risk-averse
Assumes higher
risk-tolerance
associated with
managers
No data acquired
from case
High risk-tolerance
RQ3
Values/rationality
Employs
epistemic
rationality
Assumes
instrumental
rationality
No data acquired
from case
Employs
instrumental
rationality
RQ4
Procedure Model
Expected to
work to a
meliorist
procedure
A panglossian
model may take
precedency
No data acquired
from case
A panglossian
model may take
precedency
Table 3.1: Relationship of each role category with the relevant research questions
3.3 Development of survey questions
The complete Survey is presented in Appendix 1. For brevity, this section explains how the
survey was developed, with attention to those questions for which useful data was recovered
and how they related to each RQ.
The survey took approximately 15 minutes to complete – short for purposes of maintaining
optimum concentration and minimising the completion time. Questions 10-14 were dedicated
to identifying critical incidences or drawing quantitative data for RQ2.
The success of invoking the critical incidence technique was contingent on respondents
disclosing potentially sensitive information. For this reason, the questions were not overly
specific or controversial, allowing self-selecting interviewee discretion of what they would
prefer to discuss. It was also suggested in the survey that interviewees consider a previous
organisation when answering questions.
Questions 1-9 obtained informed consent, confirmed homogeniety/heterogeniety, and
demographics that would ultimately be cross-tabulated with questions 10-14.

Question 10 identified experience of operational or experimental (developmental) technology.
Question 11 was a ranking question requiring respondents to place 8 factors in order of
potency of governing action that leads to risk. This question was the most problematic in the
pilot test and required subtle amendment of the wording to guarantee consistent responses in
the final survey. This question was important because the primacy of it in the survey would
focus the respondent on their experiences in the following questions whilst drawing out major
factors required for RQ5.
Question 12 was a question aimed at identifying respondents-experienced critical incidences of
which there were 11 listed examples, and a twelfth optional field for respondents to provide
their own example. Each example outlined a tension that could be found in any engineering
organisation and respondents had to select any that applied. One example is; 12.3 “We are
obliged to take risks and manage them, because hazards emerge during a project and we cannot
allow the project to fail”.
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Respondents that selected situations and also indicated a willingness to be interviewed were
identified as possible respondents for the interview stage of the research.
Question 13 was a Likert-scale based set of 7 closed questions that required selection of degree
of agreement on a 5-point scale. The Likert-scale was important because polarity of tension
could be signalled by agreement or disagreement with a statement, and dysfunctional conflict as
required by RQ5. For example, in order to elicit risk tolerance of engineers and managers for
RQ2, statements such as the following were used:
13.2 “They don’t understand the risk, but they make a decision based on their assumption that they
do”
All seven statements were made as neutral as possible in order that they could be applied to
either engineers or managers at various levels within an organsiation.
Question 14
Four types of Code of Conduct that might govern practice or decision-making were investigated
in this question.
3.4 Sample Selection
A potentially large sample was immediately available from LinkedIn groups as shown in Table
3.2. These particular groups were ‘members only’, minimising the potential for ‘hoax’ responses
made to the potential remuneration offered. Professional institute membership is typically
synonymous with values of professional and personal-development, therefore increasing the
likelihood of genuine and comprehensive responses. An argument that the generalisability is
limited as non-professionally registered respondents are filtered out can be countered by the
ability to obtain more consistent results by reducing the independent variables that may be
incumbent with samples of unknown provenance.

Name of Group Justification Population (as of 01/03/2014)
17
Institute of Engineering and
Technology (IET) Official
LinkedIn Group
Comprises both requisite
heterogeneity and homogeneity.
Researcher is Member
23,175
Chartered Institute of
Building Services Engineers
(CIBSE) Official LinkedIn Group
Researcher is affiliate Member. 13,189
Institute of Gas Engineers
and Managers (IGEM) Official
LinkedIn Group
Researcher is corporate Member. 1,232
Engineering Council UK
(EcUK) Official LinkedIn Group
Issuing Council of engineering
professional registration and
base CoP.
1,541
Risk Managers LinkedIn Group Large membership and expected
expertise in Risk subject area.
67,284
Engineers and/or
Enterprise owners known
to researcher
Micro-enterprise representation. 4
Table 3.2: Sample sources
The focus in this selection process was to ensure valid data would be obtained by accessing
participants who could contribute via their experience of situations akin to the Challenger case
study.
3.5 Participant Interface Process (PIP)
Figure 3.2 indicates the stages of the PIP, i.e. work where dialogue with participants was
necessary for data collection. The stages that were subject to interface with participants were
carefully scheduled to ensure the research findings were appropriately developed at each stage,
i.e. Interview selection was contingent on the survey findings. Also, the quantitative analysis of
survey data needed to be complete before the interview adminstration so that significant
findings could be discussed with interviewees where appropriate. Because statistical analysis
of quantitative data was necessary for RQ2 a minimum of 50 respondents was required for the
survey.

18
A. Survey Administration
The survey was developed and subject to a pilot test
modifications were made as necessary
A live link provided in the groups shown in Table 3.2
B. Quantitative Data Collection
Survey quantitative data was tabulated and issues identified suitable for expansion in interview
C. Interview Selection
Selection of active responses to survey questions that indicated possible critical incidences and
respondents had self-selected for interview
D. Quantitative Data Analysis
The tabulated data was analysed and subject to analysis for statistical significance
E. Interview Administration
Interviews were conducted according to the schedule
transcripts subject to interviewee verification produced
F. Qualitative Data Collection
The interview transcripts' were verified as satisfactory by the intervieweed
transcripts were formatted to a standard that would be conducive to analysis
G. Qualitative Data Analysis
Categorisation and open coding was applied to the qualitative data
Figure 3.2: Stages of Participant Interface Process (PIP)

19
3.5 (A) Survey Administration
Figure 3.3 illustrates how many respondents were retained at each stage of the PIP which lasted
6 weeks, adequate time to allow all respondents to schedule its completion, and the early
interview self-selecting respondents to have the content of the survey in their memory. The
figure shows how of 56 self-selected interviewees, 25 were both active-responses and an
interview successfully arranged, in contrast with the target of 25 and 15, respectively. ‘Pure’
managers and engineers who completed interviews were in a minority.
106
10
29
31
26
10
24
27
22
7
17
17
16
Manager
Manager Previously
Engineer
Manager and Engineer
Engineer
Unspecified Total
3
9
8
5
120
100
80
60
40
20
0
Opened Survey Proceeded past
Introduction
Completed
Survey
Volunteered for
Interview
Completed
Interview
Figure 3.3: Degree of participant retention in respect of roles throughout survey and interview process. A
question sorting respondents into role categories was applied subsequent to Introduction.

20
3.5 (E) Interview Administration
The survey’s interview self-selection process allowed respondents to determine the method of
protecting their data (Appendix 1, questions 16-20). A third of the self-selected respondents
requested not to have the interview audio recorded, therefore it was resolved that all
respondents should undertake a review/amendment of their interview transcripts instead. This
measure also fulfilled the anonymity condition that most interviewees had selected. This was
also thought appropriate to ensure accuracy of the descriptive data, enable asynchronous
analysis, and reduce biased interpretation in absence of the preferred audio recording analysis
(Saunders et al., 2009).
The interviews enabled validation of survey answers and discussion of outlying response; each
respondent’s completed survey was emailed to them in advance of the interview, providing an
aide-memoire for their answers. Respondents self-selected between real-time interviewing and
written questionnaires; of the twenty-five interviewees, five selected written questionnaires, it
is worth noting that these responses were high in content and relevance. Where possible, real-time
interviews were conducted face-to-face as the researcher found this the most effective and
expedient method of producing a completed transcript.
The interviews’ experiential reports were to be recognised as inside or outside perspectives
(Sapsford, 2001), i.e. first-person in terms of conscious processing, or third-person reports of
others’ behaviour, respectively. This was important for data subject to the differentiation issue
identified in Chapter 2, where the inclusion of values and rationality in RQ3 would likely only be
reported with any validity from the inside perspective, and such valid data may be scarce.
Researcher experiential data was recorded in the interviewer critical reflection (Appendix 5),
with an emphasis on discourse analysis. The aim was to maintain interviewer objectivity in
order that interviewee responses were not influenced, ensure any negative experiences were
not allowed to influence subsequent interview conduct, and develop the interview skills of the
researcher in this context. The critical reflection was especially important in the early
interviews, where conversation may digress or possibly enter into dispute. The critical
reflection notes ceased after six interviews, suggesting that the requisite interview competence
level had been achieved.
3.6 Data Extraction Method
RQ1: Identification of critical incidences was required to allow active responses to be followed
up in interview. Question 12 contained situations that were antecedent to NoD based on what
had been learned from the Challenger case study; Question 10 was used to distinguish between
experimental and operational technology.
RQ2: Quantitative data was collected directly from Q13.1, discussed in detail in Chapter 4.
RQ3: This was informed by interview data on compromised values in the workplace, generally
prompted by Question 13.
RQ4: This was addressed indirectly by categorising interview text. The literature review noted
the panglossian and meliorist decision procedures as distinct in terms of their degree of

21
differentiation (Sapsford, 2001); differentiation is likely to be possible only where nuances
inferred by the values are reflected in the discourse of respondents, therefore a range of
psychological and sociological epistemologies were appropriate here.
RQ5: Culture was raised in interviews, using answers to Question 11 where cliques/informal
networks were noted as important governors of risk, for example.

22
Chapter 4: Results and Analysis
This Chapter is organised around the 5 RQ’s identified in Chapter 2. The results are presented
as consolidated survey and interview data – RQ2 the exception. The relationship between in the
research questions and data from the survey and interviews is outlined in Table 4.1 below.
Research Question Survey Data Role Interview Data Role
RQ1 NoD Indicate Critical Incidence Qualitative data from
discussion
RQ2 Risk Tolerance Quantitative Data Qualitative Support to
Quantitative Analysis
RQ3 Values/rationality Indicate Critical Incidence and
record explicit values
Open-coding draws
qualitative data from
discussion
RQ4 Decision Model Indicate Critical Incidence Qualitative data from
discussion
RQ5 Culture, Structure, Size Indicate Critical Incidence Qualitative data from
discussion informed analysis
that cross-referred with
critical incidents of other RQs
Table 4.1: Relationship between each RQ and the data, and how the data was consolidated
Sections 1 to 5 discuss the results of each RQ’s data followed by a short conclusion. RQ1 reports
the positive incidence of NoD, RQ2 the statistical significance of differentiation risk tolerance
between engineers and managers, and the effects of contrasting rationalisation researched in
RQ3 are presented. These were obtained by open-code analysis (Strauss and Corbin, 2008), and
the strongest codes are included here. RQ4 identified incidence of meliorist decision models
and their role in NoD’s incidence. RQ5 reflects on the previous data and contemplates how
culture may be associated with dysfunctional conflict as well as NoD.
Due to the volume of data generated, not all examples are presented in the results. For the same
reason, the responses for all RQ’s have been represented by the most lucid quotes. For the
reader requiring a more complete view of the results, further quotes are located in Appendix 4.
Interview transcripts were coded by highlighting critical incidents with each RQ a distinct
colour code as in Table 4.1. Preference of critical incidents was generally based on the strength
of evidence, number of RQs the incident cross-referred to and the potential consequences
involved in the case. Interview Transcripts and their Numbered Paragraphs are referred to by
the super-scripts accompanying quotes or events from hereonin in the paper. “Interview 1,
Paragraph 2” is expressed “1.2” for example.

23
4.1 Research Question 1: Does NoD occur in contemporary organisations?
NoD was identified by the critical incidence technique in at least two independent transcripts.
We should note for reference that none of the micro-enterprises22,24 or SME’s3,14 explicitly or
implicitly reported NoD, NoD was identified in the case of large organisations only.
Indirectly induced NoD
Critical incidents were identified in the nuclear industry, via independent accounts of the same
failure to apply “proper root cause analysis”19.19 following “failed control of reactor cores”16.5a or
“accident/incident”19.19. These interesting cases share the failure of procedure as a precursor of
NoD, where operators/engineers acquiesce to erroneous procedures that have deviated from a
normative procedure. “Grandfathered”16.5c procedures responsible for near misses are also
reported. For this reason the category ‘indirectly induced’ has been coined, because the NoD
consequential from oversight or honest omission is an unintended consequence.
The cause of failure of procedure in indirectly induced NoD is addressed in RQ4.
Directly induced NoD
Directly induced NoD, by contrast, is where managers impose demands that engineers can only
meet by voluntarily compromising normative procedures.
Under duress of project delay or potential for increased profit margins, managers impose the
“11th Commandment” thou shalt not get caught onto gas industry engineers, whom face an
escalation of commitment, for which they may be recompensed by financial reward12.10.
In the nuclear industry, management may impose cost savings, such as extending the service of
particular facilities, whilst distributing the responsibility inequitably to engineers16.2d,19.22.
Deviation occurs due to judgement of operational risks without subjecting them to “as low as
reasonably practical” (ALARP) criteria16.2b. Inappropriate analogies made out of context by a
operating authorites in two independent cases are an example of how deviance might be
normalised in the absence of an authority for engineering16.5d,e. The compromise of ALARP
criteria by the operations section was also identified in defence aviation organisation(s)25.7. The
sensitive details of these latter examples have been omitted at the request of the interviewees,
but in both cases, operations sections used a method of framing the risk outside of the ALARP
criteria to enable deviation, which is why this category is termed ‘directly induced NoD’.
Further examples in other organisations such as the military were found2.4.
Three discrete cases16.2e,16.3,25.7 demonstrated operations departments influence of deviation
from established criteria, defining the experimental resources at their disposal as operational.
The obfuscation of the experimental and operational domains for technology is also committed
intentionally or unitentionally.
RQ1 Conclusion
NoD occurs in large organisations, induced either directly by the action of managers, or
indirectly as a result of procedures inadequately engaging the operators/engineers with the
remedial action required. This occurs even those organisations considered the most highly
regulated, a discovery pregnant with tension that will be resolved in RQ4. Importantly, the

24
incidence of experimental/operational confusion resonates strongly with the history of the
Challenger case.
4.2 Research Question 2: Can managers and engineers be distinguished by their attitude to risk?
Initial quantitative assessment of the survey’s raw data provided results that suggest that
engineers are more risk averse than manager. Findings relating to the Question asking
participants “Thinking about your experience in your job function, to what extent do you agree
with: ‘If we followed their averse attitude to risk, no project would even go ahead, nor would we
get anything done!’” are illustrated in Figure 4.1. The positive skew for managers, and the
negative skew for engineers suggests greater risk seeking attitudes in managers.
50.0%
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Agree
Strongly
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
Engineers
Managers
Figure 4.1 Survey sample response to ‘risk’ question, expressed in percentage of respondents from each
group

25
A chi-square test for association between role and risk aversion was conducted. There was a
statistically significant association between role and risk tolerance, χ2(1) = 5.926, p = 0.015,
upholding the idea that engineers were more risk averse than managers.
Did the subsequent interviews; qualitative data consolidate these quantitative results?
The following examples derived from interviews support the quantitative analysis:
Engineers’ Quotes
Engineers typically require all the facts before deciding11.4,17.12
Engineers “…naturally risk averse…”10.8,19.19
“…risk defined as hoping for a favourable outcome when you have too little information to
calculate that outcome…is not a natural situation for engineers, consequently they are very
reluctant risk-takers”13.7
This data set indicates engineers’ risk aversion.
Managers’ Quotes
[ex-engineer] “changed approach due to experience of P&L management”6.15 and “not too open
about risk because it achieves little”6.8
“…whereas Project Managers comfortable with risk”19.19,18.4
[managers’] “risk appetite is signaled by remedy, or not, of non-conformities”8.11
SME-owning manager and engineer cites his expertise of dealing with risk as his competitive
advantage13.13-18
“nuclear industry excessively risk averse – not a practical way to manage risk”6.10 The
importance of this incongruous statement will become clear later.
This data set shows that managers or engineers with management experience beyond the remit
of typical engineers results in altered attitude to risk. Managers appear to value factors
extraneous to the source of risk itself, altering as a project develops, demonstrating an
instrumental rationality.
RQ2 Conclusion
The conclusion of this section that engineers are more risk averse represents one facet of a
more complex situation where engineers and managers typically employ epistemic and
instrumental rationality respectively, which is analysed in the following section.
4.3 Research Question 3; Can engineers and managers be distinguished by their employment of
values and rationality?
Inequitable Distribution of Responsibility

A code emerged from the interview analysis that can be described as the inequitable distribution
of responsibility (IDR), an example of this may be where a manager’s decision results in a
residual risk, which subsequently made the responsibility of engineer(s), or where engineers
are coerced to take-on excessive responsibility. Such decisions, where the residual risk is
intentionally discharged onto the engineer demonstrates amoral calculation (Vaughan, 1996)
which the findings showed to feature mainly in large organisations. For example, engineers
may not be furnished with adequate resources to apply critical safety measures, which may
even be passed off as “desirable...” and “...the engineer is required to make compromise of their
own”1.4. This apparently happens because managers can claim the “savings” in resources as
their own achievement. Managers justify this by employment of instrumental rationality - focus
on goals that are unrelated to the engineering task, yet still rely on the practical success of the
engineering task, and it’s enduring safety. By contrast, engineers defend their position based on
principles rooted in the physical world, using epistemic rationality, typically requiring all the
facts before deciding11.4,17.12.
IDR was initially illuminated by survey responses to the Question 12 scenario, “We can mitigate
our exposure by contracting out that risky element of the project”. Strength of this code was
indicated by the fact that respondents in the survey ranked this statement fourth among the
twelve they were asked to assess in question 12. Further investigation of this trend via
interview questions showed that organisations’ practice of discharging responsibility intra-organisationally
as the most prevalent issue that divided managers and engineers. According to
26
engineers - or managers who were or still are engineers - managers’ means of inducing IDR
were;
“Trim the labour force”1.4
“Set unrealistic time limits”2.4
“turn a blind eye to engineering staff when they cut corners”12.4,6,7
[make] “engineers…accountable for the actions of others”16.2d
“ignoring the implied and expected specifications”19.10
“discharging their responsibility…onto “coal-face” staff”23.5
“Management were aware of the impracticality of the procedure, but this was a mechanism to
manage the risk and isolate the potential liability to the company”24.12
“discharge responsibilities but not commensurate degree of power”25.6,7
According to engineers, this also occurs inter-organisationally, where; “forcing an excessively
risky element of a project onto a contractor was a common tactic by one MNE...” (allowing)
“...managers to increase their own prospects/credibility”12.12. IDR may eventually result in
engineers being pushed to their limits and whistle-blowing to prevent themselves being subject
to prosecution3.11.
The prevalence of this practice of shifting responsibility using informal means makes it an area
of significant interest for two reasons:
 What environmental conditions allow the informal practice to be imposed?

27
 The practice of IDR has already been linked with the occurence of NoD in the isolated
critical incidents of RQ1.
Engineers’ resistance to IDR with professional integrity
Integrity is the system of values espoused by engineers that appears to differentiate them from
managers, evidenced by reports of unwillingness to compromise the engineering definition of
normative:
Engineers report their values to be based on professionalism and unwillingness to compromise
it12.18
“Competency and integrity are the best long term strategies for success”13.5.
Making a choice of vetoing or supporting a decision is defended with integrity, when ownership
for the decision is taken2.18
“…over-weighting of commercial…to technical interests is a fallacy”9.4
Some engineers (and engineering managers) have “personal standards that prevent them from
overlooking things ‘that don’t look right’”25.10
Value-based tension between Groups
Following RQ2, where risk-aversion of engineers was hypothetically linked to epistemic
rationality, deliberation of facts reflected the values of engineers3.1, non-engineering
stakeholders may consequently perceive them as pessimistic3.7. The “virtues of being honest
and up-front”3.20 are promoted by an engineer and SME owner/manager. One engineer
considered themselves “cynical”, if in the course of “refusing to undertake the task…or agree to
undertake the task and something adverse happens…you have to defend that decision with your
integrity” 2.18
In contrast, a manager reports that his “job…is to make things happen…articulating ways of
controlling risk that allow it to be…acceptable to the business”21.5a. According to two engineers,
managers are thought to be quick-decision makers, and make their mark by the volume of
decisions made.13.7, “…a blunder-buss effect”14.4
A ‘smoking gun’ for NoD as a result of managers’ instrumental rationality?
One critical incident reported by an engineer with over forty years’ experience indicated that
managers without the technical background may trivialise engineers’ job in their rationalisation
that results in IDR12.4. Sometimes, the “11th Commandment” thou shalt not get caught is applied
by managers to engineers in the context of a tight-project12.6, or, more technically, an informal
structure of influence trumps the objective, legislation-structured one. Managers’ concern with
financial metrics as targets, “…sees that a project is going to meet the 20% profit margin, he can
apply pressure to the engineering staff to speed things up by circumventing rules and
regulations where possible”12.7. Or, as another engineer reports, a “…’balanced’ view of risk was
taken, until deadlines loomed, when it was necessary to consider loss of bonus if project was not
delivered”17.4. These conditional perspectives on risk are informal instrumental rationalisation.
How seriously do professionals regard CoP?

Survey Question 14 (Appendix 1) requested respondents to select Codes of Practice (CoP) that
they may be subject to. No significant difference between engineers and managers was noted in
terms of being subject to any form of CoP, personal ethics or moral values; on the latter,
managers ranked highest (Appendix 6). With the premise that such ethically questionable
behaviour as IDR occurs at the hands of managers, we can logically argue that rationalisation of
the decisions is based on internally inconsistent beliefs and preferences, i.e. between what they
believe in terms of a CoP and what they actually do (Kahneman, 2011).
28
Instrumental Rationality shifts Reference Points
In defence aviation, on declaration of war, “serviceability of 20 aircraft raises from 2 to
20…dramatic effect”17.14 (on rationalisation). In the nuclear industry, “At the design stage…safe
guards/levels of safety are challenged regularly as they are often conflicting with time and
costs”19.3. In the heritage buildings industry, a wide range of conflicting normative documents
and legislation challenges rationalisation of planned action20.2. These examples are typical of
decisions made by managers that focus on abstract goals.
RQ3 Conclusion
IDR occurs due to instrumental rationality, which when intentionally committed reflects amoral
calculation, in turn reflecting internally inconsistent values. This was supported by an
abundance of evidence amongst the respondents, some reporting their experiences throughout
their working lives. Engineers use epistemic rationality to defer decisions until a critical mass
of information is available, framing decisions in terms of a safe and functional system. In
contrast, managers use instrumental rationalisation, they expedite decisions with the minimum
available information, and frame them in terms of an abstract goal.
4.4 Research Question 4; How do the meliorist and panglossian models manifest in
organisations’ decision management?
It was possible to identify whether a meliorist or panglossian model of judgement was
dominant within organisations.
How is engineers’ judgement coordinated?
In larger organisations, lower-ranking engineers/technicians are subject to judgement
coordination via meliorist procedures; “it’s easy to persuade low-ranking engineers to make a
decision if they’re provided with a check-list…a belief that they then understand the risks…the
person feels ‘comfortable’…results…may reduce tension in a committee”10.15. The easing of
cognitive strain (Kahneman, 2011) “…undermines or inhibits meta-cognition.”10.17. In moving
beyond the safe confines of unambiguous procedures, engineers may be able to “wrangle with
complex decisions” if adequately engaged with the organisation’s mission; a “…compromise
would have no associated cognitive strain if justification from management is provided” 19.13. A
‘pure’ manager21 explained how from a management perspective, measures were implemented
to minimise possibility of deviance.
This shows that the meliorist model is dominant in the larger organisations, and that formal
culture is used to manage it.

29
At a more senior level, tacit knowledge may be a benefit of experience15.3, 16.4a, and “within a
disciplined and controlled framework can allow engineers to gain early insights into the
magnitude of risks posed by a project under development”16.4c. Subject to an organisational
context and industry, engineers1.10 are occasionally allowed to boycott practices or designs
based solely on intuitive judgement. In a large utilities organisation however, a manager
reports, “…loss of experienced practitioners…and number of audits required to maintain
accreditation…” has reduced the opportunity for intuitive judgement21.3a.
The most concise summary of the role of instinct for engineers and was that it allows engineers
to arrive at an initial “rough order of magnitude” before being “’calibrated’ using formal more
objective analyses…subject to peer review”16.4a. Sound intuitive judgement is developed within
a “controlled framework”16.5c
This suggests the discipline of the engineer is experientially developed to facilitate decision-making
beyond the confine of typically meliorist procedures.
Procedural Overburden, an antecedent to NoD
Open coding identified a concept we shall refer to as Procedural Overburden.
Operators/engineers tend to make informal modifications to formal procedures that are
otherwise erroneous or overly complex to be practical in application. Incidences reported by
engineers in large organisations were:
“The written method for the task is incorrect...the ‘better way’ soon becomes the norm” 2.4-6
“…policies and procedures may be detached from the process…lengthy procedures are more
likely to be deviated from”4.15
“…approved documented procedure at odds with informal, adequate procedure that is more
efficient at the ‘coal face’, possibly creates tension”19.10. This is in spite of the culture at the
functional level in the nuclear industry that to compromise safety by cutting corners is
“taboo…and not communicated within a group”19.3.
These cases feature meliorist modelled procedures, as Kahneman (2011) argues. However, in
contrast, one interviewee25 stated an example of a procedure used for the potentially
complicated aircraft servicing that drew its user’s attention to the main responsibilities and the
competence of the user was usually sufficient to extend any of the elements of the procedure,
thereby not subjecting the user to overburden. This departure from the typical meliorist
approach suggests that in the largest organisations, it is possible to use alternative models
successfully that also reduce the possibility of overburden.
The overburden concept described here is very difficult to separate from the culture that
appears to uphold it; in fact, it is defined by contrasting formal and informal procedures, both
manifestations of the strength of either formal or informal culture.
RQ4 Conclusion
Intuitive judgement is considered a negative influence for all but the more senior engineers, yet
paradoxically, the standard meliorist approach to reducing non-normative judgement may
increase it:

30
1. Unintentionally via Procedural Overburden
2. Intentionally by subversive management who exploit the meliorist procedures
In large organisations, intuitive judgement as a basis for decisions may be genuinely refrained
because of scalability issues and impediment to sustainable competitive advantage, i.e. decision-makers
who follow prescriptive procedures are easier to replace than decison-makers whose
decisions are based on a high degree of experience. However, a subversive management may
elicit engineers’ intuitive judgement for their own ends.
4.5 Research Question 5: Does organisational structure, size or culture have any bearing on how
effective the organisation is at avoiding errors?
This RQ requires synthesis of the data from previous RQ’s. Dysfunctional conflict is caused by
IDR but is discussed here because it is a sociological and cultural issue.
Dysfunctional conflict (Gibson et al. 2012) may be linked to informal networks; “nepotism and
cronyism” is an issue, as reported by three engineers12.1,13.2,17.7, and one who is now a
manager15.7. Conversely, an SME owner reports informal networks are key to building the trust
that maintains the reputation of the business3.9.
In the nuclear industry, independent accounts describe incidents that prompt inadequate post
event analysis16.5,19.19. Despite the “no blame culture”19, latent risk remains where it could have
been eradicated, because “blame being attributed to lowest rank”19 displaces necessity for any
remedial action following the incident.
One internal consultant manager/engineer describes his organisation’s method of isolating risk
via their corporate level strategy by maintaining the capital structure of a conglomerate4.1 that
effectively treats each strategic business unit (SBU) as a “quasi-autonomous”4.2 SME. In
particular, each SBU’s Director’s decision errors are reduced because the available capital
influences risk-averse behaviour4.6.
Examples of intuitive decisions being eradicated in industries21 by the imposition of red-tape
and regulations, “No freedom to tolerate risk beyond the formal procedures…”8.10. Conversely,
one industry is unique in that deviation from the norm of the parent industry is necessary and
accepted practice, though justification with respect to the appropriate normative guidance is
referred to with a view to satisfying any expert witness.20.2-7
RQ5 Conclusion
Nepotism and cronyism is a means of instilling an informal culture. Formal culture in large
organisations can be inconsistent with informal culture, the latter may be stronger in some
cases, and this may result in NoD occurring. Decision models are upheld by the formal culture
in organisations but the informal culture may facilitate abuse of their purpose for the ends of
managers to induce IDR.
The result of the tension created by IDR is dysfunctional conflict from the perspective of those
engineers subject to it.
Summary of Findings

31
Some success stories of reducing decision errors were encountered in the research, but the
main focus has been the dysfunctional examples, most of which appear to be based on poorly
managed culture and inappropriate structure.
RQ1 - NoD was reported as occurring in large organisations. The antecedent confusion of
experimental and operational technology was identified in two critical incidents, in common
with the Challenger case.
RQ2 - Superficially, engineers appear more risk averse than managers, but RQ3 suggests that if
we dig deeper, the aversion to risk is due to using epistemic rationality to solve problems only
as quickly as the evidence presents itself such as requiring results of complex calculations.
Instrumental rationality may be formally applied, tracing shifting organisation goals. Managers’
amoral calculation is the most hostile form of instrumental rationality, resulting in IDR, an
intentional antecedent of NoD.
RQ4 - Procedural Overburden occurs due to misguided meliorist-type attempts to optimise
decisions and is a non-deliberate antecedent to NoD. This is a feature of large organisations,
incidentally, those with the greatest interest and emphasis in reducing errors.
RQ5 - Organisational size, structure and culture – formal or informal – have a bearing on the
effectiveness of averting error-based decisions. A common factor here is that dysfunctional
conflict results from managers’ dismissal of engineer’s protests against practices that induce
residual risk. Nepotism and a strong informal culture are the reported bases of this.

32
Chapter 5: Discussion
Introduction
This Chapter synthesises the issues raised in isolation in each of the RQs and discusses the
causal explanations for NoD.
5.1 NoD’s association with culture and structure
The present findings suggest that NoD occurs in contemporary engineering organisations across
a wide range of industries – often the most stringently regulated, and generally in those that are
large, or complex in terms of culture or structure. The findings also suggest that NoD may be
induced by any of three failures:
a. Intentional control of the decision-maker’s psychology using a meliorist approach, with
non-normative behaviour as a consequence – Procedural Overburden16.5c,19.19
b. Amoral calculation of managers that prioritises temporal and financial goals over
engineering specification – IDR2.4,16.2d,19.22
c. Confusion of experimental and operational status of technology by non-engineering
stakeholders16.2e,16.3,25.7
These failures are facilitated by relative weakness of formal culture, for example:
1. Nepotism and cliques uphold an informal culture2.4,13.2 in the context of a
bureaucratic formal culture.
2. Organisations with de-centralised decision-making – disengaged or with conflicting
internal interests to engineering departments2.4,5.21
3. Organisations whose formal culture is “no blame” where a safety incident occurs,
but informally, management places the blame on a sub-ordinate because it is
‘cheaper’ than rectifying the procedure’s weaknesses19.19
In isolation, these factors may not be directly causal of NoD. However, the failure to adapt
culture/structure to environmental changes may be (which may have called for procedure
modification, as in 3 above) in contrast with the smaller organisations that can resolve
environmental issues rapidly22.4 if their decision-making is centralised. There were examples in
the findings where no critical incidences were identified, and the management/engineering
objectives were concentric.
A formal culture of instrumentally rationalising simply reflects the nature of the problems
encountered by managers, and this may form equilibrium with engineering interests in the well-balanced
organisation. However, when instrumental rationalisation occurs informally, due to a
weak formal culture, this may result in amoral calculation, therefore it is the strength of the
culture that is in the spotlight. It is no coincidence that the present conclusion concurs with
Vaughan’s (1996).
5.2 How informative were RQ2’s findings concerning risk tolerance?

RQ2’s quantitative analysis explicitly suggesting engineers are more risk averse than managers
was considerably illuminated by RQ3. Trained to solve engineering problems, engineers are
concerned with epistemic rationalisation, where the evidence exists and needs to be processed
accurately. Those with management experience may appreciate that the requisite information
required for the abstract problems associated with management may never be available, and
therefore a necessity to ‘satisfice’ (Bazerman, 2009) may be justified, particularly when the goal
induces instrumental rationality. From this standpoint, we can argue that instrumental
rationality invites inclusion of errors, and that error are more likely to be a feature of
management decisions. An interesting finding from the data that upholds the manager-instrumental
33
rationality link, is the manager’s tendency to govern the attitude to risk,
concealing it unless absolutely necessary, exemplified by the quote, [managers’] “risk appetite is
signalled by remedy, or not, of non-conformities”8.11
Risk aversion of engineers is a stereotype that simply reflects the typical engineer’s professional
responsibility based on epistemic rationality. However, engineers with management experience
may have an advantage over either in optimising risk13.13-18. The epistemic nature of the
problems engineers face means they do not have the liberty to create informal structures in
order to create short-cuts without compromising the engineering definition of normative.
5.3 Inequitable Distribution of Responsibility and Dysfunctional Conflict
Figure 5.1 illustrates the consequences of residual risk in each of two possible conditions
described by an interviewee. In the case of an accident occurring, the engineers may bear the
brunt of recriminations. Where an accident does not occur, the risk may be perpetuated;
Thiokol - Biosjoly’s employer in the Challenger case - continued to win contracts after the
disaster, for example (Vaughan, 1996). Biosjoly’s career and mental health were effectively
ruined by the nervous breakdown he suffered some two years after the Challenger disaster, and
the futile legal battle between him and Thiokol. Here, an established theory exists to support
the IDR model, inequity in respect of the psychological contract (Conway and Briner, 2005),
which leads to contract breach or violation. The lack of neutrality associated with inequity as
experientially-based phenomena is fraught with testability issues and is contingent on the
disposition of the subject, but we can at least identify how dysfunctional conflict manifests in
either condition.

34
Project residual risk
induced - IDR of
managers to
engineers
Accident DoesOccur
Accident Does Not
Occur
Figure 5.1. The dilemma of engineers subject to IDR
Engineers found in
breach of professional
obligations2.4
Risk Justified by
Management with
view of tension as
functional conflict2.4-5
This focus on the perspective of the engineer illustrates how the unintended consequences of
IDR, viewed by managers as functional conflict in the absence an accident, reinforces managers’
risk-tolerant behaviour. Managers introduce errors into subsequent decisions in a form of path-dependency
providing residual risk is not realised. Amoral calculation is a subversive form of
instrumental rationality and would only be compatible with an unsustainable formal
organisation culture, and therefore can be argued to non-normative, upholding the ‘errors’
definition.
Including values in the term normative adds confusion and explains why the panglossian
position has little rigorous support, but a reasonable hypothesis in practice that engineers’
typically employ values of professionalism and a ‘vocational’ utility has been realised in Section
4.3 that reports engineers’ resistance to IDR with professional integrity.
Kahneman’s (2011) claim that large organisations are more effective at avoiding errors is based
mainly on theory. Yes, it may be more appropriate for large organisations to employ the
meliorist approach as he advocates, but this is easily confounded by the variability of the
organisational dimension of culture on which the meliorist procedure’s effectiveness relies. The
findings in section 4.4 that resulted in the Procedural Overburden term uphold our counter-argument
to Kahneman’s claim.
5.4 The Great Rationality Debate in the organisational context
Meliorist Approach Evaluated
RQ4’s findings superficially supported the application of prescriptive meliorist models in
organisational practice to manage decision errors by reducing cognitive strain in large
organisations, as per Kahneman’s (2011) claim. Despite these good intentions, however, such
procedures are no guarantee of reducing errors. In fact, where explicit meliorist policies on

decision-making exist, they are open to abuse by management who may exploit the structure’s
logic to place unwitting engineers in a position of IDR; the ‘fall guy’10. The findings included a
large organisation where no negative side-effects of meliorist procedures were reported,
suggesting that the effectiveness of a meliorist approach may be contingent on culture and
structure, because there was no informal influence of an operations department18.
The incidence in meliorist procedures of Procedural Overburden was common, where engineers
make pragmatic corrections2.6 to procedures in order to complete their task. What is interesting
is that this was the case in organisations in the most highly regulated industries such as nuclear
and the military, where the most mechanistic and bureaucratic cultures and structures were
employed. One interviewee highlighted this early in the data collection6.10. In Procedural
Overburden, the procedures’ correction could be described as the panglossian definition of
normative. Made in isolation, these corrections are disconnected with the organisation’s overall
mission, due to a weakness of the organisation’s culture, structure and communication2.8-12.
In one critical incident24.12, after an accident, Procedural Overburden was a deliberate
management method of inducing IDR, making responsibility for meeting engineering objectives
safely with inadequate resources ‘the engineer’s problem’, transferring management’s liability.
This was a relatively old example reflecting a different era of employment legislation.
Nevertheless it demonstrates amoral calculation as a subversive but common example of
instrumental rationality, abusing a meliorist model of procedures.
35
The conclusion from these examples is that the meliorist model is not the infallible approach
some of the literature would have managers believe.
The Panglossian approach modified
The thrust of the ‘humans good (panglossian), or not (meliorist) at decision-making’ arguments in
the great rationality debate features only meliorist control of the decision-maker’s psychology
as though the procedure is the only manageable independent variable. We have found that
sound decision-making exists in organisations where organisational and engineering objectives
are concentric3, against copious evidence of meliorist procedures organisations where
objectives are eccentric in section 4.4. In the current terms of the debate, the values that uphold
the successful decision model are errors (meliorist), or not observable enough to be repeatable
(panglossian). However, the findings in section 4.3 show values such as integrity are in fact
tangible, so their engagement via a decision model could be termed coalescent, reflecting the
coalescence of both management and engineering values/objectives. This would result in a
dually-inclusive definition of normative, which has previously been subject to dispute. From
this standpoint, the independent variable becomes that of culture, where a strong formal culture
can centralise the values. Our modification then, can be comprehensively coined as a culture-contingent
coalescence model. Although successful applications of meliorist models have been
identified18 as a ‘snapshot’, this may not endure in a changing environment, and that is why
procedures that are not amended result in NoD2.4,19.19. The danger is, that as organisational
circumstances change and the tension created between engineers and managers values
becomes greater, and it must be accepted that the dominant power of management is likely to
have the monopoly on definitions, such as ‘normative’.
The clear message is that where possible, formal culture should be of primary interest,
centralising interests of both engineering and management, after which a dually-inclusive

definition of normative will follow, and the coalescent decision model. As long as engineer’s
interests are respected, dysfunctional conflict from their perspective will be averted also.
Naturally, we accept that this may not be possible in all types of organisations and industries,
and may explain why the prevalence of critical incidences of NoD were in organisations in the
nuclear industry or similar, where explicit stringency of procedures are a mandatory function of
the industries’ image6,16,19. An exception was the Oil and Gas industry, where the Health and
Safety culture is relatively less mature5 but is taking Health & Safety increasingly seriously,
following Deepwater Horizon.
36
How viable is the coalescent approach?
As Klein (2011) indicated, a modal and normative response may be elicited from competent
persons following a broader, less detailed procedure that permits a degree of discretion and
therefore engagement with the task. This is contingent on a strong culture and appropriate
structure, but is upheld by a critical incident25.
Engineers with tacit knowledge to maximise the coalescent approach possess a high degree of
human capital that may compromise the durability of an organisation’s competitive advantage.
From the durability perspective, a meliorist approach that provides a decision output consistent
with the organisation’s policies, relying more on explicit knowledge, is preferable by
management21.
In conclusion, the coalescent approach is viable, providing a strong, humanistic culture engages
the decision-maker, and ensures instrumental rationality does not atrophy into amoral
calculation, with the caveat that these features will require significant human capital and in turn
compromise durability of competitive advantage. These characteristics, according to the
findings, are more representative of the typical SME.
Conclusion
The findings contribute to the existing literature in two ways:
 Kahneman’s theoretical assumption of the large organisation’s ability to eliminate errors
has been successfully challenged;
 The Great Rationality Debate’s definitions have been extended from the current
descriptive model to a transformational model, i.e. the panglossian approach to decision-making
has been expressed as coalescent, where the organisational context can be
optimised for decision-making without prescriptive models.
The definition of normative in the organisational context can be used to identify potentially
problematic organisations, and by contrast, those that are unlikely to exhibit dysfunctional
conflict, i.e. those with concentric engineering and management. This concentricity may be
upheld by a strong formal culture in organisations, the finding’s suggest that nepotism may
result in informal culture.

37
Chapter 6: Conclusion & Recommendations
In this chapter we draw some conclusions about the impact of the findings on the research
issues and questions presented in the opening chapters and then make some recommendations
that will aid stakeholders who may wish to avoid, diagnose or possibly implement remedial
change in organisations exhibiting the issues identified. There are also some reflections on
what has been learned from undertaking the project.
6.1 Conclusion
 The rationality debate has been discussed and positive support found for Klein et al.’s
panglossian approach. Kahneman et al’s. meliorist approach is prone to procedural
overburden or abuse by informal culture.
 The inadequacies of the debate’s terminology have been addressed for compatitibility
with the organisational context - coalescence - which enables focus on the professional
obligations of engineers to eliminate dysfunctional conflict.
 The concept of normative in the research context straddles a combination of
engineering regulations and organisation mission/vision, which should be concentric if
NoD is to be averted, as NoD is a current issue in large organisations.
 A more accurate description of a decision ‘error’ in terms of the research is ‘assessment
of a risk being influenced by factors not contiguous to it’ – the factors are normally
organisational interests, which may occasionally be ‘acceptable’, such as in the
declaration of war.
6.2 Recommendations
Recommendation to engineers and managers: Consider the concentricity of professional
and organisational interests
Why? The concentricity of engineering and organisational goals is necessary for the stability of
the organisation in order that IDR is eliminated. This is demonstrated conspicuously by the
critical incident12 that reflected an organisation’s transition from a nationalised monopoly to a
privatised listed company. Static, professional obligations may become increasingly at odds
with the organisation’s goals if circumstances deteriorate, tension may result in inequity and
psychological contract breach or even violation. The latter prompted one interviewee3 to take
up the management and engineering responsibilities by establishing his own organisation.
Recommendation to job-seeking engineers: Recognise weakness of formal culture in large
organisations where managers may exploit informal culture for their own means
Why? The weakness of a culture may also signal the possibility that engineering and
organisational interests may not remain concentric. Nepotism, corruption and informal
networks may uphold a dysfunctional culture. Engineers are hamstrung by their obligation to
observe formal normative codes, whereas managers may not be; they can use informal
structures and culture to subvert the engineers’ obligations for their own ends.

38
Recommendation to managers: Recognise organic vs. mechanistic cultures and the
relationship with the organisation’s activity
Why? Organic culture may be associated with experimental technology, and mechanistic,
operational technology. The confusion of technology’s status is an antecedent to NoD and a
workforce working within a melioristic model of procedures in a mechanistic culture may not
pay due regard to experimental technology.
Recommendation to junior engineers: Do not take for granted that following a
prescriptive meliorist procedure abrogates personal responsibility
Why? Procedural Overburden is usually unintentional and a result of procedure author’s apathy
rather than amoral calculation. However, sometimes the procedure is exploited to induce
cognitive ease and acquiescence in making decisions that favour the organisation’s interests10,
inducing IDR.
Recommendation to managers: Organisations should be aware of the optimum
environment for respective decision models
Why? The meliorist approach requires a strong formal culture and is preferable for mechanistic
cultures. The coalescent approach is preferable where decision-making is highly centralised,
usually in smaller organisations where a high degree of autonomy of decision-maker also
reflects a high degree of human capital, limiting the competitive advantage.
Recommendation to all professionals: Be aware of ‘recruitment’ by informal networks and
its consequences
Why? In extension to Steare and Stamboulides’ (2014) recommendations, awareness of biases
may be specifically those biases that are propagated via informal culture and networks. If any
such culture or network fails, only a professional’s formal reputation may remain.
6.3 Reflection on Learning
Culture emerged as possibly the most potent element of the organisation, and the research’s
original intention to focus on the more ‘interesting’ aspects of individual decision-making,
heuristics and biases became ancillary. Indeed, the message that all engineers with no
management experience might take home from the research is, as a professional, one cannot
afford to ignore the wider sphere of organisational influence that happens to fall outside one’s
immediate interest.

39
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KAHNEMAN, D. 2011. Thinking, fast and slow. 1st ed. New York: Farrar, Straus and Giroux.
KLEIN, G. 2009. Streetlights and shadows. 1st ed. Cambridge, Mass.: MIT Press.
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41
Appendix 1 – Survey Final Draft
NB. Formatting anomalies a result of the survey tool providers security system
Risk attitudes, risk rationalisation and the normalisation of
deviance
Introduction and Brief
1) Introduction and Brief
"Who are you and what are you doing?"
You may already know me personally, or we may have a connection via a professional group. I am Stephen
Peacock, an Engineer and SME owner currently studying an MBA, writing a final project-dissertation that
requires me to conduct research, including the collection of primary data.
"When do you need me to complete the survey?"
The survey will remain open until the 14th March 2014, but may be closed earlier if the requisite responses
are achieved before. The earlier you can complete the survey the better, because if you volunteer and are
selected to interview, this can be carried out as soon as possible.
"What is the survey about?"
No enterprise can be conducted without some degree of risk. I am examining the attitudes and models of
rationality that correspond with risk taken by individuals in specific roles. The Challenger Disaster (1986)
prompted considerable research into risk; one particular model, the "normalisation of deviance"
(Vaughan,1996), will be examined in detail with reference to contemporary practice in a wide range of
organisational contexts.
"What questions are there?"
The questions are multiple-choice, and cover the following areas:
Page 1 Introduction and Brief - 1 Question
Pages 2-4 Professional role and background - 3 Questions
Page 5 Demographics - 5 Questions
Page 6 Experience of attitudes to risk* - 5 Questions
Pages 7-8 Interview arrangement (where applicable) - 6 Questions
*In this section, you are invited to consider a former (as opposed to current) organisation in the interest of
sound ethical practice.
"How long will the survey take?"

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