The Impact of Blame on Continuous Improvement Models

Continual improvement is vital to business success, and management literature agrees that the
‘PDCA model’ (Plan-Do-Check-Adjust) is the most proper tool for this purpose (Tang
et al., 2005). This four-stage cycle
starts with planning, which is not only a strategic exercise to increase
organisational effectiveness and profit margins
but also a powerful rhetoric tool to convince audiences inside and outside the
organisation that ‘they know what they
are doing’ (Clarke, 2001).

However, as social, economic, political and
environmental contexts become more complex, so does the planning process. Any
potential risks that may prevent the organization from achieving the proposed
objectives that failed to be identified, estimated, or considered properly into
the strategic plans will have critical impacts on the ‘do’ stage where plans
are supposed to be implemented. According to the PDCA model (Johnson, 2002), those
risks are –in theory- identified later at the ‘check’ stage when the
implementers are expected to report the results and give feedback on the process, and finally the feedback is –in theory- used to adjust the
initial strategy, and the planning process starts over again in a spiral of
constant improvement.

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Nevertheless, in practice, right after the ‘check’
stage comes the assigning of blame. What happened? and whose fault was it?
become the centre of attention as failures could generate doubts about the
effectiveness of business management, about individual weaknesses, and could
send the message that “they really do not know what they are doing”. But does
this ‘blame game’ affects the goals that the PDCA model tries to achieve? The
objective of this essay is to analyse through blame literature the reasons that
give rise to blame within the continuous improvement model, and how it affects
organization’s performance.

 

Planning,
Delegation and Responsibility

During the planning process, companies delegate tasks
and responsibilities to be able to address a wide range of issues
simultaneously, because it is an effective way to get things done through the
division of work, and because it allows benefiting
from the expertise and abilities of different actors (Pearce, Robinson and
Subramanian, 1997). According to Hoskisson, Hill and Kim (1993), through
delegation, choices made on behalf of another
commonly result in a better outcome as someone more expert or capable ends up
taking the decision. However, things could always go wrong as ‘zero-risk’ contexts don’t’
exist. According to Steffel, et al (2016), companies use delegation as part of
a ‘blame game’ where delegating choices to others is seen as a way to avoid
responsibility and fault. They argued that people tend to avoid taking risks
that could bring unappealing consequences for someone else, and therefore, anticipating
the possibility of a bad outcome become an important driver of delegation. For
Steffel et al. beyond the economic benefits of work division, what is appealing
about delegation is the possibility to avoid the concern about feeling
personally responsible for taking a poor choice. In fact, Hood (2002)
complements that as delegating tasks
dilutes responsibility it also dilutes blame, and that is tempting for
decision-makers as it relieves them of the burdens of being fully responsible
for taking risks that could end up in failure.

 

But avoiding or limiting blame by reallocating
responsibilities and transferring risk through delegation is not only a
strategy of corporations. Weaver (1986) argued that ‘agency strategies’ for
blame avoidance are also a commonly used
political tactic motivated by the voters’ propensity to be more sensitive to
losses than to gains. In both private and public sectors, poor choices are
likely to have more public salience than the good ones, therefore
decision-makers seem to care more about avoiding blame than getting credit for
positive outcomes. According to Douglass (1992), this ‘negativity bias’ could
be explained by the socio-cultural roots of blame: in modern societies, risk is seen as a secular version of sin and
therefore it is repelled and strongly resisted by people. As consequence,
people are not prepared to take risks, even if those risks could benefit the
organization, because they fear being blamed, which generates an unjustified organizational
aversion to risk.

 

Douglass (1992) also identified a second bias in
society to blame ‘the powerful’. Failure must be able to be assigned to someone
in order to manage and reduce the risk, and according to Douglass, ‘the
powerful’ are usually blamed by ‘the powerless’. But when a decision has been
delegated, who is held responsible for the bad outcome? The person who delegates the decision or the person who
actually makes the decision? According to
Siegel (2014), children can’t be legally held responsible for their actions, so
their parents have to assume the responsibility. Similarly, organization’s power
hierarchies determine who is ultimately responsible for a decision. The person
at the top of the heap has no one else to whom he can pass the buck and hence, Bartling
and Fischbacher (2012) argue that the motivation to avoid punishment is a
strong reason to choose correctly in whom to delegate decision making.

 

In consequence, the PDCA cycle is affected positively
and negatively by the ‘blame game’ since the beginning. On one hand, as Gibson
and Shroeder (2003) highlight, tasks and responsibilities delegation in the planning
stage is not based only on economic efficiency but also on personal concerns,
and therefore organizational complexification and bureaucratization to avoid
blame could end up harming organization’s effectiveness. However, on the other
hand Bartling and Fischbacher (2012) argue that delegation is positive for the
organization not only because of the economic benefits of the work division but
also because in order to avoid blame for failure, people who are most
qualified, experienced and capable to make the right decisions are selected by decision-makers
to reduce the risk of failure (and thus blame).

 

Blame
in the Business Learning Process

Whether the ‘blame game’ during the planning-stage affected
positively or negatively the organization’s performance will later be tested during
the check-stage where both, the process and the results, are evaluated. According
to Murray and Chapman (2003), is in this stage where businesses can improve and
adapt their strategies and methods by learning from past experiences (both
successes and failures), using the feedback as an input to make the necessary
adjustments. This is known as ‘organization learning process’, and it is the
core of organization’s continuous improvement models.

But organizational learning is not about detecting risks
and failures to avoid them in the future. According to Van Dyck et al. (2005), the
process to analyse and communicate errors and risks is critical to improving organizations performance. This
requires a constructive attitude towards failure through what Sitkin (1992)
calls a ‘no-blame organizational approach’ which recognizes that no system is entirely ?awless. For Sitkin it
is necessary to shift away from understanding failure as an individual or group
mismanagement and accepting it as a lesson that contributes to enhancing organizational learning and performance because it will create a trust-environment in which people are
encouraged to provide feedback and information to understand what and why the failure happened. This increases the organization’s
resilience to failure and prepares it to face unknown future risks.

Encouraging the openness and disclosure of failures
and near misses requires a ‘no-blame’ culture within the organization. For Weick
and Stucliffe (2001), reporting is essential to detect failures and near misses
and identify future risks; then debriefing processes are important to obtain
specific details about the failures in order to fully understand them; and
finally all the failure-related information that has been collected must be
incorporated into a ‘story of errors’ that must be narrated from the managerial
levels throughout the organization.

But these process is very difficult to follow. According
to Provera et al. (2010), due to cultural biases, people tend to perceive
errors as a manifestation of individual weaknesses or lack of capability and
therefore they try to avoid it through the ‘do it first, fix it later’ approach
to cope with problems. In the language of continuous improvement, errors are
classified as ‘non-conformities’ (major or minor) and the number and severity
of these affect the certifications and
awards granted to companies. This is why, according to Vaughan (1999),
employees and organizations devote big efforts and resources to prevent errors
from being visible, hiding risks and covering up fails from internal and
external audits.

Hood (2007) and Vince and Saleem (2004) agree that the
real problem is that blame discourages communication and discussion between
colleagues or supervisors, and consequently, many risks and dangers remain
hidden, and other people won’t be prepared to face similar situations in the
future. Blame affects negatively the check-stage as people will not be willing
to report errors and risks, and thus it also affects the adjust-stage because
it will be biased since the adjustments will not reflect the real needs for
change and redesign of the original plans. Additionally, Tucker and Edmondson
(2003) highlight that blame disempowers people to make decisions in favour of the
organization because they prefer to stay in the comfort zone following strictly
what was planned and not taking risks that could alarm managers or superiors.

However, blame remains appealing to business as a
motivational instrument. Daley (2015) defines performance evaluation as the
periodical assessment of individual contributions to organization’s goals in
order to reward those who have met their
individual responsibilities and to
identify those who haven’t met their goals to develop action plans and
adjustments to ensure they will be achieved in the future. According to Daley
(2015), results from the check-stage are used as inputs to make objective
judgements and decisions related to promotions, demotions, retention, and
payment, as well as a relevant tool to give feedback to workers about their own
performance and identify training needs. Crant and Bateman (1993) point out
that just as organizations use reward systems to motivate their employees to
improve their performance, the allocation of blame is used to motivate
employees to not make mistakes and improve their performance. However, benefits
of blame in performance are still unknown as the impact of credit and blame on
good and bad performances remains relatively unstudied.

 

Conclusions

The ‘Plan-Do-Check-Adjust’ model for continual
improvement, critical for business success, is not flawless as risks can’t be
completely eliminated. Concerns about blame avoidance for (real or potential)
failures interfere with the process of
continuous improvement positively and negatively, affecting also the final
outcomes. During the ‘plan-stage’, tasks and responsibilities are delegated following
motivations other than those that economics and management literature usually
give related to the division of work to capitalize
people’s skills and potential. Avoiding blame is an important driver of the
delegation process because it dilutes the responsibility of taking risks and be
accountable of fails. On one hand, this has negative consequences on the organization’s
efficiency as it becomes more bureaucratic and complex. But on the other hand, it
also has positive consequences because decision-makers who want to avoid -or
dilute- blame choose with greater responsibility capable and appropriate people
in whom they can delegate responsibilities. At the end, more qualified people
end up taking risks and making better decisions for the organization.

Later
at the ‘do-stage’ and the ‘check-stage’ blame becomes again an important driver of people’s motivations. In
order to avoid blame, people tend to avoid risky decisions, even if they know
that they could improve the performance of the organization. Then, avoiding blame
becomes a threat to improve business efficiency. Additionally, blame affects
internal communication because people are not willing to report failures or
risks for fear to be perceived as individual weaknesses. People prefer to deal
with them on their own, preventing organizational learning. However, in a
carrot and stick system, rewards work like carrots and blame like sticks,
making people try their hardest to avoid mistakes and improve their
performance.

In
consequence, the ‘adjust-stage’ becomes sense-less as the feedback used as
input to adjust the initial plans is completely biased by blame. Blame-free
approaches might have beneficial consequences for the success of continuous
improvement, however, blame has proved not to be entirely negative for
organizational success and even carries certain benefits. Thus, organizations
need to find a find a balance between people not taking the risk of making the
right decisions for fear of being blamed, and people not striving to avoid failures
as no one will blame them for it. A matter of moral hazard vs adverse selection
on which it is worthwhile to deepen knowledge.