Individual and organizational decision-making
DDBA 8560 - Seminar in Healthcare Managerial Decision Making
Walden University
2022
Individual and organizational decision-making
Individual and organizational decision making overlap because organizations
are made up of individuals (Shapira, 1997). However, prior research differ in the way
they treat individual and organizational decision making. Daft (1998) described
individual decision making in two ways: rational approach, which guides the
individuals’ decision making processes, and bounded rationality, which describes
how decisions are made with limited time and resources. Daft listed eight steps in the
individual rational decision making process: (1) monitor the decision environment,
(2) define the decision problem, (3) specify decision objectives, (4) diagnose the
problem, (5) develop alternative solutions, (6) evaluate alternatives, (7) choose the
best alternative, and (8) implement the chose alternative. Daft explained that the
rational procedure works best in programmed decisions, where problems and
alternatives are clearly defined and the decision maker has enough time to collect
complete information. Bounded rationality on the other hand, describes the idea
that managers work with limited time and resources.
Organizational decision making, as studied in lab experiments, differs from
individual decision making in terms of ambiguity, longitudinal context, incentives,
repetition, and conflict (Shapira, 1997). In organization decision making, information
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and preferences are unclear and participants in decision making are part of an
ongoing process. Additionally, incentives and ramifications are long lasting,
decisions, such as a loan officer reviewing application for a loan, are repetitive,
and conflicts dealing with power considerations and nature of authority relations,
are pervasive. Shapira argued that those additional dimensions, ambiguity,
longitudinal contexts, incentives, repetition, and conflict, do not occur in individual
decision making.
Simon (1976) described the relationship between the individual and the group in
decision making. He noted that the organization takes the individual’s autonomy,
replaced with “organization decision-making processes”. The organization decides,
for the individual, his function and duties, and people who have power or authority
over him. The organization also limits his choices as needed for coordination with
others in the organization. Simon also described approaches organizations use to
influence individual decision makers within the organization: authority,
organizational loyalties, push for efficiency, advice and information, and training.
2.1.4 Decision Models
There are many decision making models, some, with overlapping paradigms.
Rationality, logic and reasoning, are prominent features in decision models. Huber
(1981) summarized four decision making models: Rational, political/competitive,
garbage can, and program. In a Rational Model, organizational decisions are based on
organizational units using information in a rational way. In the Political/Competitive
Model, organization decision are made by units, using strategies and tactics, to influence
decisions that are favorable to themselves. The garbage can model
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displayed the intersection of solutions, problems, and opportunities. This model was
useful in interpreting choices in certain organization settings. The program model
emphasized the effect of programs, such as standard operating procedures and group
norms, had on organizational decisions.
Similarly to Huber, Choo (2001) discussed the idea of rationality in decision
making. Choo stated that organizations adopt one of the following, depending on levels
of uncertainty: Bounded rationality, Process mode, and Political mode. Goal and
procedures are clear in bounded rationality: there is a standard set of operating
procedures, which uses search and decision rules and routines of the organization. In the
process mode, there are clear goals and strategies, though the methods and alternatives
might be unclear. There are dynamic processes for search interruptions. In political
mode, goals are disputed by multiple groups. Each group is clear about their preferred
alternative. In this mode, groups bargain, vying for their own interests.
Sathyamoorthy (2014) also described decision making models in terms of
rationality. His model, which described the rational model, bounded rationality
model and intuition model, are similar to Daft’s model provided earlier (Section
2.1.3). The addition, intuition model, is often used when decision makers do not have
enough time to gather information, and so make decisions based on instinct or gut
feeling. Sathyamoorthy noted that intuition decision making’s effectiveness is
dependent on the decision maker’s experience.
Daft (2008) warned that most organizational decisions are not made in a
logical, rational manner. Most decisions do not begin, as he and Sathyamoorthy
(2014) described, with the analysis of the problem and then systematic analysis of
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alternatives, followed by implementation of solution. Daft expressed that “decision
processes are characterized by conflict, coalition building, trial and error, speed and
mistakes.” He also explained that since individuals make decisions, but organizational
decisions are not made by individuals, decision making will almost be done in
collaboration. In agreement with the notion of collaboration, Rogers & Blenko (2006)
described critical roles individuals play in the decision making process: Recommend,
Agree, Input, Decide, Perform. People playing the recommend role are involved in
proposing, gathering information and analyzing. Those who “agree” have Veto power
and can vote yes or no. Those who provide “Input” are consulted on decisions and
those who “Decide” is the formal decision maker, accountable for the decision. Those
in the “Perform” role are the people responsible for executing the decisions. Table 1
displays the Critical decision making roles. In parentheses are the terms, changed for
clarity, used in the information gathering interviews (see Section 3.2).
Table 1 Critical decision making roles as identified in "Who has the D?"
by Rogers, Paul, and Marcia Blenko
Role Description
Recommend People in this role are responsible for making a proposal, gathering
(Proposer) input, and providing the right data and analysis to make a sensible
decision in timely fashion.
Agree Individuals in this role have veto power – yes or no – over the
(Approver) recommendation.
Input These people are consulted on the decision. Because the people who
provide input are typically involved in implementation,
recommenders have a strong interest in taking their advice seriously.
Decide The person is the formal decision maker. He or she is ultimately
(Ultimate accountable for the decision, for better or worse, and has the
Decision authority to resolve any impasse in the decision-making process and
Maker) to commit the organization to action.
(Perform) Once a decision is made, a person or group of people will be
Executor responsible for executing it. In some instances, the people
responsible for implementing a decision are the same people who
recommended it.
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Some researchers caution against the use of decision models because they are
prone to errors. Sutcliffe and McNamara (2001) studied the extent to which decision
makers used prescribed decision practice, organizational decision making procedures,
for important decisions. They discovered that decision makers were more likely to
use prescribed practice for important decisions, for known decision targets, and when
the decision maker was a part of a larger unit. However, reliance on prescribed
practice fostered stability in decisions and negatively affected future judgment due to
complacency.
Christensen & Knudsen (2010) described two types of errors decision systems
can be vulnerable to: Type I errors of rejecting superior alternatives and Type II
errors of accepting inferior alternatives. They explained that hierarchical structures,
where proposals need to be approved at different levels, are less likely to be
vulnerable to Type II errors of accepting inferior alternatives. However, flat
organization structures, or polyarchies, where proposals are approved by decisions
makers in parallel, tend to be less vulnerable to Type I errors of rejecting a superior
alternative. The authors explained that choosing the best structure to effectively
minimize Type I or Type II errors, is the core of designing decision making
organizations.
Hammond et al. (1998) described psychological traps, such as anchoring and
status quo. Anchoring is the idea that the mind gives disproportional weights to the
first information it receives. Hammond et al. advised viewing problems from different
perspectives and thinking through problems before consultation to overcome
anchoring. The status quo trap is making decisions based on biases towards normative
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or standard decisions. To avoid being too comfortable, Hammond et al. suggested
identifying other options and using them as counterbalances. For all psychological
traps that hinder decision making, one should develop tests into decision making
systems, which can expose errors in thinking. The proceeding section describes
relevant literature regarding decision-making in healthcare.
2.2 Decision-making in Healthcare
In the modern healthcare system, many different decision-makers interact to
care for patients and manage operations. The term healthcare describes a range of
activities which can include, but is not limited to, any of the following: administration
of a drug/treatment, psychological assessment, physical examination of a patient,
services provided by allied health disciplines (Guardianship and Administration Act,
2000). This review focuses largely on hospitals. Relevant research about decision
making in healthcare are sparse. The majority of the research related to decision
making in healthcare were specific to clinical decision making. Some discussed
shared decisions between doctors and patients, and others discussed optimal tools for
making clinical decisions such as diagnosis. Clinical decisions are discussed in
Section 4.1.1 and will not be covered in this chapter. The remainder of this section
discusses complexity and structure as it relates to healthcare, and compares
healthcare to other industries.
Many health research initiatives consider the complexity and challenges of
the current system. Kuziemsky (2016) reviewed challenges with traditional decision
making in healthcare and provided a framework, Complex Adaptive Systems (CAS),
to support healthcare management. CAS displays emergent behaviors and nonlinear
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properties. Kuziemsky stated that although there is a push to transform healthcare
organizations, attempts may cause unintended consequences. He provided an example
describing the introduction of Health Information Technology (HIT), an attempt to
reduce medical errors. Studies suggested that HIT caused more medical errors.
Kuziemsky argued that in order to reform the healthcare system, thorough systems
understanding of concepts and interrelations of healthcare must be known.
Doebbeling (2011) summarized strategies for “transformational” change in healthcare
and also suggested the use of complex adaptive systems to enable organization
redesign. He argued that CAS will allow integration of health information, create
continuous learning organizations, and allow the development of appropriate
measures and incentives.
Some studies consider the implications of hospital structure on patient outcome.
A study of organizational structure (Zinn and Mor, 1997) explained that structural
variables (see Section 2.1.2) and medical staff levels served as predictors of patient
outcome and quality of care. They found that higher volume and expenditures, along
with formal coordination between medical staff, nursing, and administrators were
associated with lower mortality. There is no consensus on the effects of structure on
patient outcomes. Several studies suggested that more rigid controls, such as
centralization and coordination, appear to be associated with better outcomes in hospital
setting (Longest, 1974; Shortell et al., 1976; Flood and Scott 1978, 1987; Shortell and
LoGerfo, 1981; Knaus et al., 1986). However, some research suggests that having a more
horizontal structure, which allows for better communication, is
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more effective (Teresi et al., 1993). Zinn and Mor (1997), advised that more
studies should be done on measures of patient outcomes.
Gaba (2000) described health care, particularly hospitals, as high-hazard
industries and conducted an extensive survey comparing hospitals to other high-
hazard industries. He defined high-hazard industry as those with activities that can
maim or kill. He explained that healthcare was complex due to the inherent
complexity of humans. He also suggested that medical technologies and healthcare
structure add to the complexity. With regard to centralization, Gaba argued that non
healthcare industries, such as the Navy under strict authority from operations, are
centralized. The healthcare system, with hundreds of thousands of doctors’ offices,
are decentralized. He argued that even consolidated hospitals were only centralized in
business operations and not clinical affairs. He described differences with regard to
regulation, training, and learning. Other industries were highly regulated with strict
rules and penalties for not following those rules. Healthcare, with respect to patient
care, has little and inconsistent regulation. Gaba described the intensive training,
which include simulations, in industries such as aviation. Though extensively
educated, Gaba argued that personnel scrutiny in hospitals were lenient. With regards
to organizational learning, Gaba described high profile, independent and capable
organizations, such as the National Transportation Safety Board – NTSB, role in
investigating causes of accidents. He argued that healthcare on the other hand, had
weak and mostly local systems for investigating and reporting adverse events.
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2.3 Summary
This chapter reviewed areas of research in organizational decision-making and
healthcare decision-making. Organizations are decision-making systems and should
thus be analyzed with their underlying decision processes. We found that rationality
form the basis of decision making, and many decisions models, depending on
different contexts, utilize rationality in their paradigms. We identified prevalent
themes, complexity and structure, in organizational decision making, and compared
hospitals to other high-hazard industries, using those themes. The following chapter
describes the methods used in this thesis.
