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| dc.description.abstract | Research on decision-making in lean environment has not been studied enough, and that inspired us to run more precise
investigation in that area. Nowadays, with the implementation of lean in numerous companies all over the world, it is
important to understand not only the truisms of lean, but also what impact does it have on sub processes of activities of
the organization.
As it is known, decisions are made by human and that means those decisions are influenced by many human factors. One
of those factors is biases and framing effects, that had been closely studied by Noble prize winner Daniel Kahneman and
his co-author Amos Tversky. They studied those effects from a point of view of economical psychology, yet not going into
details. We took their work as a basis for our study of human biases and decision-making under uncertainty in off-shore
construction.
In this research, we try to take a closer look into three theories (lean planning, the last planner system and decisionmaking
under
uncertainty).
We
connect
them
in
order
to
achieve
an
understanding
of
how
those
aspects
of
organization’s
activities
are
connected
and
how
they
influence
on
each
other.
This
study was performed with two main goals in mind. The first goal was on one hand to understand and identify the
main sources of uncertainty in the engineering process; and on the other hand to identify the main human biases that
affect the decisions made in the engineering process. The second goal was to see the theoretical aspects of decisionmaking
through
the
process
of
lean
planning
and
lean
information
flows
implementation
and
to
identify
ways
to
reduce
the
impact
of
the
human
bias
on
the
decisions
made.
Results
of this research are lean knowledge not sufficient, uncertainty can be handled better with lean, and overall
improvement not enough. Human biases exist in engineering department are availability bias, representativeness bias,
reliability bias and anchoring bias.
To minimize the effect of biases can be done through multi process which involved many parties, such as six thinking hats
technique, the premortem technique, checklists and memos. Besides that lean planning and the last planner system in the
engineering process make the process having better certainty.
Be on time, adapt to customer demand, inter-department coordination and information flow in general have been
improved 25% after applied lean planning.
Future research can be much more focus on evaluation and the way to handle human biases.Research on decision-making in lean environment has not been studied enough, and that inspired us to run more precise
investigation in that area. Nowadays, with the implementation of lean in numerous companies all over the world, it is
important to understand not only the truisms of lean, but also what impact does it have on sub processes of activities of
the organization.
As it is known, decisions are made by human and that means those decisions are influenced by many human factors. One
of those factors is biases and framing effects, that had been closely studied by Noble prize winner Daniel Kahneman and
his co-author Amos Tversky. They studied those effects from a point of view of economical psychology, yet not going into
details. We took their work as a basis for our study of human biases and decision-making under uncertainty in off-shore
construction.
In this research, we try to take a closer look into three theories (lean planning, the last planner system and decisionmaking
under
uncertainty).
We
connect
them
in
order
to
achieve
an
understanding
of
how
those
aspects
of
organization’s
activities
are
connected
and
how
they
influence
on
each
other.
This
study was performed with two main goals in mind. The first goal was on one hand to understand and identify the
main sources of uncertainty in the engineering process; and on the other hand to identify the main human biases that
affect the decisions made in the engineering process. The second goal was to see the theoretical aspects of decisionmaking
through
the
process
of
lean
planning
and
lean
information
flows
implementation
and
to
identify
ways
to
reduce
the
impact
of
the
human
bias
on
the
decisions
made.
Results
of this research are lean knowledge not sufficient, uncertainty can be handled better with lean, and overall
improvement not enough. Human biases exist in engineering department are availability bias, representativeness bias,
reliability bias and anchoring bias.
To minimize the effect of biases can be done through multi process which involved many parties, such as six thinking hats
technique, the premortem technique, checklists and memos. Besides that lean planning and the last planner system in the
engineering process make the process having better certainty.
Be on time, adapt to customer demand, inter-department coordination and information flow in general have been
improved 25% after applied lean planning.
Future research can be much more focus on evaluation and the way to handle human biases. | en_US |
