Description
Applying Decision-Making ToolsIdentify a recent long-term decision you recently made or a long-term decision that you are currently contemplating. Decisions such as purchasing a vehicle, changing jobs, or even adopting a pet or having a baby, or a work-related decision such as an expansion or adding a new product all fit as long-term decisions, along with many other examples. In selecting a decision for this assignment, consider a decision that has long-term consequences costs, and benefits. Select one decision-making tool from either the course material or from another credible source, apply that decision-making tool to the decision. Explain how the decision-making tool is a good choice based on your identified decision. Apply the decision-making tool to the decision. Then summarize your findings. Based on your application of the decision-making tool, how should you respond to the decision? Do you agree with this analysis? Why or why not?In decision-making, the best practice is to apply a few decision-making tools, analyze the results. Then reflect on the results from applying the decision-making tools. After reflection, consider your intuition, does your intuition agree with the analytical process or not? See the attached file for the Week 3 Interactive Lectures for more details on decision-making tools to apply to this paper.Your paper should be 3-5 pages long and conform to Business Writing Format APA guidelines. Include at least 2 credible scholarly references.
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MBA560 Week 3 – Interactive Module Lecture
Module 3
Decision-Making Tools
Overview
In this module we delve into identifying and learning about both qualitative and
quantitative decision-making tools. Learning how to make better decisions can alter your
life, as well as improve your performance working within an organization. Making
decisions such as which job to accept or what house to buy, or adding a new product line
to an existing business all require critical thinking skills, covered in the previous module,
and the application of decision-making tools covered in this module.
Objectives
1. Apply a qualitative tool appropriate for a team decision-making situation.
2. Apply a quantitative decision-making tool.
3. Compare and contrast qualitative and qualitative decision-making tools.
3.1 Team Decision-Making Tools
Team Decision-Making Tools
There are a variety of team decision-making tools. Before addressing a few of these tools,
consider the benefits and drawbacks of team-based decisions. Benefits include a greater
diversity of ideas and discussions around each idea. This process generally increases the
quality of the decision. Greater commitment to the ideas as the team has buy-in to the
decisions since the team selected the idea. Drawbacks to team decision-making include a
slower process as ideas are presented and discussed. The team also has to define the
process of selecting the decision. Failure to openly share ideas, some team members might
not feel comfortable presenting an opposing or unique idea. Or some team members may
not be fully vested in participating in the decision.
The dangers present in team decision-making include groupthink, diversity-based infights,
information bias (refer back to Module Two to refresh your understanding of critical
thinking skills and biases), and risky shift. Click on the tabs to learn more about each of these
dangers:
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Groupthink: Groupthink is a situation where team members fall into a pattern in which
they solidify their thinking, to conform to behaviors or ideas held by the group or team.
The problem groupthink demonstrates is a failure to consider alternative information, or
alternative actions. Examples of groupthink include people’s belief that the 2022 election
was wrong. Despite repeated investigations challenging the 2022 presidential results,
there is a group of people who feed upon each other’s beliefs and words that the election
was stolen or fake.
Another example of groupthink goes back to the Challenger space launch in 1986 in which
the Challenger blew up 73 seconds into the flight. When groupthink is present, group
members ignore information that contradicts their beliefs, confirmation bias sets into
harm team members, and oftentimes, other people who weren’t part of the decisionmaking process, such as the astronauts aboard the Challenger.
To guard against groupthink, assigning a team member the role of devil’s advocate can
help to mitigate groupthink. A devil’s advocate is someone who challenges ideas,
assumptions, information, and decisions. The process of challenging or questioning team
member statements increases dialogue and prevents the team from getting locked into
one pattern of thought.
Diversity-based Infighting: Diversity-based infights are present when team members
focus on differences between team members, pigeonholing a team member with a label
that negates an openness to considering various perspectives. Von Oech (1983) labeled
these types of behaviors as mind locks. Assumptions made by a person about another
person are based on mind locks of how a person thinks another person should act or think
or presumes an inside knowledge of what a person is going to say.
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Information Bias: Information bias includes frameworks such as Attribution Theory, a
tendency toward a negative mindset, and flaws in logic, such as logical fallacies or
manipulations of information. Review Module 2 for more information on these topics.
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Risky Shift: Risky shift occurs when team members make riskier decisions than what
any one team member would make on their own. Examples of risky shift occur in horror
movies when one of the group members suggests a risky action such as entering a haunted
house. Other group members feel pressured to go along with the risky action, and even
add new elements of risk to the decision such as spending the night in the haunted house.
Three commonly used team-based decision-making techniques include nominal group
techniques, delphi technique, and computer-based tools. Click on each tab to learn about
how groups can leverage these techniques.
N o m i n a l : The nominal group technique approaches team decisions with each team
member writing down ideas on cards. In this process, the team members should be well informed
about the topic, or even considered subject matter experts. The team members as subject matter
experts should represent diverse knowledge related to the topic. For example, including someone
from customer service, engineering, and finance. A facilitator has each team member read the
ideas on their cards or collect the cards; all ideas are written on a board for all team members to
read. The ideas are then discussed. After discussing the ideas, a shortlist of the best ideas is
created. The next step is ranking the ideas privately, the facilitator shares the ranking and another
discussion follows. A final vote is made to identify the best idea. This process is more constrained
than brainstorming (a technique covered in the next section on creativity), thus decreasing
creativity, but providing informed responses.
D e l p h i : The delphi technique is similar to the nominal group technique but uses a private
collection of responses from the participants. A key to the successful use of this method is
correctly communicating information related to the topic. After informing the participants of all
information related to the topic, questionnaires are used to gather information from the
participants. The participants do not share their responses with anyone other than the facilitator.
The facilitator works with a different team made up of the people directly responsible for the
decision. As the results are analyzed, a new questionnaire is created based on the results from the
first round of feedback. When the decision-making team has narrowed down the results, the
participants are asked to vote on the results. The decision-making team will make the final
decision taking into consideration the participant’s vote. A best practice is to share the resulting
decision with the participants for any additional discussion. This process taps into informed
participants’ knowledge while preventing participants from influencing each other’s responses
since the entire process is private.
C o m p u t e r – B a s e d : The last team decision-making tool is computer-based and AI
tools. These topics are covered in this module’s reading assignment. As AI expands, new decisionmaking tools and techniques will be developed. Recently, a bridge tournament was held that
included eight world champion bridge players and artificial intelligence with AI winning (Spinney,
2022). As the reading material in this module presents, computer-based decision-making is highly
effective, unless undetermined flaws in the program move AI into flawed processes.
3.2 Creativity-Based Decision-Making
Tools
Creativity-Based Decision-Making Tools
Have you heard the phrase, right-brained or left-brained? Each side of our brains does
function differently. The left side of our brains mostly controls speech, language, writing,
math functions, and reasoning. The right side of our brains mostly involves spatial, motor,
musical, and touch abilities (Lumsden, Lumsden & Wiethoff, 2010). The left brain
processes information in a logical, linear, rational manner, while the right brain is more
holistic, intuitive, and abstract. In general, males are more likely to process information
using their right hemisphere while females are more likely to process information using
their left hemisphere (Vengopal & Mridula, 2007). With this being said, humans use both
their left and right hemispheres although some people might be more dominant in one
hemisphere than the other hemisphere. Does this mean that some people are creative and
other people are not creative? The answer is no, all people are creative, and all people can
build their creativity.
To encourage creativity, there are steps organizational leaders and managers can
implement. These steps include encouraging diversity on decision-making teams and
projects, empowering decision-makers, encouraging playfulness and risk-taking, building
in rewards and recognition for creativity, and encouraging openness for everyone to
express ideas. Merely adding diversity to a team won’t increase creativity unless the
people on the team feel comfortable sharing ideas. Building a culture that supports
collaboration and acceptance of all ideas is one approach to supporting creativity,
diversity of experiences, and idea exchanges.
The creativity process includes four stages, preparation, incubation, illumination, and
verification. This process is similar to IDEO’s design thinking process which includes
challenging assumptions, empathizing from the end-user’s perspective, defining, ideating,
prototyping, and testing. Another definition of design thinking includes the following
steps:
Frame a Question—Identify a driving question that inspires others to search for creative
solutions.
Gather Inspiration—Inspire new thinking by discovering what people need.
Generate Ideas—Push past obvious solutions to get to breakthrough ideas.
Make Ideas Tangible—Build rough prototypes to learn how to make ideas better.
Test to Learn—Refine ideas by gathering feedback and experimenting forward.
Share the Story—Craft a human story to inspire others toward action (IDEO, n.d., Phases
of Design Thinking).
There are a variety of creativity-based decision-making tools such as brainstorming,
mindmaps, design-thinking, and divergent thinking. These tools align with the above
processes using different approaches to tap into individual creativity levels.
For example, a key component of brainstorming is to refrain from any judgment or
assessment of ideas and build on presented ideas from a no-rules perspective. After a
wide range of ideas is submitted, the incubation process is to consider the idea. The
illumination point is when people start making connections around the submitted ideas.
Oftentimes in a brainstorming session, the final ideas are ideas that weren’t included in
the process. But the ideas generated new and better ideas that fit the situation. This is the
verification stage.
Mindmaps are a creative tool that includes drawing pictures, making word associations
and connections between topics. A mindmap taps into different parts of our brains to add
visuals as well as words and ideas.
Divergent thinking is a technique based on generating a wide range of ideas around a
specific problem or topic. Including time to walk away from the problem or topic moves
the problem or topic to our subconscious brain. At some point, the subconscious brain
discovers an interesting or possible solution to the problem. This is the point of
illumination where the solution becomes apparent. When completed correctly, this
illumination point feels almost like magic. The point at which a person says, where did that
idea come from? The following video covers the difference between divergent thinking
and convergent thinking.
Convergent Thinking vs. Divergent Thinking
Review this short, illustrated video to learn how convergent and divergent thinking can
impact your creativity process and potential outcomes.
In many cultures such as the U.S., people are more comfortable with concrete, logical
thinking processes and explanations. However, problem-solving and decision-making are
not always best served from a logical point of view. Take some time to practice using these
creativity-enhancing tools with an open mind. Finding a solution and working backward to
explain why the solution is the best solution from a logical perspective is also an
interesting activity as people find that even though they thought the creative process was
not acceptable or professional, the solution ends up being quite logical.
3.3 Quantitative Decision-Making Tools
Quantitative Decision -Making Tools
Quantitative decision-making tools use statistical or mathematical models to aid in
decision-making. Given the wide range of quantitative decision-making tools, a few
models are covered here and in other courses in the program. You will find that most
disciplines have recommended decision-making tools that fit the types of decisions
needed to support organizational success. A few popular decision-making tools include
scenario-based-what-if models, decision trees, cost-benefit-analysis, and hypothesis
testing with statistical analysis.
Quantitative data is based on collected data that can be counted and subjected to
statistical analysis. Examples of common quantitative data collection tools are surveys,
employee records, and other internal data such as tracking employee sick days, vacation
days, productivity rates, warranty numbers, and a variety of other data all depending on
what the research question is, or what information is needed to support decisions.
Scenario Planning
Scenario planning includes making predictions with what-if variables. An example is
creating a scenario around the price of fuel. Scenario planning could include either the
delphi technique or nominal group technique to find out what people think oil prices will
be in the future. Once the amounts are agreed upon, a scenario is created to analyze the
impact of the information. Let’s say the team came up with these three predictions, gas at
the pump is $3.50, or $4.00, or 4.75. The next step is using these different prices in the
company’s Pro-forma financial statements to review how the fuel price changes the
financial statements. All other categories would be adjusted based on historical and
predicted percentages such as anticipated increases in sales volume, wage increases, and
other known changes. The results are then analyzed from a strategic planning perspective
to decide if product pricing needs to change and by how much, if a previously identified
expansion should still be implemented, and what risks might arise based on the scenario
planning results and analysis.
Companies use scenario planning to avoid or mitigate risks and uncertainties. Having an
idea of how to proceed given different scenarios decreases the chance of making
impulsive decisions. Another example of how scenario planning is used as a quantitative
decision-making tool is in the airline industry. Depending on the price of fuel, airlines
purchase futures contracts to decrease uncertainties. Futures contracts are based on
industry expectations of commodity prices.
Learn more about scenario planning in the following article:
Scenario Planning: https://www.conocophillips.com/sustainability/managing-climaterelated-risks/strategy/scenario-analysis/
Decision Tree Analysis
Decision tree analysis is a visual outline, similar to a flowchart, that includes potential
costs, consequences, and potential opportunities. Decision trees include alternative
branches that represent different choices, decision nodes are displayed as a square and
represent decision points, chance nodes are displayed as circles representing multiple
possible outcomes, and end nodes are displayed as triangles that include a final outcome.
Notes are included in a decision tree providing details and numerical values, and
percentages are used to reflect the confidence level related to the different choices.
https://www.conocophillips.com/sustainability/managing-climate-relatedrisks/strategy/scenario-analysis/
https://asana.com/resources/decision-tree-analysis
Diagram of decision tree structure with decision points as squares, options branching from there,
with chance nodes as circles, branching into possibilities, each with a value and a probability,
and then branching into end nodes shaped as triangles.
Interesting in learning more about how decision trees can benefit your process?
Review the following article:
What is decision tree analysis? 5 steps to better decisions Links to an external site.
Cost-Benefit Analysis
Cost-benefit analysis or CBA is another quantitative tool used in decision-making. Costs
are identified related to a decision such as an expansion. The projected costs are
compared to the project benefits received from the project. As a student, you might have
used a CBA to decide if the decision to complete a master’s degree is worth the financial
expenditure.
To apply a CBA to this example, the student would add up the amount of money needed to
complete the degree. This would include tuition, textbooks, and any other costs. If the
student was working and decided that a full-time job and being a full-time student was too
much to take on, the lost income would also be included in the costs. Next, the student
would make a most likely projection of how completing the master’s degree would
increase the student’s income. Then subtract the potential income from the costs of
completing the degree to compute the net gain or net loss from the decision. In this
example, the student might want to consider the income earned over a few different
timelines such as three years. The question posed in the CBA is, is it financially beneficial
to spend the money needed to complete a master’s degree?
Another approach to using the CBA is to include a time-value of money computation since
the financial outflow of money is over a couple of years or so, and the financial gain from
the degree is realized over a few years. A third approach is to not extend the financial gain
beyond a few months of achieving the degree, then divide the costs by the benefit to find
the number of years before you would realize a net gain from spending the money on the
degree. This last approach is called a cash payback method, the cash investment (cost of
the decision) divided by the benefit of the decision or cash inflow. This analysis informs
the decision-maker how long it would take to reach a breakeven point between the cash
outflow and the cash inflows. Additional resources on CBA can be found in the following
set of articles: An Expert Guide to Cost-Benefit AnalysisLinks to an external site..
Scientific Method
The final tool covered here is the scientific method. The scientific method begins with a
research question. Next, a hypothesis is created that supports the research question. For
example, let’s say the research question is do students perform better on a multiplechoice exam or an essay exam. The null hypothesis is, there is no statistically significant
difference between mean average scores on a multiple-choice exam and an essay exam.
The alternative hypothesis is there is a statistically significant difference between mean
average scores on a multiple-choice exam and an essay exam. Both types of tests would be
administered to students, the results tabulated for both groups, then the statistical
analysis would be completed to determine if the null hypothesis was proven correct or
incorrect. The alternative hypothesis is assumed to be the opposite of whatever the
results are for the null hypothesis.
Quantitative tools provide numerical analysis to support decision-making, a much better
approach than trial and error which is quite costly to an organization. The general belief
about decision-making is that the more analysis made in exploring the decision, the higher
the likelihood that the end decision will be the best decision. There is some research that
supports one final step and that is to walk away from the decision to tap into the
unconscious parts of our brains, relax and stop thinking about the decision, then wait for a
divergent thinking moment when you know you have made the right decision.
This last section brings together how qualitative decision-making and quantitative
decision-making are different from each other and use different tools and processes. And
yet, the best decisions result from using a combination of both methods.
Check Your Understanding
Answer the following questions to review key concepts from this module.
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Question #1
Question #2
Question #3
Which of the following statements are true? (Select the best answer.)
Quantitative tools are based on numerical data and analysis
Qualitative tools are based on decisions that do not fit a numerical analysis
Both qualitative and quantitative tools contribute to effective decision-making
All statements are correct
Check Answer
What’s Next?
You’ve reached the end of this lecture. To move to the next area of the module, click on
the “next” button below. If you’d like to review any of the lecture content, use
the module link on the left side of the page or the “previous” button below.
References
(Nd). What is design thinking? https://www.ideou.com/blogs/inspiration/what-is-designthinking
Spinnery, L. (2022, March 29). Artificial intelligence beats eight world champions at
bridge: Victory marks milestone for AI as bridge requires more human skills than other strategy
games. The Guardian. https://www.theguardian.com/technology/2022/mar/29/artificialintelligence-beats-eight-world-champions-at-bridge
Vengopal, K., & Mridula, K. (2007). Students’ learning and thinking styles. Journal of the Indian
Academy of Applied Psychology, 33, 111-118.
von Oech, R. (1983). A whack on the side of the head: How to unlock your mind for
innovation. Warner.
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