Decision Making Model: Analysis and Application for Case of
Bring Me Home Box.
Quang Dung Dang
Master of Business, School of Business, Western Sydney University, Locked Bag 1797, Penrith NSW 2751,
Australia
Executive Summary
The purpose of this paper is to provide urgent solutions to Bring Me Home Box to engage more customers by
analyzing decision making models. Bring Me Home Box is a newly opened Australian company that specializes
in the culinary industry. The company provides fruit delivery services to customers with the aim of preventing
waste and redundancy. The company is currently struggling as the number of customers is declining, so it is
imperative to make the right decision for the company's future strategy and operations. The models used in this
report include rational model, the dual model using system one and system two (including consideration of
biases), the dual processing model based on cognitive continuum theory (without considering biases), intuitive
thinking and bounded rationality model. The Rational model has been identified as giving the company certain
advantages in general decision-making such as analyzing the accuracy of information, comparing decisions.
Post-study decisions are included spend on marketing, offering discounts and freebies, identifying target buyer
groups and enlarging distribution channels. The next model adopted is the dual model using system one and
system two. This chosen dual-processing model applied in bring me box home to examine and evaluate the
market needs to target customers. The model drive with system one as fast thinking and system two slow
thinking it is ethically feasible to make a better decision. The first step of the process examined the system one
decision output in heuristics and intuitive with individual skills and knowledge to achieve the goal. It found
various biases and filters them to select the best alternative to implement in the strategy. In the evaluation part,
both system one and two chosen data entered to weigh the process factor. The decision-making matrix is the
attributes and other factors considered to be expressed in terms of the decision, variables, and parameters
discussed to make a decision. The final chart 2 identified the need to take action and implement it into the
market process. The third model adopted is the dual processing model based on Cognitive Continuum Theory.
With this model, the research found that innovative and motivate actions need to be taken to boost the
company's operations and attract more potential customers. In addition, Intuitive thinking has also been
discussed and researched, the result is that the company needs to organize surveys to create restaurants in the
region, cooperate with other businesses in the same industry such as Uber eats or Menulog, and requires
government confirmation of the safety of the products that the company is providing. Finally, bounded
rationality model has also been discussed to realize the limitations in each decision because according to this
theory, all human decisions are limited by cognitive limitation, inaccurate information and time constraints. To
minimize these shortages, the company needs to use all its resources to conduct market surveys, from which to
get the most accurate information to make important decisions. Overall, all models have advantages and
disadvantages, each of which helps the company to make different decisions. The research recommended that
the company use this report as a reference for upcoming company decisions.
Keywords: Decision Marking, Rational Model, The Dual Model, Dual Processing Model, Cognitive
Continuum Theory, Intuitive Thinking.
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Introduction
‘Bring Me Home Box’ Scenario
Bring Me Home Box is a startup company with the aim of eliminating food waste in
Australia. The company was found in 2018, has the headquarter in Melbourne and performs
in most of the states including News South Wales, Victoria and Queensland. In the
beginning, Bring Me Home worked with less than 30 businesses and this number has risen to
over 130 including Roll'd, Sumo Salad and Pappa Rich, attracting approximately 20,000
users (Masige, 2020). One of the main reasons why the company has created boxes is food
waste which has resulted in a massive environmental issue. Their service is focused on
sending boxes of local, in-season produce, and restaurant-quality meats to customer's door
without shipping fees (Forster, 2020). They partner directly with local suppliers, delivering
no plastic boxes and plant a tree every month with every subscriber. As a result, the company
has achieved more than 11,900 Kg of food rescued, 9,160,000L of water saved, 25,000Kg
CO2 prevented and 380 of trees were planted this year (Bring Me Home Box,
2021). Currently the company is having difficulty in retaining old customers and attracting
new customers. Recent data show that the company's customer base is severely reduced,
leading to consequences such as budget deficit, affecting development plans and operations
of the company. The reason is that the company misjudged the needs of the customer, leading
to the wrong direction of investment and development of the company. The following paper
will analyze the models of decision making and apply them to the case of Bring Me Home
Box.
Methodology
Working with virtual teams’ collaboration:
This process meets the intention; here, sustaining trust is essential to build a virtual
team. It challenged to decide on a group to complete the task, gather information evenly,
processes the objective, and clarify the roles and responsibilities (Gignac, 2015, p. 68). The
team needs to concentrate on what they do, share a vision and clarify what required to do?
Facilitate and enable to get work done as a group from the leader. However, heuristic and
intuition commonly found in virtual collaboration. The other result curried in group
discussion.
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Decision:
This result discussed further to make a decision effectively and efficiently to get
optimum result. Effective communication led to influence the group outcome to shape
various input. The group interaction made ideas and options; then, the decision proposal
tested, refined, modified and confirmed for development. Group meet can clarify, set goal,
shown to be ambiguous, challenged and make commitments (Hirokawa, & Poole., 1996, p.
215). Biases used in conversation such as blind-spot fail to realise what required in action?
Individual argued strongly influenced by heuristics to recommend ideas. The confirmation
biases and choice supportive biases commonly found in the group to consider independent
arguments such as to choose the organisation, issues and strategy. The Bandwagon effect
realised member fall in one direction others voted them immediately in the discussion.
However, the final decision concluded the availability of data and measure given below.
Measure the result (Gignac, 2015, p. 91):
The result is measured ability to meet the target with efficiency and quality. The result
further focuses on being responsible for influencing under pressure and fulfilling the
requirements.
Discussion
Rational model
This section covers the application of the process model designed by Harrison in 1996.
Through this model, the decision-making process is going to be analyzed for bringing more
sales to the business from the Adelaide region. This model is very helpful in evaluating
different alternatives, using deductive analysis and choosing the appropriate alternative for
successful implementation. Furthermore, through this approach, we tried to reach on the
mutual point until its implementation and revision as shown in the following figure 1
(Harrison, 2014).
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Figure 1- Managerial decision-making process. Source: HARRISON (2014).
The decision-making process used by the group started with setting our goals as a team
process and deciding on the defining the objectives we need to achieve. We started from
defining our objectives of the chosen topic in order to understand each other properly despite
different professional backgrounds such as management, marketing, human resource and IT.
The research involved the case study of meal kit delivery industry and it was easier for the
team to be on same page while discussing and researching about it.
The identified challenge that we got was that everyone had different opinions about the
success of the company in a regional city like Adelaide based on their own belief notions.
Post identifying the main challenge, the research worked on gathering the related information
from the official app page, blogs written on the web & social media pages of the company,
relevant websites about the food industry statistics in Adelaide market and success stories of
the company from various recognised food websites. In order to make the decision rational
and effective is to overcome biases and make effective decisions (Bang and Frith, 2017)
In terms of weighing decision criteria, the research decided on following points:
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Sales
20%
30%
10%
40%
Spend on Marketing
Offering Discounts and Freebies
Identifying Target Buyer Groups
Enlarging distribution channels
Figure 2- Weighing decision criteria. Source: Author
Regarding this, we reviewed options from different companies working in the same field such
as Hello Fresh, Home Chef etc. Consequently, we made a research of recent updates in the
business and we found that the company is trying to tap Adelaide market by putting up “popup stores” in the prominent locations such as Rundle Mall. We decided to work on it because
it would definitely help us in achieving the success that we were looking for our research.
Despite having various advantages, this model involves few unrealistic assumptions as well.
One of the most important among these are that the decision maker completely understands
the available alternatives, they do not have any perceptual biases and optimal decision will be
made. However, although this model could help in making decisions while evaluating the
available options, it does not guarantee the success of that decision as many biases may come
along. In this project, we all worked through this with a lot pre- occupied beliefs and biased
opinions (Roberts, & Wernstedt, 2018). Also, even if we had evaluated all the alternatives, it
was really challenging to rank them according to everyone’ s preferences.
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This model has definitely helped us in the decision making process because it has helped in
presenting the organized process the analysing the existing scenario effectively and
considering each of the alternatives for an effective decision (Wolfs,. et al, 2012).
The Dual Model Using System One and System Two (Including consideration of Biases)
Problem:
Situation to bring loosed and new customers from the covid-19 impact market play
essential role to increase customers.
How has the decision model chosen?
At first, the rational and balance model chosen to apply from experience widely used
in organizations by individuals. It is data-driven, balanced, effective and efficient output, but
alternative dual processing has a similar safety feature with an optimum solution. It has
logical and intuitive thinking, flexibility, balance, and ethics to make market decisions.
Chart 1.0 Comparison Result from Chosen Model
Other model
16%
Rational model
32%
Duel processing
model
26%
Balance model
26%
Rational model
Balance model
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Duel processing model
Other
Biases:
The rational and balanced model identified as choice supportive biases because it
realised the brain to recall past decision self-enhancing to support present situation (Benney,
& Henkel, 2006, p. 1001). The following dual-process model helps to examine how the brain
system work in decision making?
Dual processing model (Hall & Shaw, 2019)
The requirement viewed in two ways How to understand different customers and
think through the dual processing model? Buyers think two ways typically (1) quick, easy,
intuitive and automatic, or engage in (2) slow, controlled and effortful (Bazerman & Moore,
2013; Evans, 2008; Kahneman, 2011, as cited in Hall, & Shaw, 2019, p. 215). The following
model of decision-making is a dual processing cognitive process.
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Valuation by intuitive, experiential,
Affective,(System 1); VI (C)
Decision/choice
under uncertainty (C)
Final choice
VC = Vl (C) + VII (C)
Valuation by deliberative, reflective,
analytical/logical (System II); VII (C)
Figure 3- Model of decision-making using dual processing processes
Above figure 3, where C represents a decision-making situation “choice”, VI system one
decision making, VII system two decision making is analysed and evaluated to decide
(Djulbegovic et al., 2012, p. 2). The process is applied in the report to make a final choice.
SYSTEM ONE THINKING
Analysis
System one:
It has natural property in heuristic that is associative, intuitive and experiential. It can read
customer’s mind to understand their behaviour and make rapid interactional moves based on
activity. It leans towards the ‘fundamental computational biases of automatically
contextualising problems (Stanovich, 1999, as cited in Lapsley, & Hill, 2008, p. 316). The
market choice (C) given below, such as
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a) To implement the price option (e.g., basic, medium or large)
b) Market large populated & prestige suburb
c) Buy one and get a second one fifty percentage offer
d) Follow old data
e) Feedback from customers
f) Introduce celebrities for advertisement
g) Add value to a product
h) Senior suggestion to launch small box alternative of existing one
Analysing the above-market solution has heuristic & biases; what makes Heuristic & biases
led? It can lead to a wrong decision.
Valuation by Intuition decision from system one VI (C): The knowledge stored in memory
from experience and it required to examined and overcome heuristic & biases process.
Identified Biases:
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Above, Table 6.1 examined the information and overcame the heuristic & biases in the
process.
Selected criteria after examine from system one VI (C):
a) Customer feedback.
b) Add value to a product.
The above two option had chosen for evaluation, further in system two thinking to obtain the
customer feedback data.
SYSTEM TWO THINKING
System (two):
It is a slow but rational, conscious, analytical, controlled and rule-based process. It
acquired by formal instruction and leaned towards depersonalisation and decontextualization
of problems in the service of underlying principles (Lapsley, & Hill, 2008, p. 316). This slow
thinking develops the question How to get customer feedback? Is identified to build a
relationship.
Valuation by reflective, analytical/logical from system one thinking V Il (C):
Understand customer obsession build relationship: listen to build trust, create interest, ask
questions, be direct, open and honest (Berridge, 2016, p. 22).
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DATA
DESIGN
Figure 4- Design and data should cover deliver seamless gather data
Identify customer problems and expectation. Design: Move towards current practice
and embrace the new idea to keep customers and the ever-changing business environment
(Berridge, 2016, p. 83). The data develop various question to build and understand
the customer.
Customers interviewed:
Research from the consumer’s interview; considered necessary when shopping
groceries that derived the following supply (Irle, & Katz, 2019, p. 559).
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The above table 6.2 customers have a high preference but examine they used system one
thinking has availability heuristics. The feedback considered because their requirements
significant to evaluate to make a judgement (Appendix 4). The further data evaluated in the
decision matrix table 6.3.
Evaluation
The evaluation helps to weigh the information gathered and apply them in the
decision matrix.
Decision matrix (Haimes, 2015, pp. 123-124): Weigh the data by normalised to five and
derived in Table 6.3.
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Above table 6.3 derives the solution to weigh the data method; the first attribute is added
value, and normalised weigh is ‘one’ multiplied with bring me box score ‘three’ and total the
next column. The balance attributes follow the same concept to calculate and also with the
competitor’s data to compare. Further, chart 2.0 provides areas to take action to make a
decision.
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Chart 2.0 represent customers with high expectation; the competitor has a better strategy but
bring me home box required to achieve customer requirements to solve the organisation goal.
After analysed and evaluation, the following data provides a feasible decision.
Final decision from system one and system two for customer V I (C) + V II (C):
✓ Add value to customers such as an organic certificate or quality certificate.
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✓ Product choice introduces an alternative, e.g., cherry or Roma tomatoes.
✓ Accessibility delivery with quality.
✓ Price level monitors the competitors, market situation and update.
✓ Agglomeration to improve a product, e.g., bread, nuts and cake.
✓ Maintain a safe level of inventory.
The Dual Processing Model based on Cognitive Continuum Theory (without considering
biases)
The Dual processing model is currently one of the best preferred explanations of the
cognitive processes that describe people judgement and decision making (Djulbegovic, et al.
2012). According to the Dhami and Thomson (2012), Cognitive Continuum Theory there are
various methods of cognition that lie on a continuum between intuition and analysis.
Moreover, traditionally theories on models of cognition have determined on the dual
processes of intuition and analysis.
In addition to this, they also suggested that dual processing model has numerous advantages.
For examples,
•
It provides flexibility in decision making.
•
More than two minds work on a problem which helps to give better solution.
•
Brings an essential reality to decision making.
For Bring Me Home employees are working hard and looking after the community, people
and environment with their work culture. In this fast-moving world people are wasting so
much food every day, and in particular Australia around retail food sector throw away over
55,000 meals per day. Bring me Home is a food rescue start-up with a mission to eliminate
this food waste in Australia. The dual processing model is one the model, which help the
company to complete their mission. For example
•
Company provide flexibility to the owners and customers to sell and buy food through
the App.
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•
Not only company is worried about to save the environment, also retail food sector
business owners are also wants to save environment. In this way many minds work on
a problem which helps to give better result to both parties.
Moreover, not only in Australia, but food wastage being also an issue globally. According to
the Kou J (2020), 1 in 3 meals are going to waste. To solve this significance problem in
particular Australia Bring Me Home start taking the innovation actions. For example, for
example with the help of people they provide food to the needed people. This helps both
sides (employer and public).
Figure 5- A Brief Comparison of two forms of Analysis: Logic and Intuition
There are various methods have been constructed within the theory, but researchers have
claimed that are two different methods of cognitive systems. The author also stated that
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Cognitive Continuum Theory features the significance of the interaction between cognition
and the task for judgement and decision making.
Figure 6- Two System of Processing Involved in Thinking and Decision Making
IntutiveThinking
Intuition is a storehouse of unspoken knowledge. You must gain experience before you can
completely trust your instincts in decision-making. To choose the best answer, your mind
needs a frame of reference from previous situations. According to Kelly Turner, Ph.D.'s post
The Science Behind Intuition, the use of intuition has declined in modern times because we
no longer require a quick trigger for decision-making. These alerts are typically generated by
the right side of our brain, which is an instinctual operating system. In times of conflict,
intuitive thinking shines brighter. The Office of Naval Research spent $3.85 million in 2014
on a research programmed to better understand the phenomenon of premonition [Matzler, K.,
Ballom, F. and Mooradlan, T. (2007)].
Moreover, in complex circumstances, battlefield intuition aids decision-making, particularly
when time is short, risks are high, and knowledge is scarce. “Intuition is the Highest form of
intelligence” by Sylvia Clare. We discover that our minds know much more than we realise
as cognitive computing attempts to decode how Artificial Intelligence (AI) is best designed to
predict and respond to problems.
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The use of intuition in decision-making has been discovered to have a U-shaped development
curve. The novice may rely on inexperienced intuition before he or she conforms to the
modern environment, rules, and regulations. With practice and time, intuition matures into a
mature
intuition
that
starts
a
new
upward
curve.
Once
organisation
has the
necessary experience, it will have a better understanding of situation and then makes good
intuitive decision.
Figure 7- Intuitive Decision
One of AI's eight challenges is that biological systems must adapt to new conditions, while
software has less dimensions. We can come across the same problem many times and
respond in a different way each time[Mike James, 2019]. In clear way, can we continue to
neglect our intelligence's abundance if routine activities are automated, freeing up our time
for more innovation and governance? To better exemplify, there have been a few cases where
businesses have ignored their gut instincts and hired a professional who changed jobs within
18 months. BRING ME HOME BOX's IT department must make a significant investment in
each recruit. Although the talent was flawless, it came at the wrong time. As a consequence,
questions like how will I know what food I'd get? and does bringing me home cater to
different dietary habits arise, how can I tell if the food I'm eating is healthy? , What do I do if
I'm not happy with my order?, and similar questions were frequently asked in the bring me
home box.
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Bounded Rationality Model
The Bounded Rationality Model was conceived by Herbert Simon, which, according to this
theory, almost rejected earlier economic theories that: the systematic and rational choice of
possibilities has always been determined by human beings in order to maximize the economic
benefits of the latter (Ellision, 2006). This theory has proven that humans have a limited
capacity and tend to look for simple ways that only take into account some aspect of the
problem when determining options in the making decision process (Selten, 1990). As a result,
human decisions are often irrational, without optimality. The main limitations outlined in this
theory include cognitive limitation, inaccurate information and time constraints (Simon,
1990). In Bring me home box's case, the company's decisions seem to be limited by the lack
of inaccuracy in the information the company can obtain. Leading to consequences that the
customer leaves, affecting business capabilities and profitability of the company. The
information obtained by the company may come from unreliable sources leading to
inaccurate decision making. In order to minimize these mistakes, the research recommends
that the company need to do close research on the market and the customer. Reports and
research need to be focused by the company to provide accurate measurements of the market
situation and consumer level of consumption. From there, it is possible to minimize
unnecessary mistakes in company decisions.
Conclusion
To sum up, report on academic information to ensure accuracy of information each debate.
The decision-making models have been analyzed and applied to the Bring Me Home Box
case. Each model has its own advantages and biases. These biases appear due to individual
perceptions and external influences on decisions. The recommendations are made based on
our analysis results of each model, companies need to try the tests of each decision to be
made by a final decision for the development path of the company. The paper advises that the
company should use the above report as an important reference and use the resources it holds
to be able to make informed decisions in order to bring the company through the difficult
immediate period.
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