Business Decision Making Analysis: Group Power, Big Data & Risk Theme

This report provides a comprehensive analysis of business decision-making, focusing on the power of groups, the application of big data, and risk evaluation. It explores group decision-making techniques like Affinity Diagrams and Open Space Technology, examining their effectiveness and ineffectiveness. The report also discusses the potential applications of Big Data in various sectors, including finance, healthcare, and customer insights, detailing the data required, processes for collection, and associated costs and benefits. Furthermore, it critically evaluates qualitative and quantitative approaches for risk determination, applying these methods to a selected firm. The analysis includes recommendations for improving decision-making processes and leveraging big data effectively, emphasizing the importance of informed, data-driven strategies for organizational success. Desklib offers similar resources for students.

Running head: BUSINESS DECISION MAKING ANALYSIS
Business decision making analysis
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1BUSINESS DECISION MAKING ANALYSIS
Table of Contents
Theme 1:.....................................................................................................................................2
Affinity diagram:....................................................................................................................2
Open Space technology:.........................................................................................................3
Effectiveness and ineffectiveness of group based decision making:.....................................4
Recommendation:..................................................................................................................5
Theme 2:.....................................................................................................................................5
Potential application of Big Data:..........................................................................................5
Data required for the firm for customer insight:....................................................................8
Processes, systems and capabilities to collect Big Data:.......................................................8
Costs and benefits of employing big data:.............................................................................9
Recommendations:...................................................................................................................10
Theme 5:...................................................................................................................................10
Critical evaluation of qualitative and quantitative approaches for risk determination:.......10
Risk evaluation for the selected firm by qualitative and quantitative approach:.................11
Recommendations:...............................................................................................................12
Reference:................................................................................................................................13

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Theme 1:
Organisations during 21st century under competitive market framework operates in
such an environment which is characterized by the wide amount of turbulence and dynamism
germinated through change in large amount of factors on which growth path of the market
depends (Wang and Chuang 2016). In addition to this, uncertainty in the market and strict
governmental intervention into the operational framework of the firm for the social corporate
responsibilities make the situation more complex where group decision making process is one
of the valid tools to deal with all of these.
Affinity diagram:
It is a categorised diagram that aids the firms to determine and pin point its ongoing
and future issues. As the mechanism to establish the same, the firm first asks the employees
to provide their respective comments regarding the present situation of the problem. Next to
this, given responses are stored as per their generic form and then heading were created under
which the comments given by the employees are placed (McNeill 2015). This way affinity
diagrams are created. Considering the present case, it can be said that the affinity diagram for
the ongoing problem remain within various factors and as per the previous endeavour of the
firm it can be argued that the firm is willing to focus on its product quality, maintenance,
manufacturing cost and environmental safety standards (Boopal and Kumar 2016).

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Open Space technology:
Open Space Technology has been defined as:
A simple, influential way to catalyse operative conversion working and actually germinating
firms that thrive for the swirling change. Open space technology is such a methodological
tool that transforms the self organising groups of different size to deal with the highly
complex issues within a short span of time. Main aim of the Open Space Technology is to
meet and create space and time for the group of people who are deeply indulged in the issues
affecting the performance of the firm (Lucero 2015). When it comes to the selected

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organization, then it can be said that the firm can utilise open space technology in order to
mitigate their ongoing issues in different sectors (Ratti 2017).
Effectiveness and ineffectiveness of group based decision making:
Effective group discussion encourage the participants to take part in the healthy
conflict that introduce creativity and bring in change in the ideas in order to solve the ongoing
issue within the firm. Conflict among the group members regarding the solution of the
ongoing issues is seen as the positive light by towards the better outcome (Chaudhury et al.
2017). There are various effectiveness of the discussion based problem solving method. Some
of them are as follows:
 Open discussion – Associates take part and make assistances to the group, with the
deliberations being sensible, and associates being ready to listen to and learn from
other group members. It allows better information sharing that eventually takes the
group towards better problem solving.
 Decision taking - Accomplishment a decision by a procedure of resounding members
by rational argument, rather than voting can leave a size-able minority disgruntled. It
aids the group to bring in parity among the group members.
 Using situational leadership – In a group there will be intellectuals with different
perspective regarding a problem, which will allow the group to find itself in different
circumstances Utilising the situational leadership, the group will be able to find right
through from the issue
 Proper assessment - Assessing the progress of the group to achieve its aims and
making the essential changes to improve its performance.
As per the Karhade et al. (2015), ineffective groups establishment depending upon the
agreed view point can defend it against any new or original idea that can aid to achieve the

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task quickly, though it often lead to the symptom treated rather than underlying cause. Such
negativity in the group can be characterised by the following:
 A lack of decided purposes and an atmosphere full of tensions held in check,
however, on times flare into critical conflict at personal level can reduce the
effectiveness of the group.
 Decision making through the voting enables the chance of scrutiny. However, in
group form of problem solving does not allow the same (Salehzadeh 2017).
In essence, one can look at these characteristics for effective and ineffective groups with
regards to certain elements.
Recommendation:
There has been lot of debate regarding the efficiency and the ability of the groups to
take rights decision. Though there are negative and dampening impact of the groups in the
rooking environment and in the case of the operational decision making of the firm, yet there
are more number of positive impact of the groups. Under the given scenario, it is essential to
bring in the group decision making process in order to take proper decision and make it
potential for solving the issues (Sun et al. 2016).
Theme 2:
Potential application of Big Data:
Industry influencers, academicians, and other stakeholders surely agree during the
recent years there has been lot of change in the data mining and the amount of available data
has been vast. Getting information provides a large amount of input regarding the everyday
lives, which has been argued as a large move from the perspective of the Big Data regarding
discovering genuine incentive in its utilization (Zhang et al. 2014).
While considering the approximation of enormous information keeps on residual a
test, other reasonable problems counting rate of return and financing and aptitudes keep on

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remaining as a critical task for a large number of enterprise that has embraced Big Data
(Rondovic et al. 2017). As per the Gartner Survey for 2015 it has been found that almost 75%
of groups are willing to put their resources into the Big Data in the next two years. These
findings express to a critical augmentation from a comparative overview done in 2012 which
showed that 58% of organizations put or were intending to put resources into Big Data inside
the subsequent 2 years (Looss and Lemaitre 2015).
Uses of Big Data is as per the following:
Keeping money and secure:
The Securities Exchange Commission (SEC) is utilizing Big Data to examine
monetary market action is one of the best impact of Big Data on the financial sector. They are
as of now use the system regular dialect process and system examination to track ulawful
exchanges relaed to the market. Big banks, Retail dealers, mutual funds in the money related
firms utilize Big Data for conversation examination utilized as a part of pre-exchange choice
help Estimation, Investigation, High Recurrence Exchanging, Predictive Analytics and so
forth (Pianosi et al. 2016). This industry thus intensely rest on Big Data for risky
investigation including illegal tax avoidance. Additionally it has aided the banks to bring in
module for better customer governance known as "Know Your Customer", and
misrepresentation relief.
Correspondences, Media and Entertainment:
Associations in this manufacturing during the same time examine client information
alongside social information to make good customer profiles which can be used to
(Akbarzadeh et al. 2016):
 Create content for various target groups of onlookers
 Recommend content on request
 Measure content execution

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Healing centres:
Healing centres like Beth Israel, are using information collected from mobile phones
through a large number of patients in order to enable experts to use prove based medical apart
from overseeing lab test towards all the patients who visits doctor. A sample for the test us
costly and unavailable nowadays as well, thus utilising the latest technologies doctors can get
in touch with the patients and derive crucial data regarding their health performance (John
2014). In addition to this University of Florida has also utilised Big Data for the investigation
of the social insurance data in order to attain their research aim and it has proved to be
beneficial for the research showcasing its potential to become one of the latest software that
can aid the firm to operate under controlled environment.
Customer insights through Big Data:
The client encounter is the most compelling motivation individual’s work with
specific organizations, regardless of whether they remember it. Almost 80 percent of buyers
have abandoned an exchange due to one poor administration encounter. In many markets, one
can get a similar item at an variety of stores, so it's fantastic client benefit that separates
awesome stores from normal ones (Marz and Warren 2015). Enormous information
influences awesome client to benefit conceivable. On account of the capacity to gather client
criticism through online audits, web-based social networking, and other brand says on the
web, organizations can take the input clients leave and place it into enhancing the general
involvement.
Better item for consummation:
Organizations can likewise utilize the pasting of information to enhance items. As
they figure out how their items are being utilised, to which extent it is being used and
preferred, organizations can take that data and transform it into Product. Enormous
information is the reason that consistently or two Apple turns out with a fresh out of the box

8BUSINESS DECISION MAKING ANALYSIS
new form of their iPhone. Or then again the reason that PCs and PCs get slimmer and more
brilliant with each rendition. The web hears what clients are missing from their items, and it
makes an interpretation of the data to organizations, who roll out awesome item
improvements happen.
Decreased crime and upgraded proficiency of administration:
Around 75 percent of government IT experts trust that huge information is basic in
counteracting and overseeing crime today. The reason numerous police divisions are
currently either creating or utilizing prescient models is to perceive where, when, and how
violations will happen (Lazer et al. 2014). On account of aggregate information, medicinal
services experts can utilize the data to find examples and connections in quiet care and
conduct, which are basic in diagnosing and treating patients. It gives an upgraded nature of
watch over every restorative patient. All things considered, huge information spares lives.
Data required for the firm for customer insight:
As per the Forbes, 87% of the firm considers that Big Data is potential to change their
industrial structure and performance which was different during one decade ago. In Addition
to this, Big Data is essential for the performance of the banking as well as the consumer
sector. It aids the firm to avail data of the customer demand and enable it to take action as per
the requirement (Wu et al. 2014). All the credit goes to the Big Data analytics that has aided
the firm to get rid of storing financial data and add value of the same.
Big data analytics conduct their historical analyses based on the business performance
that happen in real time in order to drive the immediate decision making. For this case, big
data will require information regarding the efficiency of work of the employees with the
present working environment.

9BUSINESS DECISION MAKING ANALYSIS
Processes, systems and capabilities to collect Big Data:
Data for Big Data can be collected by utilising the data mining technique. Under this
practise firms collect their user data and utilise the same for decision making. Considering the
given scenario it can be said that the firm can collect and share data real-time in order to
process the Big Data software.
Costs and benefits of employing big data:
Utilising the big data the firms can enjoy various benefits and additionally it can aid
the firm to have good growth path in long run. The significance of Big Data does not
alternate around the fact that an firm have or have not, however, it is concerned about the fact
whether the firm is sharing information or not. Every organisation utilises information as per
their own specific manner that makes the firm operationally and financially more stable
(Raghupathi and Raghupathi 2014). The firm can consider infoamrtion from any source and
utilise the same in order to attain answers that will enable it to do the following:
Cost Savings: Big Data with the devices like Cloud based Analytics and Hadoop can convey
cost points when a lot of information neeed to be put away. In addition to this, Big data helps
in recognition of more productive process for working jointly.
Time Reductions: The rapid speed of devices like in memory examination and Hadoop can
without much of time can recognize new sources of information which helps organizations
breaking down information instantly and settle on brisk choices in view of the learnings
(Chen and Zhang 2014).
New Product Development: By deliberate knowledge regarding the patterns of client needs
and fulfilment through investigation firms can make objects as per the needs of consumers.
Understand the economic circumstances: By analysing Big Data, firm can display signs of
development knowledge of present economic conditions. For example, by breaking down
clients' obtaining performs, an institution can learn the substances that are sold in large

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numbers and preferred by the consumers most. Depending on this, the firm can advance
beyond the rivals and capture more market share.
Control online image: As per the strategies of the Big Data, it can do sentiment examination.
In this way, firm can acquire reproach about itself and amend itself in order to act as per the
requirement of the consumers. Thus, market information that the firm need to screen and
improve the online immediacy of the business, a large number of instruments can be utilised
in order to do the same.
Recommendations:
For the present problem, it would be ideal to utilise the big data through real time data
collection that would aid the firm to achieve what it aims to.
Theme 5:
Critical evaluation of qualitative and quantitative approaches for risk determination:
Qualitative risk examination involves that the result and the probability be measured
using independent examination strategies and apparatuses, portraying them high, low,
moderate and very low categories. These different type of measurements of the risk
assessment are attached to every particular risk outcomes and occasion and potentially need
to be plotted with the help of the Probability Impact Matrix (Ni et al. 2016). It demonstrate
that the simple process of multiplication of the scale values in order to trace level of risk
associated with the endeavour. As per the Creswell and Creswell (2017), it can be seen that
the likelihood of negative factors potential to affect the environment and people need to be
judges with the alternative scale for better understanding.
Though Qualitative risk search is extensively without considering the fact that
whether sufficient information is available or not for the valuation by the means of
quantitative examination or not. Primary aim of the quantitative research are as follows
(Alvesson and Skoldberg 2017):

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 Determine the likelihood of accomplishing a particular task objective
 Quantify the risk presentation for the task, and decide the extent of cost and time
possibility that might be required.
 Identify dangers requiring most consideration by evaluating their relative commitment
to the ongoing task.
 Classify practical and attainable costs, timetable, and scope of the targets
The quantitative approach needs:
 The meaning of the probabilistic estimation of each single risk factors event.
 The quantitative meaning of the potential effect.
Quantitative examination for the problem solving of the firm is specially utilised in the
case of the potential task and to draw the timetable as well as the cost structure of the same.
Related confidence interval level for each possible value of the considered value aid the
researcher to determine the probabilistic distribution. Under this situation, potential
estimation of a given variable provides the researcher insight regarding evaluation of the
most extreme and the base point of the estimated value, depending upon which, firm can
derive the possible solution of the problem.
Risk evaluation for the selected firm by qualitative and quantitative approach:
In order to execute qualitative and quantitative valuations with the least level of bias,
the procedure has been organised with the definition of well-defined signs for each measure
levels. Depending upon the likelihood magnitude and range of each project impact area
qualitative and quantitative valuation is done. The assessment remain done on qualitative
base however, depending on homogeneous and standard approaches depending upon the
quantitative method performs the calculation (MacGregor et al. 2015). Associating the score
of probability and impact scale an improvement in the case of the Qualitative Assessment
Process can be done. Further possibilities of the analysis will be as follows: