Analytical Thinking and Decision Making Process for Google's Suppliers

This report examines the decision-making process within Google, specifically addressing the challenge of selecting appropriate raw material suppliers. It emphasizes the importance of decision-making and the application of decision analysis techniques, including the use of big data analytics. The report identifies key issues related to supplier selection and utilizes SMART tools to define the problem and evaluate criteria. It also explores the role of big data in decision-making and the factors influencing decision quality. The report discusses the application of decision analysis techniques like research, risk analysis, decision modeling, and systems design to improve decision-making efficiency. The report also highlights the significance of big data analytics in decision-making and the need for standardizing tasks within Google's operational processes. The report concludes by underscoring the importance of continuous improvement in decision-making to enhance organizational performance. This analysis aims to provide a comprehensive understanding of Google's decision-making challenges and offer insights for better resource management and strategic decision-making.

Running head: ANALYTICAL THINKING AND DECISION MAKING PROCESS
ANALYTICAL THINKING AND DECISION MAKING PROCESS
Name of the Student
Name of the University
Author Note

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Executive summary
The aim of the report is to identify the main issue that is identified within the Google
organization in the decision making process. The decision making process is considered as one
of the important factors that are needed to be analyzed. The report has identified all the decision
making process so that it can provide better support towards the Google. The main issue that is
identified within the report is with the effective analysis of the raw material supplier that can be
selected for the purpose of supporting the business activities. The report has also discussed the
importance of decision making along with the application of this process. BD is obtained
from various sources, which have various in the development of a large data chain in Google.
Veracity such as manipulation and noise, diversity such as information heterogeneity and speed
is constantly changing the data sources exacerbated by the scale of big data demand for
hierarchical and contractual management structures to maintain BD reliability and for being able
to contextualize the data. The report will also use SMART tools for the purpose of defining all
the necessary components associated with the project.

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Table of Contents
Introduction......................................................................................................................................3
Decision making process.................................................................................................................3
Application of decision analysis......................................................................................................5
Decision making technique- using big data analytics......................................................................7
About the decision problem within Google.....................................................................................9
SMART tools for identifying decision problem............................................................................11
Criteria for selecting raw material supplier...............................................................................11
Table for selecting appropriate raw material provider..............................................................14
Decision making tree.....................................................................................................................14
Conclusion.....................................................................................................................................15
References......................................................................................................................................17

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Introduction
The main aim of the report is to identify the main issue that is faced by the Google.
Google is one of the most successful organization that is having a wide number of customer as
well as employee base. Thus it becomes very much essential to identify the issues that are faced
with the decision making process in Google. The main issue that is faced within the organization
is with selecting an appropriate raw material providers for the purpose of managing the resources
within the organization. The report will critically focus on highlighting the necessity of decision
making process along with the application of this process. GOOGLE creates its own data and
does not solely relies on the outsourcing aspects. Thus it becomes very much essential to select
an appropriate raw materials provider who will be capable of meeting the needs of the
organization. The report essentially incorporates the role of big data in the decision-making
procedure of GOOGLE. The report also forecasts limelight on the factors influencing the
decision making quality.
Decision making process
Decision making process plays an important role within every organization as this helps
in managing the performance and ensures that each decision is taken in such a way that it will be
beneficial for the organization. Decision making process is further divided into different types
that includes tactical and strategic decision making process, basic and routine decisions,
organizational and personal decisions. Big Data has found a huge importance in the decision-
making process as it helps in supporting a wide range of factors. Particularly in cases where
several people are involved and all phases of the BD process are challenging to manage, the
reliability of decisions could be undermined. For understanding the factors that affect this, a

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thorough understanding of the meaning is needed. A thorough knowledge of the Big Data chain
is required in the similar vein in order for understanding the factors that influence the
performance of decision-making. Such in-depth study was therefore performed within a broad
information-processing enterprise. For achieving a deep understanding the factors affecting the
performance of decision-making, a methodological methodology focused on study analysis was
introduced. The technique of this study analysis is particularly suitable for researching
institutional problems. Through fully understanding the meaning and documenting perceptions, a
single study may lead to scientific development. To recognize a large range of factors affecting
decision-making performance, deep understanding is important, while knowing interactions
contributes to the recognition of processes for enhancing decision-making efficiency. Since the
performance of decision making relies on a decision-maker, the compilation and storage of
information, all these considerations are taken into consideration while evaluating the case study.
It was found to be limited the number of cases that could reveal factors influencing BD for
quality decision making and using BDA for decision making (Lakshen, Vraneš and Janev 2016).
This was more compounded as some of the situations examined were unable to disclose their
activities. Once the data is prepared, big data analytics started to analyze the information for
identifying the patterns. The department collaborated with department of data quality, as the
dataset is required for being enriched, which requires additional data. The sources of BD
originate from the various places associated with YK construction industry.
Patterns of BDA show the generic relation that cannot hold the individual case. For an
instance, anybody trading goods can mean that he or she is selling the own belongings for being
able for buying the new goods or products. In the similar outcomes of BDA, it shows that the
self-employed have become unemployed or ill often make mistakes in filling the tax. The

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decision making process is determined with the help of identifying the outcomes. Decision
making process should be carried out in such a way that it has the potential to offer effective
support towards the business, consumers and also will provide proper individual benefits. Thus
the decision making process is being divided into
Application of decision analysis
The term decision analysis refers to a quantitative, systematic and a visual approach for
making several strategic decisions related to business. Several kinds of tools are utilized by
decision analysis which in turn assimilates various aspects of economics, various techniques of
management and psychology (Raghupathi 2014). There are various decision analysis techniques
like research, analysis of risk, modeling of decision, systems, design, decision making, and
improvement of decision etc. These decision analysis have their applicability almost everywhere.
Research is necessary for gathering of all the information related to any particular
decision which in turn involves analysis of both the solution and the problem space along with
risk identification of any particular decision. Research also involves various experiments,
analysis of the business, experiment of the thought process as well as the strategic drivers
(Sagiroglu and Sinanc 2013). It is applied for gaining solutions to the ongoing issues about the
decisions to obtain a correct logic for a decision made.
Next decision analysis is the analysis of several kinds of risks that is related with any
particular decision. This involves the analysis of impact and probability of all the risks that have
been identified. It also focuses on the investigation of the treatment which can be utilized for
reducing the risks that have been identified. The risk moment and the risk triggers might be
modeled in certain scenarios (Saha and Srivastava 2014). It is very helpful in representing the

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matrix of impact and probability along with the ratio of reward and risk. It find its applicability
in risk management projects where it is helpful in the determination of the different kinds of risks
associated with a particular project, security issues information technology etc.
Decision modelling is also a decision analysis where the structure of any particular
decision is modelled like in a scoring system for the identification of all the tradeoffs that are
primary and options for a particular decision. This kind of decision making involves criteria,
architecture of choice, criteria and matrix of decision, decision tree, balance sheet of decision,
modelling and mapping of decision, SWOT analysis and gap analysis as well (Visinescu, Jones
and Sidorova 2017). It is applied for relating the logic of the business to the use cases, methods
and software models.
An important role is played by the systems in the process of the analysis of decisions.
The utilization of a software for calculating, processing and visualizing all the data related to any
particular decision is very important. Efforts are executed for the semi-automation or automation
of the decisions with the utilization of artificial intelligence and several algorithms in certain
scenarios (Woerner and Wixom 2015). An example of it can be the calculation of the credit score
for automation of certain decisions regarding the rejection or acceptance of any application of a
credit. This also involves analytics, processing of data and decision support.
The design of the solution is very important and is referred to as a creative process that
commences when brainstorming of several ideas takes place resulting to the progress of the
evaluation processes which is way more systematic. This involves logic, strategy, thoughts that
are rational and design thoughts (Hazen et al. 2014). This is applied for the implementation of
several technical solutions to the projects and it is customized to specify business process
management and integration related to a particular project.

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An essential is also made by the process of decision making on the basis of the tradeoffs
like risk and several opportunities regarding the specified goals of the decision and the tolerance
of the risks. It is also referred to as a qualitative method of for scoring. The decision is made by
the several individuals like designer, architect or leader (Gandomi and Haider 2015). This also
involves sanity check, dominance of strategies and certain tradeoffs. It is applied in various
organization for improving their businesses and maintaining the standard.
Improvement of the decision is also very necessary for the betterment of any business and
is termed as the method of evaluation of the outcomes of various decisions which were
previously made for the aim of improvement of processes which are involved in analysis
practices and methods of decision making (Janssen et al. 2017). It involves the individuals to
counterfactually think and focuses on the quality of the decisions which are made. This is
applicable for improving the quality of decisions for accomplishment of a certain goal (Elgendy
and Elragal 2014). It is expected that with the use of decision making tools and techniques it will
become easy to manage the performance of the organization. This will also help in selecting
appropriate raw material for the organization and hence will ensure that a better way of
managing the products is being incorporated within the organization.
Decision making technique- using big data analytics
BDA and BD were innovative activities for Google. However, the BDA and BD were
stated within operational department initially, but the new entity was found of Google. This
entity was operated from the department of operation separately. In the agile manner as Google
is not bounded by the institutionalized patterns, principles and procedures. For being the separate
entity that helped for attracting the high skilled workforce and for searching the new ways for

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using the BDA and pilot the new practices. The BOD (Board of Directors) controls the entity of
Google for enabling the quick decision-making of the directors those are to be taken (Juddoo
2015). The agility has the advantages for allowing the organization for making the conscious
trade among the individual requirements and the government. The government must avoid the
power of exercising and the use of BDA and BD and that is needed to be careful. The board
consulted the other stakeholders for ensuring the various interests in the account while deciding
the usages of BD.
Particularly where BD's usage exceeds the individual's privacy was observed to become a
commonly occurring trade-off. The findings of BD and the BDA culminated from the need
for standardizing and routinizing the tasks and incorporate them into the organizational operating
processes in order to allow BDA to be used in real time. There was the need to teach, improve
and inspire workers at the same time. This process has been initiated by Google. However, the
full implementation of the real-time use of the BD for the functional processes has not been
implemented as significant technical challenges have been encountered. It was found particularly
challenging to integrate the BDA into the systems business process management that support
the administrative work. Some other concern was the swap of knowledge on collecting and
manipulating the data (Dong and Srivastava 2013). The information speed and the need to grasp
the concrete sense also make it hard to routinize the research and integrate the use of the BD and
BDA into the organizational processes.
Factors influencing the quality of decision-making
The study supports a fascinating insight on the various factors that affect the performance
of decision-making. Although there was no randomized controlled trial, the reports and surveys
revealed that over period the impact of these influences has shifted (Demchenko et al. 2013).

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Using BD for Google has become more sophisticated and institutionalized. BD and BDA
implementation was the evolving process that started with the ad-hoc operations and needed
institutional improvements to take the advantage of the possibilities (Janssen et al. 2017).
Agreements have been reached with the other parties over the time for acquire the necessary
information. They hired new employees and created a new division. For taking advantage of BD,
the separate department of the organization was established that operates the operational
department independently. This culminated in the potential within the short time frame for
creating value with BDA.
About the decision problem within Google
Google was willing to share its activities and there was a lot of publicly available
information. In addition, this broad data management company is seen as a front-runner in
Google usage of BD and BDA. The tax agency operates a dynamic BD system and has already
implemented BDA in its decision-making systems, resulting in new insights and significant cost
reductions. The media recorded these examples. This study was conducted utilizing blogs,
records, articles and media interviews and analysis. All strong-identify decision-making reasons.
The decision making process for selecting appropriate raw material provider plays a crucial role
as it will help in managing the performance of the organization.
Google has many links with the other organizations for retrieving the data about hundred
and thousand million citizens and millions of organization, who are paying taxes. Sources of
relevant data of the other organizations consist of the base registers such as vehicle registry,
business and citizens. However, the information of crime or the surveillance is also the data
resources. Moreover, Google wants to employ information, which is published by the citizens on
the social media sites such as Facebook. Other public organizations gather the structured or

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unstructured information for the own purpose that is used for enriching the internal information
of Google. Google manages the BD chain by gathering the information from the other private
and public organization and combine the information with the internal system. The use of the
BDA and BD was dynamic and ad-hoc initially. The information was available but the
information was not clear. Mainly four departments were connected that were respectively
collected, prepared, analyzed and the made decision (De Mauro, Greco and Grimaldi 2016). The
BD collection was the ad-hoc process based on the personal relation with the organization that
required the agreements with others. This makes it crucial to identify the importance of selecting
appropriate raw material supplier so that each products can be managed effectively within the
system.
Various types of interrelated factors impact the performance of decision-making and they
are established through taking the chain perspective. Several variables affect the quality of
decision-making. Data quality affects decision-making from many data sources. Such data will
then be analyzed. Key factors were found for being the quality of systems, the integration of
the data handling processes and the contract and the relational governance to ensure the data
quality and the knowledge transfer. The more the processes are configured, and the simpler it
becomes to handle BD, they are ideal for managing BD. The capability of the workers was found
to be essential as the rights expertise and competencies should be open to employees. Training
was required and foreign workers were sometimes recruited on the basis of collaboration with
BD organization. Governance is a dynamic aspect, as it is influenced by considerations such as
connectivity, loyalty, decision-making obligations and processes that can be seen as a model to
governance. Mechanisms for relationship and contract of governance were found. In the early
stages, the first controlled, while the latter is essential when the BD chain is institutionalized. A

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dependency on the chain is that the reliability of BD collection affects the need for data
processing activities (Cai and Zhu 2015). Sometimes it took many compilation phases before the
information could be used. The balance of the performance of the data source and the ability to
process data affects the quality of decision making. The aim of governance is to create the right
environment for data processing and to insure that the correct data is obtained at the right quality.
Most facets of BD affect the quality of decision-making.
SMART tools for identifying decision problem
Simple multi attribute rating techniques is entirely based on the linear additive model.
This helps in evaluating different aspects related to the project. The analysis process for SMART
includes different stages that are typically identified as determining the decision makers,
identifying the issues within the selected area, identifying an alternative for overcoming the
issue, identification of the criteria, assigning appropriate values for each of the criteria,
determining the weight for each of the criteria and calculating a weighted average, making a
proper provisional decision and finally performing sensitivity analysis (Bi and Cochran 2014).
With the help of SMART technique it becomes easy to determine overall value for a given
alternative that is calculated as the total sum of performance value.
Criteria for selecting raw material supplier
There is a huge need to select effective supplier who will be able to meet the needs of the
organization by providing support. The below table is being developed for the purpose of
analyzing the raw materials that are used for enhancing the performance of the Google. The table
has evaluated top suppliers name and the composition they can offer towards an organization.

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Raw
material
supplier
WEIGHT
British
federation
group
Total
polyme
r
solutio
ns
ALBIS IMAGR
O
Plastributio
n
Ultra
polymer
s
laptop 2.3 4 3 2 3 4 2.5
Mouse 10 15 10 14 10 15 10
Hardware 30 20 40 36 40 30 25
Chromeca
st digital
media
players
10 10 25 20 30 25 20
fiber optic
cables
200 150 155 180 100 200 180

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252.3 199 233 252 183 274 237.5
Values for making decision
ATTRIBUTE
S
WEIGH
T
British
federatio
n group
Total
polymer
solution
s
ALBI
S
IMAGR
O
Plastributio
n
Ultra
polymer
s
Safety 30 70 50 45 50 70 65
Fluency 25 50 40 90 70 50 60
Reliability 15 40 50 10 50 30 50
Security 25 50 70 45 40 50 40
Effective 20 20 30 30 20 30 30

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Aggregate
Benefits
Table for selecting appropriate raw material provider
Raw material supplier ANNUAL
COST
YOUR OWN
SUPPLIES
£
ANNUAL
COST
AGENCIES
SUPPLIES £
ANNUAL
JANITOR
COST £
TOTAL
COST
£
1. British federation group 400 500 15,600 19,670
2. Total polymer 500 400 14,902 18,000
3. ALBIS 600 450 13,900 17,500
4. IMAGRO 560 400 14,900 16,900
5. Plastribution 320 590
12,800
13,400
6. Ultra polymers 450 300 13,200 12,800
Decision making tree
Decision making tree is developed in the form of graph that uses different branches for
the purpose of illustrating every possible result for a particular decision. This helps in
strategizing the activities effectively. The main advantage that is offered with the use of decision
tree analysis is that it offers the ability to assign specific values towards a problem, ensures an
effective way of making decisions and also helps in analyzing the outcomes. The main reason
behind using a decision making tree is that it helps in reducing the ambiguity.

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Conclusion
BD and BDA value is created by improving the efficiency of decision-making.
Notwithstanding its significance, the use of the BD in decision-making has been restricted to
date. BD and BDA are often assumed to lead to better decisions, but this may be too simplistic.
There are many factors that influence the quality of decision-making. Therefore, it is too easy to
conceptualize BD and BDA as just a single process run by a single data scientist as shown in this
study. Having a chain viewpoint helps both the actions carried out in a BD system and Google
carrying them out to be examined and the interdependencies between those activities to be
recognized. This contributes to a better knowledge and diverse set of factors that affect the
performance of decision making. BD origins vary and have various characteristics that impact
how to handle BD and how to use BDA. There are many aspects affecting the quality of
decision-making that need to be discussed at the same time to improve the efficiency of decision-
making. The key factors listed include process improvement and implementation, skill

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development, maintaining expertise and human resources, ensuring data quality, agile processes,
teamwork, knowledge sharing, reliability of decision makers, building trust and handling
relationships. The main challenge described was not to tackle the size, but the ability to
understand the BD and use BDA for creating value through addressing information diversity,
rate, veracity, and validity. In comply with these BD features; these systems need to be in
operation. The reliability of decision-making relies not only on BD and BDA, but also on the
ability to manage the BD chain.
The results show that the reliability of source information, information processing, and
how data exchange is treated affects decision-making performance. Such results demonstrate the
need to establish adequate and efficient frameworks for the management of the BD chain for
contractual and interpersonal governance. It also highlights the need for structures of government
to handle BD's storage and distribution. Government must provide exposure to BD outlets,
provide input into BD efficiency, and recognize BD's sense and limitations.

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