OMGT2229: Big Data Analytics and Supply Chain Strategy Case Study

This case study investigates the applications of big data analytics in supply chain management, focusing on the period between 2010 and 2016. It highlights the increasing volume of data and the challenges enterprises face in leveraging it effectively. The study emphasizes the importance of improving processes, integrating activities, and enabling business analytics through big data. It also outlines strategies for mitigation, including building a strong technological infrastructure and enhancing competitive benefits. The operational plan involves acquiring the necessary infrastructure, implementing effective management, and utilizing intercultural evaluations for team integration. Data storage solutions, such as cloud-based systems, are considered for cost-effectiveness. The analysis of data is crucial for deriving valuable insights and potential courses of action. The study also discusses the benefits of big data analytics, such as improved infrastructure and core competencies, as well as the risks involved, such as outsourcing logistics. The conclusion emphasizes the need for effective business management and customer experience to compete effectively in the market. The document is contributed by a student and available on Desklib, a platform offering study tools and resources for students.

BIG DATA
ANALYTICS
SUPPLY CHAIN
STRATEGY
Name of the Student
Name of the University
Author note:

INTRODUCTION
 The paper investigates the research
regarding big data analytics research as
well as applications in the field of supply
chain management in 2010 and 2016. It
also provides specific insights to the
organization. In addition, the current
years and the amount of data that are
important for the organizations. In
addition, it is important to develop
specific process that are arranged
properly.

SUMMARY OF THE REAL WORLD
CHALLENGE
 The amount of data that are produced
as well as communicated over internet
is increasing in a way positively. Hence,
creating challenges for the enterprises
would be helpful for reaping the
advantages from analyzing the big data.
 It is important for the organizations to
provide insight about big data as well as
the BDBA on the logistics as well as
supply chain management.

ISSUES IDENTIFIED
 It is important for the organizations to
improve the process, comprehend the
activities with the help of strategic
assets, and require managers
integrating the process through
analyzing the use of big data.
 In addition, it is important for the
organization to set the process and
enable the organization enabling the
business analytics (Tan et al. 2015). On
the other hand, big data analytics has
been a multi-step access.

OBJECTIVES OF THE INVESTIGATION
 Big data processing systems are
important to set the process and obtain
competitive benefits.
 On the other hand, the supply chain
management is important to the
technology as it has currently reached
to the layer insights (Chen et al. 2015).

STRATEGY
 SCM organizations that can assist the
process and reported.
 The organizations are inundated with
the data that the process helps and
markets or transformation. In addition,
an entity and apparently true in the
formation.

STRATEGY FOR MITIGATION
 A main strength lies powerful strong
foundation in the infrastructure in
physical as well as technological is
organized.
 As a small organization trying to
develop the market, it is significant that
the organization increases competitive
benefits to well-developed competitors.

OPERATIONAL PLAN
 In order to deploy the process and achieve
success in the processing, it is important to
involve in the process. On the other hand, it
is required to acquire the infrastructure for
deploying the retailing process and big data
analytics. The infrastructure is important the
process (Papadopoulos et al. 2016).
 On the other hand, it is required to enhance
the process with the help of effective
management. In addition, it helps the
organization by implementing the process
and big data and enhance the process.

DATA COLLECTION
 Intercultural evaluations are utilized as
the part of on boarding procedure and
contingency for employment. However,
it is required helping a new team
member get succeed in the cultural
diverse environments. The feedbacks
are based on an evaluation process that
can assist new hires emphasizing on the
areas required attention for personal
development.

DATA STORAGE
 A cloud based storage is considered as
flexible without a requirement of
physical systems where it is important
minimizing the costs in deploying big
data (Wamba et al. 2015). On the other
hand, it is important to assume the data
stored separately and integrate the
process and assist the data storage
professionals helping to transiting the
data.

DATA ANALYSIS
 Big data does not provide the
advantages. The analysis of data as well
as ability deriving the useful information
that provides value for the big data.
 In addition, the vendors are generally
renowned such as google as well as
oracle services that can assist in
analyzing the data as well as give a
proper insights as well as potential
course of actions for the customers (Wu
et al. 2017).

TERM 2 (3 MONTHS)
 It is also important to develop own
analysis team and working together
with the process. It is also important to
work in the procedure that can be sent
from the organization. In addition, it
assists the organization to develop the
process and the vendors are helpful to
be involved in the process (Akter et al.
2016).