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INFLUENCE OF BIG DATA ANALYTICS IN SUPPLY
CHAIN MANAGEMENT-A CASE STUDY IN
BANGLADESH SUPPLY CHAIN PERSPECTIVE
Md. Monwarul Islam
EV-17016051
Introduction
What is Big Data Analytics
Big data analytics is the often complex process of
examining large and varied data sets, or big data
Problem Statement
Massive amount of data
Hardly analyzed
Big data is providing supplier networks with
greater data accuracy, clarity, and insights,
leading to more contextual intelligence shared
across supply chains
Research Question & Objective
Research Question
RQ1. What are the implications of Big Data Analytics on information usage and
on decision making at corporate and supply chain level
RQ2 – How has BDA been used to manage SCM resources
RQ3 – In which SCM processes has BDA been used
Research Question & Objective
Research Objective
General Objective: Challenges and Opportunity of Digital Information at the
intersection of Big Data Analytics and Supply Chain Management
Specific Objective: Apply big data analytics in the field of Bangladeshi SCM for
asset productivity and business growth
Literature Review
The emergence of the internet combined with leaps in information technology
(Bandyopadhyay et al., 2010), such as storage, network, and
telecommunications capabilities, enables companies to have access to large
amount of data almost in real time, viewing “information as a strategic asset”
(Mason-Jones and Towill, 1997, p. 140).
The issue that the lack of up-to-date and “right” information, although being
an essential ingredient for the application of Big Data Analytics, may pose a
risk to the supply chain has gained little attention in the academic supply chain
landscape, as identified in a literature review study by Kache and Seuring
(2014)
Literature Review
In turn, not being able to mine the data available and thus not having access
to actual, accurate, and meaningful information represents a risk for
companies and subsequently for the supply chain, as decisions need to be
made on a reliable, evidence-driven basis (Ross et al., 2013).
Companies highly expect to capitalize on BDBA in logistics and supply chain
operations to improve the visibility, flexibility, and integration of global supply
chains and logistics processes, effectively manage demand volatility, and
handle cost fluctuations (Genpact, 2014)
Literature Review
Analytics describes the application of advanced statistics to historical data, with
the aim to identify behavioral patterns which eventually enable the forecasting
of future behavior to some extent (Shmueli and Koppius, 2011)
Analytics describes the application of advanced statistics to historical data, with
the aim to identify behavioral patterns which eventually enable the forecasting
of future behavior to some extent (Shmueli and Koppius, 2011)
Significance of the Study
51% of the population have agreed that BDA will help
to get better market position
44% of the population have strongly agreed that BDA
will help to increase productivity
44% population have agreed that BDA will help to get
better profit margin.
Conclusion
The use of Big Data Analytics is vividly debated among
scholars and the discussion is not limited to the field of
SCM
In order to fully unlock the potential of BDA-enabled
information availability across the SC, companies are
required to adopt cross-functional integration and
collaboration approaches with key partners
Influence of Big Data Analytics in Supply Chain Management- A case study in Bangladesh Supply Chain Perspective- Presentation

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Influence of Big Data Analytics in Supply Chain Management- A case study in Bangladesh Supply Chain Perspective- Presentation

  • 1. INFLUENCE OF BIG DATA ANALYTICS IN SUPPLY CHAIN MANAGEMENT-A CASE STUDY IN BANGLADESH SUPPLY CHAIN PERSPECTIVE Md. Monwarul Islam EV-17016051
  • 2. Introduction What is Big Data Analytics Big data analytics is the often complex process of examining large and varied data sets, or big data
  • 3. Problem Statement Massive amount of data Hardly analyzed Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains
  • 4. Research Question & Objective Research Question RQ1. What are the implications of Big Data Analytics on information usage and on decision making at corporate and supply chain level RQ2 – How has BDA been used to manage SCM resources RQ3 – In which SCM processes has BDA been used
  • 5. Research Question & Objective Research Objective General Objective: Challenges and Opportunity of Digital Information at the intersection of Big Data Analytics and Supply Chain Management Specific Objective: Apply big data analytics in the field of Bangladeshi SCM for asset productivity and business growth
  • 6. Literature Review The emergence of the internet combined with leaps in information technology (Bandyopadhyay et al., 2010), such as storage, network, and telecommunications capabilities, enables companies to have access to large amount of data almost in real time, viewing “information as a strategic asset” (Mason-Jones and Towill, 1997, p. 140). The issue that the lack of up-to-date and “right” information, although being an essential ingredient for the application of Big Data Analytics, may pose a risk to the supply chain has gained little attention in the academic supply chain landscape, as identified in a literature review study by Kache and Seuring (2014)
  • 7. Literature Review In turn, not being able to mine the data available and thus not having access to actual, accurate, and meaningful information represents a risk for companies and subsequently for the supply chain, as decisions need to be made on a reliable, evidence-driven basis (Ross et al., 2013). Companies highly expect to capitalize on BDBA in logistics and supply chain operations to improve the visibility, flexibility, and integration of global supply chains and logistics processes, effectively manage demand volatility, and handle cost fluctuations (Genpact, 2014)
  • 8. Literature Review Analytics describes the application of advanced statistics to historical data, with the aim to identify behavioral patterns which eventually enable the forecasting of future behavior to some extent (Shmueli and Koppius, 2011) Analytics describes the application of advanced statistics to historical data, with the aim to identify behavioral patterns which eventually enable the forecasting of future behavior to some extent (Shmueli and Koppius, 2011)
  • 9. Significance of the Study 51% of the population have agreed that BDA will help to get better market position 44% of the population have strongly agreed that BDA will help to increase productivity 44% population have agreed that BDA will help to get better profit margin.
  • 10. Conclusion The use of Big Data Analytics is vividly debated among scholars and the discussion is not limited to the field of SCM In order to fully unlock the potential of BDA-enabled information availability across the SC, companies are required to adopt cross-functional integration and collaboration approaches with key partners