An investigation on IoT, Big Data and their influence on the supply chain, procurement and logistics using the oil and gas industry as a case study -- 4
Budget: £250 – £750 GBP
Research Problem
The oil and gas industry has always been one of the engines of the global economy and labour creation. In 2016, according to the US Bureau of Economic Analysis, it represented 4% of all the GDP of the US (Bureau of Economic Analysis, 2016). Regarding labour, according to the Bureau of Labour Statistics in 2017, the Oil and Gas account for 448 thousand of employees directly, meaning the equivalent to 6.8% of all the workforce of the US and indirectly to approximately 12.6% (Bureau of Labour Statistics, 2017). Thus, the importance of keeping the industry updated with the latest technology cannot be over-emphasized. In the current dynamic and competitive business environment, oil and gas companies compete against one another on behalf of their focal firms. In a scenario of network-based competition, the effective and efficient flow of goods and services determine the strength of a supply chain. Since IoT and Big data have been established to make possible for companies to run leaner, efficient, more sustainable production, supply chain, procurement and logistics processes. However, even though there is a tremendous opportunity for businesses to make these systems, there is still a gap between what companies want to achieve and what they can achieve. Because, they lack of digital culture, training, and high financial investment requirements (PwC, 2016). Therefore, oil and gas companies have not gotten a clear idea which technologies they should focus their investments on, and which methodology should they use to develop optimized systems in their operations.
Aim and Objectives
The aim of this research is to explore the possible impact IoT and big data can have in the context of supply chain, procurement and logistics in the oil and gas industry, and to propose a methodology to tackle the digitalization gap in this industry.
The objectives of the research will be to:
i investigate the effect of integrating IoT and big data on the capability on oil and gas industries
ii Investigate the effect of IoT and big data-enabled supply chain, procurement and logistic on oil and gas performance.
iii To develop a reliable IoT/Big data driven framework and system architecture for the coordination and monitoring of supply chain, procurement and logistics processes.
iv To validate framework and model developed to evaluate their effectiveness and efficiency, thereby identifying areas requiring improvement or modifications.
v To draw conclusion on the study, identifying major risk factors / causes of failures and offer recommendations accordingly
Research Questions
Therefore, the following two research questions will guide the respective objectives of the study:
Q1. Can IoT-enabled system influence supply chain, procurement and logistics performance and subsequently improve oil and gas performance?
Q2. To what extent does the existing or lack of IoT deployment effects the system and in turn influences supply chain, procurement and logistic performance of oil and gas companies?
Limitation of Research
The research will be limited by a variety of factors that will influence the methodology and the access to information. The following are the key perceived limitations that will determined the scope of the research.
There has not yet been confirmation about a developed structure for digitalization (IoT and big data) in the oil and gas industry in Nigeria. The sample size will be limited to Oil and Gas companies that have embraced digitalization or attained full digitalization in the area. The companies that have undergone digitalization process in its completeness are a few thus not all components of digitalization will be sufficiently evaluated.
The self-reported data is highly dependent on the pre-existing data. Therefore, self-reported data will be limited by the fact that the data collected will not be independent.
To reduce this, data will be collected using various factors such as the responses of questionnaires,
The oil and gas industry has always been one of the engines of the global economy and labour creation. In 2016, according to the US Bureau of Economic Analysis, it represented 4% of all the GDP of the US (Bureau of Economic Analysis, 2016). Regarding labour, according to the Bureau of Labour Statistics in 2017, the Oil and Gas account for 448 thousand of employees directly, meaning the equivalent to 6.8% of all the workforce of the US and indirectly to approximately 12.6% (Bureau of Labour Statistics, 2017). Thus, the importance of keeping the industry updated with the latest technology cannot be over-emphasized. In the current dynamic and competitive business environment, oil and gas companies compete against one another on behalf of their focal firms. In a scenario of network-based competition, the effective and efficient flow of goods and services determine the strength of a supply chain. Since IoT and Big data have been established to make possible for companies to run leaner, efficient, more sustainable production, supply chain, procurement and logistics processes. However, even though there is a tremendous opportunity for businesses to make these systems, there is still a gap between what companies want to achieve and what they can achieve. Because, they lack of digital culture, training, and high financial investment requirements (PwC, 2016). Therefore, oil and gas companies have not gotten a clear idea which technologies they should focus their investments on, and which methodology should they use to develop optimized systems in their operations.
Aim and Objectives
The aim of this research is to explore the possible impact IoT and big data can have in the context of supply chain, procurement and logistics in the oil and gas industry, and to propose a methodology to tackle the digitalization gap in this industry.
The objectives of the research will be to:
i investigate the effect of integrating IoT and big data on the capability on oil and gas industries
ii Investigate the effect of IoT and big data-enabled supply chain, procurement and logistic on oil and gas performance.
iii To develop a reliable IoT/Big data driven framework and system architecture for the coordination and monitoring of supply chain, procurement and logistics processes.
iv To validate framework and model developed to evaluate their effectiveness and efficiency, thereby identifying areas requiring improvement or modifications.
v To draw conclusion on the study, identifying major risk factors / causes of failures and offer recommendations accordingly
Research Questions
Therefore, the following two research questions will guide the respective objectives of the study:
Q1. Can IoT-enabled system influence supply chain, procurement and logistics performance and subsequently improve oil and gas performance?
Q2. To what extent does the existing or lack of IoT deployment effects the system and in turn influences supply chain, procurement and logistic performance of oil and gas companies?
Limitation of Research
The research will be limited by a variety of factors that will influence the methodology and the access to information. The following are the key perceived limitations that will determined the scope of the research.
There has not yet been confirmation about a developed structure for digitalization (IoT and big data) in the oil and gas industry in Nigeria. The sample size will be limited to Oil and Gas companies that have embraced digitalization or attained full digitalization in the area. The companies that have undergone digitalization process in its completeness are a few thus not all components of digitalization will be sufficiently evaluated.
The self-reported data is highly dependent on the pre-existing data. Therefore, self-reported data will be limited by the fact that the data collected will not be independent.
To reduce this, data will be collected using various factors such as the responses of questionnaires,