Leadership and Managerial Decision-Making in an AI-Enabled Oil and Gas Industry

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Operating Cost ◽  
Oil Industry ◽  
Digital Age ◽  
Oil And Gas Industry ◽  
Management Decision ◽  
Business Decision ◽  
Leadership And Management ◽  
The Future

Abstract The Age of AI is defining a new set of challenges for leaders and the integration of digitalization and analytics into management decision-making is now a strategic priority for the oil industry. The fundamental challenge currently confronting the industry is to find leaders who can lead in the digital age. As the industry grapples with the AI revolution, pressure is mounting on leaders to react swiftly to the disruption that comes in its wake. Leadership and management methodologies currently employed by most organizations will not suffice in the digital age because leadership in this new age requires a different set of skills and organizational alignment. Yet, many organizations continue to struggle to put leaders in place with the knowledge and expertise to take on the challenges of leading in an AI-enabled world. This paper addresses the challenges and responsibilities that the AI revolution presents to oil industry leaders and provides practical insights to confront them. It details the concept of ambidexterity and why it is difficult for oil industry managers to achieve. It also outlines what it takes to implement an ambidextrous strategy in the industry and presents a framework for leaders as they drive transformation and explore strategies that will shape the industry's transition to net-zero energy. With social media now shaping business decision-making, the paper also discusses its impact and presents a unique approach for leadership to be strategically positioned to reconfigure their organizations to ensure they survive and thrive in the social age. Artificial Intelligence in the oil industry is not just about managing operations and reducing operating cost. It is also about developing a completely new way of doing business. Leadership in the digital age will be held accountable to a different standard. They would not only be judged by their ability to drive strategy and deliver financial results; they would also be judged on their ability to leverage AI resources and drive deep analytics mindset across their organization, while dealing with energy transition and social media. The workforce of the future will be dominated by technologically sophisticated people connected to multiple platforms. Managing this workforce will require a new kind of managerial wisdom. The big gains from digital transformation will not be realized unless industry executives rethink the criteria with which leadership and management success is judged. Becoming a transformational digital leader requires the ability to define a strategic vision for transformation, understand the promise and peril of social media, cultivate employees to succeed with AI, and use AI responsibly. The future belongs to leaders with these abilities and capabilities.

Artificial Intelligence and Robotics in the Oil Industry: Will it Take My Job?

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Artificial Intelligence ◽  
Oil And Gas ◽  
New Technologies ◽  
Oil Industry ◽  
Oil And Gas Industry ◽  
Human Robot Interaction ◽  
Gas Industry ◽  
Deep Dive ◽  
The Future ◽  
And Robotics

Abstract Historically, the oil and gas industry has been slow and extremely cautious to adopt emerging technologies. But in the Age of Artificial Intelligence (AI), the industry has broken from tradition. It has not only embraced AI; it is leading the pack. AI has not only changed what it now means to work in the oil industry, it has changed how companies create, capture, and deliver value. Thanks, or no thanks to automation, traditional oil industry skills and talents are now being threatened, and in most cases, rendered obsolete. Oil and gas industry day-to-day work is progressively gravitating towards software and algorithms, and today’s workers are resigning themselves to the fact that computers and robots will one day "take over" and do much of their work. The adoption of AI and how it might affect career prospects is currently causing a lot of anxiety among industry professionals. This paper details how artificial intelligence, automation, and robotics has redefined what it now means to work in the oil industry, as well as the new challenges and responsibilities that the AI revolution presents. It takes a deep-dive into human-robot interaction, and underscores what AI can, and cannot do. It also identifies several traditional oilfield positions that have become endangered by automation, addresses the premonitions of professionals in these endangered roles, and lays out a roadmap on how to survive and thrive in a digitally transformed world. The future of work is evolving, and new technologies are changing how talent is acquired, developed, and retained. That robots will someday "take our jobs" is not an impossible possibility. It is more of a reality than an exaggeration. Automation in the oil industry has achieved outcomes that go beyond human capabilities. In fact, the odds are overwhelming that AI that functions at a comparable level to humans will soon become ubiquitous in the industry. The big question is: How long will it take? The oil industry of the future will not need large office complexes or a large workforce. Most of the work will be automated. Drilling rigs, production platforms, refineries, and petrochemical plants will not go away, but how work is done at these locations will be totally different. While the industry will never entirely lose its human touch, AI will be the foundation of the workforce of the future. How we react to the AI revolution today will shape the industry for generations to come. What should we do when AI changes our job functions and workforce? Should we be training AI, or should we be training humans?

Marketing and Social Media

2018 ◽  
pp. 90-97 ◽  
Author(s):  
Reshu Goyal ◽  
Praveen Dhyani ◽  
Om Prakash Rishi
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Web 2.0 ◽  
The Internet ◽  
Internet Applications ◽  
Business Decision ◽  
World Today ◽  
The World

Time has changed and so does the world. Today everything has become as a matter of one click. With this effort we are trying to explore the new opportunities features and capabilities of the new compeers of Internet applicability known as Social Media or Web 2.0. The effort has been put in to use the internet, social media or web 2.0 as the tool for marketing issues or the strategic business decision making. The main aim is to seek social media, web 2.0 internet applications as the tool for marketing.

Business Decision Making Based on Social Media Analysis

2021 ◽  
pp. 203-213
Author(s):  
C. Santiago Morales ◽  
M. Mario Morales ◽  
S. Glenda Toala ◽  
B. Alicia Andrade ◽  
U. Giovanny Moncayo
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Media Analysis ◽  
Social Media Analysis ◽  
Business Decision

scholarly journals Evaluation and decision making in social media marketing

2017 ◽  
Vol 55 (1) ◽  
pp. 15-31 ◽  
Author(s):  
Brendan James Keegan ◽  
Jennifer Rowley
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Planning Process ◽  
Evaluation Framework ◽  
Social Media Marketing ◽  
Management Decision ◽  
Exploratory Research ◽  
Report Generation ◽  
Content Type ◽  
Wide Range

Purpose As organisations are increasing their investment in social media marketing (SMM), evaluation of such techniques is becoming increasingly important. The purpose of this paper is to contribute to knowledge regarding SMM strategy by developing a stage model of SMM evaluation and uncovering the challenges in this process. Design/methodology/approach Interviews were conducted with 18 key informants working for specialist SMM agencies. Such informants are a particularly rich source, since they manage social media campaigns for a wide range of clients. An exploratory research was conducted and thematic analysis surfaced the key components of the SMM evaluation process and associated challenges. Findings The SMM evaluation framework is developed. This framework has the following six stages: setting evaluation objectives, identifying key performance indicators (KPIs), identifying metrics, data collection and analysis, report generation and management decision making. Challenges associated with each stage of the framework are identified, and discussed with a view to better understanding decision making associated with social media strategies. Two key challenges are the agency-client relationship and the available social analytics tools. Originality/value Despite an increasing body of research on social media objectives, KPIs and metrics, no previous study has explored how these components are embedded in a marketing campaign planning process. The paper also offers insights in the factors that make SMM evaluation complex and challenging. Recommendations for further research and practice are offered.

scholarly journals Group Collaboration And Group Decision Making Information Technologies In Petroleum Industry

2005 ◽  
Vol 9 (3) ◽  
pp. 47-52
Author(s):  
Alpana M. Desai
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Management Practices ◽  
Business Processes ◽  
Oil And Gas ◽  
Group Decision ◽  
Petroleum Industry ◽  
Oil Industry ◽  
Oil And Gas Industry ◽  
Oil Companies

The technical management of important natural resources such as oil and gas resources is a challenging responsibility that faces oil companies. The increasing global demand for oil and gas coupled with declining oil and gas reserves has forced the oil industry to make significant changes in its business processes. Major oil companies have exploration and production operations that span several continents. Massive amount of data that is generated at all levels in an oil company has to be stored, analyzed and disseminated. In this paper, the changes in the management practices and business processes in the oil industry are traced over the past several decades. The use and application of information technology as change agents is also explored and evaluated. In particular, this paper focuses on the role of visualization centers in the oil and gas industry in revolutionizing effective group decision making that has enabled teams to be more productive, innovative, and outcome-focused.

Research on Customer Value Evaluation Based on Data Mining and Mathematical Statistics

2014 ◽  
Vol 926-930 ◽  
pp. 3890-3893
Author(s):  
Bin Yang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Customer Value ◽  
Customer Relationship ◽  
Management Decision ◽  
Value Assessment ◽  
Business Decision ◽  
Value Evaluation ◽  
Customer Information ◽  
Management Decision Making

In business you can get a number of data about customer information. How to find useful information for business decision-making from so many complicated, messy data and then to perform customer value assessment is a very important and complicated process. In this paper, data mining topics is identified as customer value assessment to assess customer value through data mining and statistical methods, in order to support the company's marketing decision making and customer relationship management decision making.

Management of Implementation of Nanotechnology in Upstream Oil Industry: An Analytic Hierarchy Process Analysis

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Pouyan Motamedi ◽  
Hasan Bargozin ◽  
Peyman Pourafshary
Keyword(s):  
Decision Making ◽  
Energy Demand ◽  
Oil And Gas ◽  
Emerging Technologies ◽  
Process Analysis ◽  
Oil Industry ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Novel Technologies ◽  
Single Matrix

Nanotechnology has had revolutionary effects in various fields of industry such as electronics, pharmaceuticals, and biomaterials. However, upstream oil industry has been noticeably slow in adopting the emerging technologies. This is mainly due to the exceptionally large investments needed to implement novel technologies in this industry. However, the projections for the increasing global energy demand require that oil and gas industry inevitably move toward adopting the emerging technologies. The high risk associated with enormous investments required for this aim necessitates measured and well-researched energy policies, with regard to the implementation of nanotechnology in the oil and gas industry. This paper presents a concise summary of the research reported in the literature on the potential benefits of nanotechnology in upstream oil industry. These applications were categorized into ten groups, and presented to a pool of experts, who judged on their relative importance with respect to various decision-making criteria. All this information was then compiled into a single matrix, which indicates the priority of each investment alternative with respect to every criterion in the form of a raw number. Finally, using a decision-making software package, a dynamic analytic hierarchical process (AHP) analysis was performed, providing a route to customized investment policies.

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