Knowledge management is an essential strategy of gaining competitive advantage for organizations. Academics and managers realize that knowledge is an important resource that requires management since it creates value, is rare, non-substitutable, and non-imitable, especially for knowledge with tacit characteristics (Alwis & Evi, 2008). The management of knowledge is increasingly a part of technological organizations, intended to promote the sharing of knowledge with the aim of successfully creating innovation. This drives the need to study the role of knowledge management in technological firms like those in the oil and gas industry since they are rich in tacit knowledge. In addition, research shows that knowledge management is a theme that is continually a reflection of the competencies and organizational practices (Choudrie & Mohamad, 2004). This is because though knowledge management is the management of information, it also entails the facilitation of new knowledge creation, and the manner in which people share and applies knowledge (Alwis & Evi, 2008; Davenport & Marchard, 1999).

This review of literature will explore the various approaches on knowledge management, in terms of tacit, explicit knowledge, and the barriers to knowledge building. It will further investigate the different information processing, value adding knowledge management in the oil and gas industry and the lessons an organization can learn from these. The review of literature will also study knowledge management systems, their architecture, and application within the oil and gas industry. Lastly, it will analyze how knowledge capturing, development, retention, and sharing are applicable to the oil and gas industry.

2.1 Tacit Knowledge

There are many levels of knowledge in an organization’s resources. The first and most common is structured knowledge obtainable from instruction books and databases (Choundrie & Mohamad, 2004). The most difficult form of knowledge is tacit knowledge, which is the subjective and transparent knowledge form (Choundrie & Mohamad, 2004). Other authors define tacit knowledge as that information that is informal and personal, with roots in procedures, action, emotions, values, and commitment (Alwis & Evi, 2008). This knowledge is unconventional and un-coded, and is only acquirable through observation, imitation, and sharing of experiences (Kikoski & Kikoski, 2004). The idea of tacit knowledge was brought to the academic field by Rosenberg (1982), who defines it as that which entails methods, techniques, and designs working in a certain manner and with certain consequences, which a person cannot explain (Alwis & Evi, 2008). Tacit knowledge is important for technological firms, like those in the oil and gas industry since it encompasses all technical and cognitive expertise of an individual. Therefore, this knowledge entails all the individual’s talent, education, judgment, and experience.

Different academics and scholars have explored different approaches that firms can use to vitalize and manage tacit knowledge. Alwis and Evi (2008), shows that tacit knowledge activation is through the involvement of individuals in innovative processes within the organization, along with the stimulation of creativity. In addition, Kikoski and Kikoski (2004) indicates that the capitalization and activation of tacit knowledge, can occur through group brain storming activities, which also can provide new and innovative ideas for the organization. These can occur through social and group work activities, but for difficult-to-acquire tacit knowledge, in-house learning is required (Nonaka et al., 2000). Learning occurs through production and innovation processes of an organization, occurring both from the internal and external environments of the organization.

2.2 Explicit Knowledge

The second form of knowledge is explicit knowledge described as knowledge embodied in language or codes because of communication and verbalization processes, storage, and transmission (Kikoski & Kikoski, 2004; Nonaka et al., 2000). This form of knowledge is widely recognized since it exists in print form like journals, books, and television among others. This is the information individuals are aware of and share it in the form of scientific formulas, data, and manuals among others (Alwis & Evi, 2008). Nonaka et al. (2000) shows that explicit and tacit may be different in form but are complements, since both forms are essential in the creation of knowledge. Kikoski and Kikoski (2004) explain that explicit knowledge in any form looses it meaning without tacit knowledge. The study results of these researches show that a firm can only gain competitive advantage if it creates a knowledge learning curve for individuals by developing both tacit and explicit knowledge (Kikoski & Kikoski, 2004). The study of the evolution of tacit into explicit knowledge arises from the aspect that these forms of knowledge are in use in knowledge management.

Studies show that knowledge can evolve from the individual’s information to organizational knowledge, with the expansion and valuation of organizational knowledge stimulating individual knowledge (Nonaka et al., 2000). The concept of evolution of knowledge arises from the idea that knowledge in firms is convertible in a firm’s interactions to achieve knowledge management process (Alwis & Evi, 2008; Williams, 2006). Williams (2006) refers this evolution of knowledge as the articulation of knowledge to show the interplay between tacit and explicit knowledge. These studies indicate that effective management of tacit and explicit knowledge in firms also entails the ability of the firm to create knowledge conversion continually. Knowledge conversion occurs through socialization, where tacit knowledge converts to tacit knowledge through sharing (Nonaka et al., 2000). Conversion also entails the externalization of knowledge, where tacit knowledge converts to explicit knowledge. Explicit knowledge converts back to tacit knowledge through internalization or learning processes (Nonaka et al., 2000; Williams, 2006). Nonaka et al. (2000) explores that the last mode of knowledge conversion entails externalization, where explicit knowledge converts to explicit knowledge. This conversion sums up knowledge management processes of knowledge creation, transfer, creation, reuse, sharing, detection/discovery, and assessment/organization. The review of literature offers insightful information for this research on the necessary processes a firm can use to build knowledge management, and handle tacit and explicit knowledge. These basic principles form the foundation of this study’s search for understanding of effective knowledge management in the oil and gas industry.

2.3 Knowledge Building Barriers

Knowledge management involves various processes like creation, transfer, creation, reuse, sharing, detection/discovery, and assessment/organization of explicit and tactic knowledge. This study has gained insight on the importance of the interplay between explicit and tacit knowledge to a firm, from the exploration on literature. An emergent theory on this is the use of “collaborative and learning knowledge building” activities that will allow the interplay between organizational and individual knowledge (Kimmerle et al., 2008). Knowledge building (KB) is a product of social software systems and a concept of innovative methods of knowledge management (Wagner, 2006). Knowledge building is the production of new knowledge and entails innovative and permanent advancement of ideas (Kimmerle, Cress, & Held, 2010). It is also those socio-cultural processes, which occur to create information relevant to any firm to allow members to create and internalize useful information. Therefore, given the importance of knowledge building in knowledge management, it is necessary to address barriers of KB that limit effective knowledge management.

2.3.1 Organization Effect

The assumptions and beliefs of an organization constrain the building of individual cognition and use of knowledge. Organization effect creates the surprise value in the failure of KB due to discrepancies in the beliefs and assumptions of the organization. KB entails the creation of knowledge through the facilitation of transfer and explication, driving the study of barriers of KB to focus on the organizational climate (Schein, 2002). Organizational climate or effects are the psychological environment entailing primarily of organizational culture. Peter and Scott (2005) indicate that the barriers to KB and information transfer can arise from any level of learning in the primary path, either from individual to team, team to individual, team to organization, organization to team, or organization to inter-organization (Peter & Scott, 2005). The organizational effect barrier is the organizational imperatives like management imperatives at the management level. They also entail organizational culture determined by the lack of a psychological safe environment for the transfer of knowledge, the presence of team conflict, and strong hierarchical and political barriers (Peter & Scott, 2005). It also includes an organization that lacks trust and team sharing, lack of capability and confidence in learning, lack of flexible organizational systems and structures (Propp, 1999; Peter & Scott, 2005). The belief is that organizational culture is the combination of these assumptions and beliefs, which either motivate or hinder KB.

2.3.2. Technology

Technology is a second major barrier to knowledge building. Technology, especially in the current information world is proving to be a formidable new challenge to individuals and organizations. This is because the development of individual and organizational knowledge requires the possession of up-to-date technological knowledge, and equal participation in the creation of new knowledge using technologies (Amar, Coakes & Granados, 2010). Technology in knowledge management supports the functions of transfer, capture, and storage of information. Desouza (2003) in a study found that the use of technology for knowledge management initiatives creates limitations. The study analyzed this problem in the scope of resistance to using knowledge management systems that employ technological skills and resources (Desouza, 2003). This is more so in working environments that are more likely to make use of technology like those in the information and technological field. The results of this study offer a deeper insight into the reasons why technological firms may find the use of technology in knowledge management a barrier. Desouza (2003) shows that an engineer’s resistance to knowledge sharing is associated to their perception of acknowledgeable expert. This is because they perceive future projects having a foundation on past knowledge rather than on learning (Amar, Coakes & Granados, 2010). There is also evidence that the use of technology is limited especially where there is a lack of categorization and capturing of the necessary knowledge. For example, software technicians and program analysts find it difficult to input or explain their tacit knowledge (Desouza, 2003). Moreover, in the technological firm, there are alternative knowledge exchange platforms that do not necessarily require the use of technology.

Amar, Coakes, and Granados (2010) on the other hand, show that the limitation of technology arises from the lack of adequate action and communication between management and staff. Often, management pushes for KB and use of technology, through training and learning, but does not attempt to use technology therefore setting unclear standards. In addition, Mason and Pauleen (2003) find that the use of technology is hampered by the fact that information originates from individuals, therefore where there is a lack of sharing no IT solution can deliver the goals of KB. Moreover, firms that makes technology the core of their knowledge management system rather than a facilitator of interactions, with experience challenges in implementing technology systems in KB.

2.3.3 Knowledge Sharing

Extensive research has been carried out on the knowledge building through knowledge sharing. One of the prominent themes that emerge is that knowledge building is fueled by the interaction of individuals, organizations, and knowledge through the sharing of knowledge. While knowledge sharing is vital for KB, research shows that it presents major hindrances to KB. Knowledge sharing becomes a challenge in an organization that employees fear to share their tacit knowledge. Kearns (2008) finds that employees will hold on to their knowledge if they feel their experiences are nor utilized or sought. The inability of knowledge management to make use of their knowledge drives employees paranoid and frustrated about their job security (Kearns, 2008). In the process, employees that feel unappreciated will deteriorate in their roles and responsibilities. Zawawi et al. (2011) in a study of knowledge sharing in public universities found three factors that prevent the practice of knowledge sharing among members of a firm. These are factors were tested and proven, and identified as the lack of self-efficacy in presenting individual information, lack of communication and information technology for technological factors, and the lack of organizational reward (Zawawi et al., 2011). This is also supported by the qualitative study by Ardichvili, Page & Wentling (2003) that shows an organization that lacks motivation of employee participation in knowledge sharing hinders KB. The study finds empirical evidence that employees that feel that knowledge is a public good of the whole organization, tend to share it more and increase the flow of information (Ardichvili, Page & Wentling, 2003). Even when they have this perception, employees will not share knowledge from fear of criticism, or the influence of misleading members. In addition, the resistance to share information hampers knowledge sharing in a matter of expertise, is from a fear of losing valued position (Kearns, 2008). However, in project teams, it is the ability of sharing expertise and knowledge that makes one an expert.

3.0 Knowledge Management in Oil and Gas Domain

The goal of this research is to study the state of knowledge management in the energy sector in a broad manner to reveal any future directions for practice and research. Knowledge is essential for the operations and strategy of organizations within the oil and gas sector. This knowledge is in various forms, which include scientific knowledge like petroleum chemistry, management knowledge like the motivation of engineers to produce new operating practices, and technological knowledge like the efficient running of generators (Edwards, 2008). knowledge management to this sector is important since even at basic and simple processes like extraction of value in the supply chain requires technological and scientific knowledge. This section studies knowledge management in the oil and gas industry by analyzing the concepts of information processing, and value added knowledge management.

3.1 Information Processing in the Oil and Gas Domain

Information in the oil and gas industry is often in the form explicit knowledge or data. Tacit knowledge exists in the form of expertise and individual knowledge of the engineers, managers, and oil exploration experts among others (Edwards, 2008). The oil and gas industry relies on technology or intelligent techniques like fuzzy reasoning, neural computing, and evolutionary computing to analyze and interpret data (Masoud, Lofti, & Victor, 2004). The role of using intelligent techniques in data interpretation and analysis is to make breakthroughs in engineering and science to transform the data obtained into information, and turn information into useful knowledge (Masoud, Lofti, & Victor, 2004). There are different information processing approaches in the oil and gas industry, with the most common entailing intelligent techniques.

Intelligent techniques are used in various functions of this industry, these are like risk assessment, uncertainty analysis, data analysis and interpretation, knowledge discovery, data fusion and mining (Masoud, Lofti, & Victor, 2004). These information-processing techniques use data from different sources like geological data, well log, three dimension seismic analysis, and production and management data (Edwards, 2008). The aim of using these techniques for this industry is for exploration purposes, reduction of risks, increase production, and achieve efficient production of wells, and extending the life of production wells (Masoud, Lofti, & Victor, 2004). Therefore, information processing in this industry mainly uses technology for various management, scientific, and technological reasons.

3.2 Value Added Knowledge management in the Oil and Gas Industry

The review of literature indicates that knowledge plays an essential role in the operations and strategy of firms in the oil and gas industry. This section examines the literature on knowledge management practices within this domain, and explores possible value added knowledge management examples in the industry. The oil and gas industry strives to create better and innovative ways of carrying out operations through value added knowledge management. Collins and Parcell (2004) in a study found knowledge management strategies for project teams that made use of innovative aspects of traditional knowledge management practices like virtual teamwork, and learning achieved greater efficiency and production. The paper drew from the case study of BP, which successfully made use of virtual teamwork approach to improve knowledge sharing (Collison & Parcell, 2004). Consequently, BP was able to improve its expertise globally over its geographically dispersed branches to have each expertise assist in bearing local problems, like trouble-shooting of equipment failures (Edwards, 2008). Collison and Parcell (2004) found that BP was able to achieve such successful results since it adds value to its knowledge management by making use of an innovative learning strategy. In this organization, learning as a means to transfer knowledge and share information, was modeled on the theme, “Learning before, Learning during and learning after” (Collison & Parcell, 2004). The company makes use of communities of practice, to create teams that share a common bond under the sharing of expertise and passion. This introduces the use of communities of practice, as an essential practice in knowledge management as it encourages the existence of shared communities, teamwork, and information sharing through group work (Wenger & Snyder, 2000). To Barrow (2001) adding value to the knowledge management strategy using communities of practice as BP did, entails the creation of different team-networks to cover major business and management operations.

The studies on BP make major contributions to the field of knowledge management because the results show that for knowledge management to add value to the company, it requires the building of a culture in which individuals are willing to share information. Another value adding practice to knowledge management is the adoption of holistic approaches to knowledge management by companies (Coffman & Greenes, 2000). The authors identify that oil and gas corporations like BP and Shell were able to achieve knowledge management that value-added to their companies through holistic methods. The holistic approach entailed the transfer of the best Knowledge management practices from and into the energy sector (Coffman & Greenes, 2000). The holistic approach also entails the creation of networks of employee teams to share knowledge, and the creation of a culture of ownership among employees for knowledge management initiatives. Therefore, it is evident that adoption of knowledge management principles in the oil and gas industry adds value to companies as they opt to create a knowledge management culture that will drive communities of practice to share knowledge, and create employee ownership to knowledge management practices (Alwis & Evi, 2008). This review finds these points paramount in understanding the best approach a business can add value, using knowledge management following the example of the oil and gas sector. an interest fact introduced by studies by Davidson & Black knowledge management an (2005),Van den Berg & Popescu (2005), and Pauleen et al. (2007) studies is that value added knowledge management leads to better coordination of specialists and professionals from different oil and gas organizations. The studies also indicate that value added knowledge management in this industry assists organizations to deal with the uncertainty of the industry’s environment.

This line of reasoning arises from the literature that shows that knowledge management culture is applicable in all business operations and management functions. According to (Edward, 2008) this knowledge management culture was valuable to BP for it assisted in its mergers. Literature also identifies several methods of adding value to knowledge management approach like the combination of resilience and diversity by Shell, as an innovative knowledge management strategy (Leavitt, 2002; Reinmoeller & Van Baardwijk, 2005). Smith & Farquhar (2000) found in their study of knowledge management application in the oil industry that, project driven knowledge management portals assists companies to improve exploration, production and deal with problems of geographically dispersed specialists. Such studies therefore, draw attention to the need for innovative knowledge management strategies applicable to an organization’s line of business.

The mergers were successful since BP made use key principles in knowledge sharing to achieve technological and expertise knowledge (Barrow, 2001). BP added value to its knowledge management during the merger by creating communities of practice CoPs for different operation and management practices. This is evident in the network of CoPs for refinery operations management to new employee networks (Barrow, 2001). Apart from CoPs, research show that adding value to knowledge management also entails the use of technology to improve knowledge transfer, storage, sharing, and building. Barrow (2001) finds that BP was able to increase knowledge building and sharing with technology like 3-D visualization technology. The technology offered his resolution visualization environment for the specialists and engineers with different skills to work together remotely (Edwards, 2008). Technology adds value to knowledge management approaches in the oil and gas industry, like the use of virtual seminars or meetings by scientific and engineering experts in the petroleum industry (Edwards, 2008). In the oil and gas domain, web-based virtual seminars are common as they join the geographically dispersed geoscientists, as they share information in interpretation of seismic data. The web-based virtual technology has increased the manner in which specialists in the oil and gas sector share information and solve complex problems in exploration, using teleconferencing, and video conferencing (Edwards, 2008). Another use of technology is the linking of employees in one department spread across geographically location to gain similar results. Edwards (2008) shows that technology like Technical Information Centre has assisted in the provision of knowledge to geographically dispersed teams in the oil industry, as seen in the case of Venezuela’s State Oil Company.

3.3 Lesson Learnt from Oil & Gas Knowledge Management Practices

The review of literature on knowledge management practices in the oil and gas industry indicates that there are several lessons organizations can learn. This entails the creation of a need and importance for knowledge management in the organization, by top management to achieve notable success. This was evident in the case of BP, which created a knowledge management culture, and Km theme, which were applicable to the communities of practice. In addition, from the example of BP, organizations learn that KM can be a culture, where employees embrace KM initiatives passionately through ownership. This ownership leads to commitment to the communities of practice or the KM teams, in which knowledge management processes like sharing and transfer are achievable. Moreover, employees that are able to own knowledge management initiatives tend to be more corporative in developing and creating new knowledge and information essential for the development of the organization.

The review of literature also indicates that organizations can learn from oil and gas industry value adding approach to knowledge management. From the examples of BP and Shell, organizations can learn that application of knowledge management initiative must transcend from the traditional practices to new innovative and up-to-date practices. These practices entail the use of technology in knowledge capture, sharing, transfer, processing, and storage, especially in the creation of communities of practice. From the example of BP, organizations learn the value of communities of practices created not only within companies, but also for geographically dispersed teams. The organizations can make use of expertise and knowledge from different parts of the world with communities of practice, and virtual teamwork, which make use of technologies like video conferencing and teleconferencing. Moreover, the adding value learning process use to share and create knowledge can improve KM strategies. Organizations can learn from BP the value of encouraging employees to learn before, during, and after any KM practice. This entails the creation of an environment in which employees continually learn and gain knowledge and expertise from continuous sharing with colleagues in projects and in the workplace. Therefore, knowledge management evolves beyond time and place constraints to become a continuous process. Organizations should realize that this is possible in a firm that is able to encourage ownership and commitment of employees to knowledge management, by creating a knowledge management culture. The goal is to create an environment in which teams share a common bond of continuous knowledge sharing.

Organizations can also learn the value of making knowledge management a people-centered approach to allow the sharing of tacit knowledge. People centered approach to knowledge management in the oil and gas industry is evident in the wide use of communities of practice and the network of teams. Moreover, given the use of a culture of knowledge management where employees are encouraged to have ownership over KM, the oil and gas industry shows that it is possible to adopt people-centered approach. Moreover, organizations learn that this approach is accentuated by enhancing it with information technology tools to support the sharing of explicit knowledge. Moreover, given the people-centered approach used by oil and gas industry, it is evident that organizations can learn the importance of selling solutions to communities of practice or project teams, the value of obtaining support on KM from fellow employees. This implies that knowledge sharing in KM is not limited to the communities of practice, but communities of practice can obtain knowledge from colleagues. This is because organizations need to realize that KM succeeds if there is peer recognition of the knowledge sharing processes.

4.0 Knowledge Management Systems

4.1 Introduction

4.1.1 Definition

Knowledge management Systems are the information systems designed and adopted for an effective and efficient way for firms to store, acquire, and apply intellectual capital or the experience and knowledge of employees (Wickramasinghe, 2003). knowledge managements are the environments that organizations use to manage their information assets like databases and documents, and offer knowledge management an integrated approach for creating, delivering, verifying, evaluating, and sharing knowledge assets (Dattero, Stuart, & Richard, 2002). Firms use KMS to support information processing, and the facilitation, and enabling of sense-making actions of employees’ knowledge, simply these are systems that actualize knowledge architecture (Wickramasinghe, 2003). This section discusses in detail KMS architecture and technology, and its use in the oil and gas industry.

4.1.2 Architecture

The knowledge management field evolves with each evolution of different technologies and information systems. In the environment of organizations, there are two models of KMS architecture. These are network, and repository systems (Kamla & Olfman, 2005). Repository models seek to capture an organization’s explicit knowledge including knowledge management processes of creation, storage, retrieval, collection, and dissemination of knowledge (Kamla & Olfman, 2005). This model entails technologies like Information Systems, like databases and document management systems. Network model KMS, entail the transference of knowledge between individuals through person-to-person systems, information technologies and communication channels (Kamla & Olfman, 2005). This type of architecture stores the source of the knowledge but not the knowledge itself. Examples of such architecture are Yellow pages that stores employees’ information, or videoconferencing systems that transfer knowledge.

Systems that analyze and design like JAD and use cases support user activities like the addition of entries into the KMS and enable firms to search for relevant information (Wickramasinghe, 2003). However, sharing and integration of information across departmental boundaries becomes a challenge for such systems. Literature shows that this challenge is overcome by KMS architectures within the Enterprise Application Integration systems (EAI) like client/server systems, which create a network of knowledge (Wickramasinghe, 2003). Iyer, Shankaranarayanan, & Wyner (2006) shows that within this architecture are innovative software components that assist organizations to coordinate knowledge management processes and carry out integrated information-processing approaches.

Dattero, Stuart, & Richard (2002) explore the architecture of KMS by analyzing architectures that support passive and active knowledge in organizations. This study presents knowledge on information systems management architectures that support knowledge management like computer languages, collaborative and group software, database management systems (Dattero, Stuart, & Richard, 2002). The study shows that the organizational environment is able to process information faster and more efficiently with the use of such client/server architectures that entail network technologies and data storage systems. These architectures are important for they promote knowledge management with an integrated approach to capture, identify, retrieve, share, and evaluate information. Dattero, Stuart, & Richard (2002) shows that organizations that can integrate technology architecture into their KMS end up with innovative, effective, efficient, and sustainable systems that support knowledge management processes, while making it easier for users. KMS is also identified by literature to make use of architectures like database management systems, messaging and communication systems like instant messaging and VoIP, retrieval and browsing systems like the internet over networks (Iyer, Shankaranarayanan, & Wyner, 2006). Internet and internet based KMS architectures have offered organizations with seamless integration of different technologies and currently play a dominant role in the support of knowledge management activities.

4.2 Knowledge Management Systems within the Oil and Gas Domain

Literature shows that knowledge management systems are in use in the oil and gas industry. In the oil sector, the most common knowledge management systems are Decision Support System (DSS) is an expert system that assists in the use of specific documents and information to support specific decisions. The study by Irgens and Landryova (2006) on data systems and information processing in the oil sector shows the wide use of technical ICT aspects in an oil refinery. One of these technologies is the SCADA or the Supervisory Control and Data Acquisition system, which in combination with the Rule-Based Expert System, generates information and knowledge on the state of corrosion in an oil refinery’s equipment (Irgens and Landryova, 2006). This information system then makes this knowledge available to refinery workers through SCADA screens. The information presented on the SCADA screens can be specifically selected for specific tasks with the assistance of DSS. The DSS assists in the sharing of information between employees on knowledge obtained from the SCADA system.

Another aspect of the oil industry, is the use of technology and information systems to process chemical processes, and share this knowledge across the industry. According to Aldea et al. (2004), the oil industry makes use of an integrated prototype multi-agent chemical processing system, to process information of petroleum products and agents. This information is then shared, processed, retrieved, and stored across a web system and a team configuration system for the chemical engineers (Aldea et al. 2004). Studies by Edwards (2008) and Masoud, Lofti & Victor (2004) show that the oil and gas industry is making use of intelligent technology like neural computing, fuzzy reasoning, and evolutionary computing to interpret and analyze data obtained from the oil exploration and drilling sites. These technologies make up a large part of the knowledge management systems of the oil and gas industry, as they make up the largest system that interprets and analyzes data, and turns into information, and into knowledge for the engineers and scientists to comprehend. The study of Masoud, Lofti & Victor (2004) also shows that in this industry, such technologies are integrated with information, communication technology like videos, screens, internet, to transfer and share the knowledge. Transference and sharing of knowledge between the specialists in this industry is possible with the use of technologies that allow videoconferencing and teleconferencing across great geographically dispersed regions.

Moreover, the review of literature shows that, knowledge management systems within this industry are innovative and integrated. This is because they are based on up-to-date intelligent computer and software technologies (Edwards, 2008). Edwards (2008) and Aldea et al. (2004) find that knowledge management systems are integrated to support employees in not only carrying basic knowledge management processes of retrieval, collection, storage, analysis, transfer, and sharing but also engineering and scientific processes. the knowledge management systems in this industry incorporates processes like uncertainty analysis, risk assessment, interpretation, and analysis of data, data mining and fusion, and knowledge discovery (Masoud, Lofti & Victor, 2004). These systems assist in the management of information from employee profiles, prices of oil and gas, business processes, understanding of cash flow, production cycle, and maintenance strategies. Masoud, Lofti & Victor, (2004) identified in their study that the oil and gas industry makes use of intelligent and integrated information systems to handle information from maintenance management, research and development, and share it from the research community. Therefore, knowledge management system in the oil and gas industry is innovative, integrated, intelligent, and value added because it uses knowledge management system architecture that is current, integrative, and intelligent.

4.3 Knowledge Management System Issues in the Oil & Gas Domain

the review of literature shows that the gas and oil industry has taken advantage of knowledge management approaches for decades. Consequently, the industry has seen rapid changes, as knowledge management has assisted the industry to manage mergers, explore the advances of technology, manage acquisitions, carried out extensive offshore drilling, and managed environmental issues. Knowledge management plays a major role in making operations in the oil and gas industry more effective and efficient. However, application of knowledge management initiatives has not been easy as the industry faces several problems, discussed in detail in this section.

4.3.1 Knowledge Development and Capturing

One of the major challenges of application of knowledge management and knowledge management systems initiatives in the oil and gas industry has been the challenge of effective knowledge capturing and development. This is because, the oil and gas industry information development and capturing, has faced problems arising from new technologies, new partners, and outsourcing (Barrow, 2001). The challenge is that these management approaches provide new and dynamic ways of managing information requiring the constant improvement of knowledge management approaches. Moreover, the industry faces challenges in coordinating the geographically dispersed workforce in offering support to knowledge management development and knowledge capturing (Leavitt, 2002). This is complicated with the need for these teams to offer technology support, asset management, and knowledge transfer capabilities to knowledge development and capturing initiatives (Barrow, 2001). The geographical dispersion of teams especially specialists makes it difficult for the industry to apply knowledge development and capturing techniques or processes, behaviors, and tools, which deliver the right information to the right teams in the right content, at the right time, and within the right context (Reinmoeller & Van Baardwijk, 2005). The issues of this challenge is that it prevents teams from making the best decisions, creation of innovative ideas, and therefore, preventing the industry from exploiting new business opportunities (Leavitt, 2002).

The other challenge to knowledge development and capturing are business issues involving capacity management, environmental issues, and cost reduction. These business issues present the oil and gas industry challenges in creating knowledge management initiatives that can forecast, schedule, schedule, process, and use innovative techniques (Reinmoeller & Van Baardwijk, 2005). Moreover, such business issues common in the current business world present challenges to knowledge management initiatives by making it difficult to improve the convenience and speed (Leavitt, 2002). In addition, these business issues make it difficult of knowledge management initiatives to expand and address point-of-sale adoption of technology and the achievement of effectiveness of procedure.

4.3.2 Knowledge Retention and Sharing

Studies by Edwards (2008) show that the industry makes use of knowledge development and capturing techniques to retain and share information from different sectors like engineering, exploration, science, and management. However, these functions are hampered by challenges from new and increasingly pertinent issues in operations like the retention of valuable knowledge especially during the period when workforce ages. Moreover, knowledge retention and sharing in the sector is hampered by an increasing and diminishing efficiency in the communities of practice affected by workforce rates (Pauleen et al., 2007). Moreover, the industry is facing challenges arising from the fine-tuning of best practices by many companies, which transfer process with the use of content management systems (Van den Berg & Popescu, 2005). In such fine tuned environments, it is difficult for the workforce to retain and share knowledge especially in the communities of practice, which further reduces the downtime in oil and gas field sites across the world (Leavitt, 2002). Moreover, knowledge retention and sharing faces challenges from the many mergers and acquisitions that are a common business practice with the oil and gas sector (Pauleen et al., 2007). The mergers and acquisitions lead to major turnover rates, growth, and contraction fluctuations of workforce, and internal deployments making application of basic knowledge management initiatives a challenge (Leavitt, 2002; Reinmoeller & Van Baardwijk, 2005). Studies indicate that according to the Society for Petroleum Engineers, the median age for employees is 47. The studies also indicate that the turnover rates continually shift since the attrition rate in the last decade was at 44 by 2010, among oil engineers. This indicates that in the last two years the industry has lost approximately 231,000 years of accumulated engineering or specialist knowledge and experience due to retirement. Therefore, making the retention and sharing of knowledge difficult for knowledge management initiatives since, almost half of the workforce in the new decade will be new (Van den Berg & Popescu, 2005). In addition, the retention and sharing of knowledge is hampered by the loss of more than sixty percent of employees in the upstream gas and oil companies, along with their knowledge and skills. Therefore, the largest challenge for the oil and gas industry’s knowledge management retention and sharing initiatives is the high attrition rates or brain drain phenomenon.

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