Knowledge retention in oil and gas industry – the case of contract workforce

M. Saleem Ullah Khan Sumbal, Irfan Irfan, Susanne Durst, Umar Farooq Sahibzada, Muhammad Adnan Waseem, Eric Tsui

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Purpose: The purpose of this article is to investigate how organization retain the knowledge of Contract Workforce (CWF) and to understand the associated challenges in this regard. Design/methodology/approach: Adopting an inductive approach, 15 semi-structured interviews were conducted with senior managers, project heads and consultants working in leading oil and gas companies across eight countries (USA, Australia, UAE, KSA, Pakistan, UK, Thailand and Russia). Thematic analysis was carried out to analyze the data collected. Findings: CWF appears to be a significant source of knowledge attrition and even knowledge loss in the oil and gas sector. There are various risks associated with hiring of CWF, such as hallowing of organizational memory, repeated training of contractors, no knowledge base, workforce shortage among others which can impede the knowledge retention capability of O&G companies in the context of contract workforce. Various knowledge retention strategies for CWF have been revealed, however, there is interplay of various factors such as proportion of CWF deployed, proper resource utilization, cross-functional multi-level teams' involvement and strength of transactional ties. Maintaining strong relationships (Transactional ties) is crucial to maintain a virtual organizational memory (partial knowledge retention) and to follow a adopting a rehired when required policy. Originality/value: The knowledge retention issue in the context of CWF has not be addressed in past researches. This article attempts to fill this gap.

Original languageEnglish
Publication statusAccepted/In press - 2021


  • Contract workforce
  • Knowledge loss
  • Knowledge retention
  • Knowledge risks
  • Oil and gas

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science (miscellaneous)
  • Engineering (miscellaneous)
  • Social Sciences (miscellaneous)

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