Drivers and challenges associated with the implementation of big data within U.K. facilities management sector: an exploratory factor analysis approach

Ashwini Konanahalli, Marina Marinelli, Lukumon Oyedele

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The recent advances in Internet of Things (IoT), computational analytics, processing power, and assimilation of Big Data (BD) are playing an important role in revolutionizing maintenance and operations regimes within the wider facilities management (FM) sector. The BD offers the potential for the FM to obtain valuable insights from a large amount of heterogeneous data collected through various sources and IoT allows for the integration of sensors. The aim of this article is to extend the exploratory studies conducted on Big Data analytics (BDA) implementation and empirically test and categorize the associated drivers and challenges. Using exploratory factor analysis (EFA), the researchers aim to bridge the current knowledge gap and highlight the principal factors affecting the BDA implementation. Questionnaires detailing 26 variables are sent to the FM organization in the U.K. who are in the process or have already implemented BDA initiatives within their FM operations. Fifty-two valid responses are analyzed by conducting EFA. The findings suggest that driven by market competition and ambitious sustainability goals, the industry is moving to holistically integrate analytics into its decision making. However, data quality, technological barriers, inadequate preparedness, data management, and governance issues and skill gaps are posing to be significant barriers to the fulfillment of expected opportunities. The findings of this study have important implications for FM businesses that are evaluating the potential of the BDA and IoT applications for their operations. Most importantly, it addresses the role of the BD maturity in FM organizations and its implications for perception of drivers.
Original languageEnglish
Number of pages14
JournalIEEE Transactions on Engineering Management
Early online date17 Jan 2020
Publication statusE-pub ahead of print - 17 Jan 2020



  • Analytics
  • Big data (BD)
  • Facilities management (FM)
  • Technology implementation

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