Using big data to improve the performance management: a case study from the UAE FM industry

Purpose: This paper aims to explore how big data analytics (BDA) collected and stored through specific data software [Construction Operations Building Information Exchange [COBie], integrated workplace management systems [IWMS], computer aided facilities management (CAFM), etc.] can play an essential role in improving the performance management system in the facility management (FM) industry. It defines the big data components and explores the benefit of BDA in any business through an extensive literature review and a pilot case study in the UAE. Design/methodology/approach: The research was carried out based on a qualitative approach. It attempts to identify through a case study how the data collected and the technologies that go along with will increase the functionality and the efficiency of the FM services. The research studies the implementation of a big FM organization, hereafter referred as “M” of software that exports the data collected from COBie and the computer aided facilities management (CAFM) system and shapes them into input to improve the performance of the FM service providers. The study includes two components in anticipation of providing a complete picture: first, five semi-structured interviews with industry experts and company employees representing the hierarchy of the staff, i.e. top, middle and operational levels; one director, two managers and two operational-level employees were interviewed to determine the current situation of the company in terms of BDA; and second, detailed documents and archives records review for the data collected on a randomly chosen sample of facilities for the period 2013-2015. The interviews were designed to achieve two specific objectives. Primarily, they were aimed at collecting empirical evidence on the existing status of big data within the UAE FM context and at investigating the importance of the data collected for performance measurement in the industry as supported in the literature. Second, these interviews sought to identify any critical issues that need to be addressed within the data collection process when devising the big data platform for FM. Findings: The paper seeks to provide a guideline to the service providers in the FM market to understand the importance of big data to be shared from the design and construction to the operational phase as it improves their operational performance. Originality/value: This paper studies the impact of big data on the FM performance management, a very recent topic where only few researches were conducted earlier.