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The purpose of this paper is to understand the impact of digital technologies adoption on the forms of organization of large architecture and engineering (A/E) firms. Network theory has attracted scholarly and managerial attention, particularly from the perspective of the changes of project organization. However, little research focuses on network theory as a lens for understanding and managing the new forms of firms’ organization. Additionally, conventional organizational analyses are hampered by the lack of methods for understanding the changes in roles and relationships due to the adoption of digital technologies and examining their impact on organizational structures.

To address this gap, this research adopted a mixed-method case-study approach. This approach combined interviews, regular check-ins, and document analysis with data mining and social network analysis (SNA) to capture the changes of intra-organizational roles and relationships and for understanding their impact on the firm’s organizational structure. Using the data gathered, the authors created a dendrogram that shows the formal organizational structure, a sociogram that displays the informal organizational structure and a network map that visualizes the interplay between the two structures.

From this analysis, the authors identified four main findings: informal roles – as go-to people for advice and information about digital technologies – play within A/E firms facing digital transformation; such go-to people operate through informal networked relationships and beyond their formal roles; most of these relationships do not overlap with the formal reporting relationships; the combination of both these roles and relationships create an informal social network. The authors also show how managers can use SNA to understand the changes in roles and relationships due to the adoption of digital technologies and to diagnose their impact on organizational structures.

This research contributes to the literature of organizational design and change management from a network perspective in the context of the digital transformation of large A/E firms. It provides a systematic data-driven approach to understanding the changes of intra-organizational roles and relationships within A/E firms facing digital transformation and to diagnosing the impact of these changes on firms’ organizational structures.

Facilities management (FM) plays a key role in the performance of businesses to ensure the comfort of users and the sustainable use of natural resources over operation and maintenance. Nevertheless, reactive maintenance (RM) services are characterised by delays, waste and difficulties in prioritising services and identifying the root causes of failures; this is mostly caused by inefficient asset information and communication management. While linking building information modelling and the Internet of Things through a digital twin has demonstrated potential for improving FM practices, there is a lack of evidence regarding the process requirements involved in their implementation. This paper aims to address this challenge, as it is the first to statistically characterise RM services and processes to identify the most critical RM problems and scenarios for digital twin implementation. The statistical data analytics approach also constitutes a novel practical approach for a holistic analysis of RM occurrences.

The research strategy was based on multiple case studies, which adopted university campuses as objects for investigation. A detailed literature review of work to date and documental analysis assisted in generating data on the FM sector and RM services, where qualitative and statistical analyses were applied to approximately 300,000 individual work requests.

The work provides substantial evidence of a series of patterns across both cases that were not evidenced prior to this study: a concentration of requests within main campuses; a balanced distribution of requests per building, mechanical and electrical service categories; a predominance of low priority level services; a low rate of compliance in attending priority services; a cumulative impact on the overall picture of five problem subcategories (i.e. Building-Door, Mechanical-Plumbing, Electrical-Lighting, Mechanical-Heat/Cool/Ventilation and Electrical-Power); a predominance of problems in student accommodation facilities, circulations and offices; and a concentration of requests related to unlisted buildings. These new patterns form the basis for business cases where maintenance services and FM sectors can benefit from digital twins. It also provides a new methodological approach for assessing the impact of RM on businesses.

The findings provide new insights for owners and FM staff in determining the criticality of RM services, justifying investments and planning the digital transformation of services for a smarter provision.

This study represents a unique approach to FM and provides detailed evidence to identify novel RM patterns of critical service provision and activities within organisations for efficient digitalised data management over a building’s lifecycle.