Developing Critical Success Factors (CSF) for Integrating Building Information Models (BIM) into Facility Management Systems (FMS)

Abstract

Current practices in the construction industry could negatively affect the long lifecycle of building management due to the lack of information and stakeholder management. The purpose of this paper is to identify the critical success factors (CSFs) of integrating BIM models into facility management systems (FMS). This paper conducted a series of semi-structured interviews with industry experts in the FM sector. It used a structured questionnaire to identify the hierarchy arrangement of the identified CSFs using statistical analogies. The findings demonstrated a robust consistency with significant correlation, alongside a strong correlation established using Spearman’s rank correlation coefficient and strong agreement using Kendall coefficient. Additionally, the Relative Importance Index (RII) was employed to prioritize factors according to the professionals’ assessments, yielding the subsequent impact ranking: (1) define the OIR, AIR, and FM information requirements; (2) acquire correct files, data, and formats; and (3) update of information requirements during the defect liability period (DLP). These findings would help in assisting the management of information during FM operations by establishing clear guidelines to be added into the EIR in the early project initiation stages for a successful integration of BIM-FMS for more efficient life cycle management, operation, and maintenance by the FM.

1. Introduction

There are more opportunities to leverage in FM. According to [1], existing facilities have not yet fully explored the benefits of integrating BIM-FM system, as most are designed traditionally using CAD. BIM has been available and used for decades, but its utilization focuses on the design and construction phases more, without extending it to facility management [1]. Despite this issue, BIM has gained significant attention and high demand for its utilization in the FM industry [2]. However, it is still challenging for FM to aid in accelerating the process and be adequate for the cost solutions, and there are specific skills required to use it. According to [3,4], one significant issue hindering the use and optimization of BIM in FM is accuracy in the data capturing and generation of the model. The construction industry does not comprehend FM work nature and needs, especially with BIM [2]. Furthermore, building information management (BIM) is known to be a multi-dimensional database for FM; it offers structured and organized information management solutions throughout the facility lifecycle [5]. It helps improve the fragmentation of information delivered during the handover. It is also used as a bridge to pave the way to a better outcome between BMS, analysis, and BMS and structuring [5]. However, most projects only scrape the surface of the utilization of BIM in FM, and they fail to benefit fully from BIM-FM systems integration. Ref. [5] mentioned that the problem stems from acquiring underdeveloped BIM data that lack some specific FM requirements; due to the delivery of models without considering post-construction needs at the beginning, refs. [6,7] discussed the use of BIM for FM owners as a source of information to support the management and planning in FM activities. In addition to the requirement of acquiring adequate standards, workflows, and tools, FM organizations could fully benefit from integrating BIM with their systems by tailoring BIM specifications and guidelines (e.g., naming conventions, standards, LoD, objects and line styles, units, etc.) that suit their requirements from the start of the project [8].

Moreover, BIM technology in FM has proven effective in some developed countries, with remarkable outcomes; it is described as a tool for improving project delivery and quality and facilitating collaboration between project stakeholders [9]. External and internal factors affect the applicability of BIM-FM integration, as ref. [9] explained. External factors include government regulations, unfavorable contractual requirements, and a lack of mandated BIM standards. On the other hand, internal factors are mostly related to project stakeholders like consultants and contractors, and they include collaboration frameworks, organization setups, support of top-management, technical factors, and training. Furthermore, critical success factors (CSFs) must be present at the beginning of the project to prevent these issues. According to [9], CSFs are defined as elements that foresee achievements; they can be elements or agendas to be followed by stakeholders for BIM-FM integration success. Most importantly, CSFs are vital factors that prevent delay, ensure successful processes, and increase project performance and efficiency [9]. The purpose of this paper is to identify the critical success factors (CSFs) of integrating building information models (BIM) into facility management systems (FMS) and further propose their integration into the employer information requirements (EIR). To overcome the challenges and optimize the benefits of such integration for project stakeholders, the critical success factors are defined through three phases: data collection, data analysis, and data validation and classification. The study combines an extensive literature review with semi-structured expert interviews and a Delphi-based survey to capture industry insights. Advanced statistical techniques, including the Relative Importance Index, Spearman’s rank correlation, and other correlation analyses, were employed to validate and rank the identified factors. The outcome of this research is a set of empirically validated CSFs explicitly linked to EIR elements, offering practitioners practical guidance for implementing BIM in facility management contexts. By bridging the gap between theoretical knowledge and practical requirements, this research contributes critical insights to ensure data consistency, improve collaboration, and support effective decision making in BIM-FM integration.

2. Literature Review

2.1. FM Systems (BMS) and (CAFM)

During the operation and maintenance phase, one of the most effective monitoring systems used is the building management system (BMS). The major focus of the BMS is to ensure the safety and effectiveness of the facility’s operation while monitoring the utilization of its connected systems, like HVAC, central heating, water, technical steam, sprinklers, and electrical monitoring systems [10]. It guarantees improved comfort, notably increased safety, and efficient consumption of resources [10]. As explained by [11], the BMS, an automation system, is a significant element when creating energy-efficient smart grids. A successful integration of the BMS into a vast system network requires standardized harmonization [11]. It also needs an accurate interaction between main elements such as building automation and control systems (BACS), energy data management systems, and advanced metering interfaces (AMI) [11]. Furthermore, a sensor network is the most vital fundamental element in a BMS system; the design stage must include specifications concerning the required accuracy for the network [12]. Building information modeling (BIM) offers an opportunity to store the necessary sensor specifications into the designed sensor network on the model. According to [12], BIM is considered as an integrated and structured data library that allows the smooth contribution of stakeholders to the coordinated information. It is also considered the most efficient platform for storing building and performance information to define sensors’ requirements during integration with the BMS. The geometry of the building, lighting, HVAC systems, and the performance hierarchy that defines the requirements of the sensors must all be included in the BIM before passing it to the network design tool and before the integration with the BMS [12].

2.2. Integration of BIM-FM Systems

The daily use of the BMS by facility managers requires a practical, efficient way of dealing with the data by taking full advantage of combining BIM with the BMS for standard operations improvement [13]. Instead of integrating static information from fragmented sources, ref. [13] advised introducing an information-rich BIM model that offers real-time data through the integrated BMS system. This allows facility managers to interact with the built environment on time for an enhanced user interface rather than the traditional BMS integration methods [13]. The gaps in integrating the BMS data into BIM have been noted as significantly affecting the graphical energy information provided by manual inputs of energy management systems. According to [14], several advantages of the integration of BIM-BMS can be noted, including better accessibility of BIM data, better validation, and better continuous on-time updates on the facility. Moreover, BIM processes allow energy consumption reduction through energy analysis and operations productivity improvements through the creation and simulation tools of the model [14]. To benefit from these advantages, it is essential to integrate BIM requirements and specifications from the start of each project.

2.3. Employer Information Requirements (EIR)

Awareness across the FM industry is growing rapidly, yet there are inconsistencies regarding the maturity and utilization of BIM [15]. The importance of the integration and involvement of FM in early project stages is stressed for better integration of BIM with FM systems. It is discussed that creating well-structured and specified employer information requirements (EIR) allows all stakeholders to start with the end result in mind [16]. The EIR is a pre-tender document specifying the information required to be delivered and the standards as an integral part of the project handover. The EIR as explained by [16] offers opportunities to encourage collaboration between project stakeholders to agree on what BIM data they need to create, the associated cost, and how they work together to achieve the result in the early stages of BIM projects. It also helps clients and FM define their requirements from the early stages and during the project construction phase; this provides clear guidelines for the design and construction teams. Ref. [16] stressed the importance of the EIR for clients and FMs and considered it a starting point for any BIM project. It helps establish the data required to guarantee future optimization of assets and operations and encourages stakeholders to consider the LoD and complexity alongside the project specifications and objectives. The EIR is directly connected to the RIBA Plan of Work (2013) and other significant BIM standards that underpin the BIM integration process in the FM industry. The EIR is structured into three main categories that cover all the project requirements that can be linked with the CSFs to achieve successful BIM-FM integration, as shown in

Table 1. The EIR structure.

No.	EIR Category	Guides
1	Management Requirements	Applicable standards and guidelines
		CIC BIM protocol
		Project roles and responsibilities
		Existing client CAFM/IWMS or enterprise asset management systems
		Model creation and ongoing management
2	Technical requirements	Software
		IT and system performance constraints
		Data exchange formats
		Common coordinates system
		Levels of definition
		Specified model and information formats
		Site information and floor and room data information
3	Commercial Requirements	Exchange of information in line with RIBA project stages
		Supplier BIM assessment form
		BIM tender assessment

Reference [16].

.

Therefore, this study aims to link the above-defined EIR with the CSFs to achieve successful BIM-FM integration.

2.4. Critical Success Factors (CSFs)

Critical success factors (CSFs) are required to be present at the beginning of the project to prevent the occurrence of issues that arise during the integration process.

Table 2. CSFs key points and definitions.

No.	References	CSF Definition	Key Points	Category
1	[17]	“A limited number of areas in which results, if they are satisfactory, will ensure successful competitive performance for the individual, department or organization”	Competitive performance	Policy
2	[18]	Factors that affect the construction process	Construction process	Product Process
3	[19]	Drivers or enablers whose presence can cause success and their absence can cause failure in the implementation and adoption of building information modeling	Drivers or enablers Presence = success Absence = failure	Product
4	[20]	CSFs are the most significant factors in preventing delays in the project, increasing project performance, and ensuring success for construction projects	Prevents delay, increases project performance, and assures success	Process/E.G QA/QC
5	[21]	Factors alleged as significant for the implementation of BIM are both on organizational and project level	Significant	Product
6	[22]	Drivers or enablers for successful risk assessment and management practices by way of clarification between drivers and enablers	Drivers or enablers Successful risk assessment Management practices	Product Process Policy
7	[23]	Elements that are seen as essential and that facilitate successful implementation of new systems	Essential elements that facilitate success	Product
8	[24]	“Denotes a certain element which significantly contributes to and is remarkably vital for the achievement of a project”	Significant contribution	Product
9	[25]	“Elements that foreseen achievement instead of simply the unadulterated survival of a construction project”	Foreseen achievement	Product
10	[26]	CSF can be defined as certain rules, executive procedures, and environmental conditions that are felt to have an important impact on whether or not a project will succeed	Certain rules Executive procedures Environmental conditions	Policy Process
11	[27]	CSFs are objects or agendas to be put in place for an organization or project to succeed	Objects or agendas	Process
12	[28]	CSFs have been defined as foundations that determined the successful performance of an individual, department, or organization [28]; the identification of CSFs is needed to enhance project performance and organization performance	Foundation	Policy

presents several definitions captured from the literature, categorized into the 3PT analogy categories (Policy, Product, Process, and Technology) to identify the suitable definitions related to the BIM-FM integration.

After defining the CSFs, the literature fails to connect these factors directly to the EIR framework. Therefore, this paper addresses this gap by identifying CSFs from the literature, validating them through expert input, and proposing their alignment with the EIR.

2.5. The Gap and the Selected Critical Success Factors from the Literature

A gap in the existing literature has been identified concerning the alignment of critical success factors (CSFs) with the employer information requirements (EIR), which is a crucial document defining the success of BIM-FM integration during planning and prep for pre-project start and early stages of a project. While prior studies have examined CSFs related to the successful transfer and ongoing management of 3D BIM models, alphanumeric data, and documents for FM systems, such as [9,29,30], few have connected these factors explicitly to the EIR framework. Therefore, this paper aims to identify specific CSFs derived from the literature and validate and prioritize them through expert input, with the goal of proposing a structured alignment with the EIR.

Table 3. Selected CSFs items from the literature.

Main Theme (MT)	Category	Reference	Sub-Categories	3PT Category
MT-3	Addressing and overcoming perceived barriers and challenges to the adoption and use of BIM	[29]	Upskilling FM teams to empower them for successful engagement in BIM projects	Policy
			Setting realistic expectations of what BIM can deliver	Policy
			Understanding the link between BIM, CAFM, and FM management	Technology
MT-4	Making the benefits of BIM to FM transparent, realistic, and achievable	[29]	Planning realistic timelines for the realization of benefits	Policy
			Ensure access to good quality data from one place	Product/policy
			Improving the handover from construction to operation	Process
	BIM investment and organization readiness for change	[31]	Organizational re-engineering for BIM	Policy
			Adequate investment in BIM	Policy
	FM leaders and staff commitment to BIM	[31]	Early involvement of in-house FM project teams	Policy
			Availability of competent staff	Policy
MT-7	Clarifying the role and tasks of FMs in the BIM process	[29]	Defining the EIR, OIR, AIR, and FM information requirements to support the AM strategy	Policy
			Writing key BIM documents and guiding clients	Product
			Identifying client needs and using FM know-how to help improve BIM project outcomes	Process
	BIM policy	[32]	Governments need to establish a specific policy for adopting BIM on all projects	Policy
			Specific government departments are responsible for setting BIM policy	Policy
			Specific organizations are to take responsibility for BIM implementation in the country	Policy
MT-8	Acquiring essential knowledge of key BIM standards/guidance documents for practical use in a BIM project	[29]	Using BIM standards and guidance in projects to achieve better outcomes for all stakeholders	Process/policy
			Other useful BIM guidance documents	Product
MT-9	Ensuring people have adequate BIM training and competency skills for successful engagement in BIM projects	[29]	Acquiring essential knowledge about BIM standards and guidance documents	Policy
			Sources for EIR guidance, BIM books and BIM training courses	Policy/product
	Accessible BIM hardware and software packages	[31]	BIM hardware and software availability	Technology
			Accessible BIM software vendors for FM	Technology
MT10	Ensuring the “successful transfer and on-going management” of “3D models, alphanumeric data, and documents for CAFM/FM systems”	[29]	Planning the data transfer and quality checking process for BIM projects	Process
			Planning what data to collect and how to transfer it into FM management systems	Process
			Using standards and specific classification systems to ensure data are well-structured to enable easy transfer from BIM models using COBie/IFC	Technology
			Bi-directional data transfer and improving data handover processes and future possibilities	Process
	Product information sharing	[32]	Capacity of the BIM implementation system to exchange information among different BIM and non-BIM systems without data loss	Technology
			Make explicit design information available to stakeholders so they can easily understand and evaluate the design, construction, or operation intent.	Product

presents elected CSFs from the literature, which are categorized using the 3PT analogy (Policy, Product, Process, and Technology) and form the basis for integration with expert insights.

3. Research Methodology

3.1. Research Literature and Study Workflow

The research methodology for this study adopted a qualitative and quantitative research approach through the exploration of the literature and semi-structured interviews with industry experts for data collection, a workshop, and a survey for data validation and ranking. The literature review was conducted to define the work nature of FM systems and their integration requirements, identify the EIR structure for future CSF alignment, and identify selected CSFs related to the successful transfer of BIM data to FM systems. The interview series helped capture integration processes from the project initiation stage, the final handover to FM, and the operation stage. It also helped define obstacles, challenges, and major problem areas faced by the FM when receiving the information from the contractors in addition to a brief definition of the success factors that would have aided the process from the start.

Table 4. Research Participants.

No.	Interviewees	Participants	No. of Interviews
I-1	University’s Facility Management team—Doha	1 FM Manager	1
I-2	A Smart City Facility Management team—Doha	- 2 FM Managers - 1 ICT Engineer/Manager - 1 ELV Engineer - 1 GIS Engineer (FM) - 2 Engineers and 1 Architect (contractors) - 1 GIS Specialist (GIS Consultant)	4
I-3	Facility Management Consultants—Doha	- 1 General Manager - 1 Technology Manager	2
I-4	Public Transportations Facility Management—Doha	- 1 FM Manager - 1 FM Engineer	1
I-5	Sport Venues Facility Management team—Doha	- 1 FM Manager	1
I-6	Research Associate with FM experience—UK	- 1 Research Associate	1
	Total	16 Participants	10 Interviews

below introduces the interviewees who participated in this series, where each participant has a reference number. As this study is highly dependent on real-life experience, certain criteria were utilized to choose the participants. Therefore, participants must have at least 1–2 years of experience in both FM and BIM.

Furthermore, a workshop was conducted to analyze primary data collected from the literature and interviews, select specific relevant items, categorize them into the 3PT analogy, and propose an initial link to the EIR categories. The survey was distributed among experts with BIM-FM experience to validate and identify a hierarchy arrangement for the identified CSFs and further propose a final alignment with the EIR with the Delphi approach that was followed by [33]. Then, the CSF and data validation were carried out through consistency coefficients, as shown in [34]. A summarized process map of the research methodology is shown in Figure 1. The process map shows that the adopted research methodology was conducted in three phases, where each phase had certain tasks and outcomes that were utilized in the next phase.

3.2. Statistical Analysis

To identify and validate the hierarchy of critical success factors (CSFs) for the integration of building information modeling (BIM) into facility management systems (FMS), a two-round Delphi survey was conducted involving a selected group of experts with experience in facility management (FM) and BIM. Participants ranked and validated various identified CSFs in three key categories: (1) guidance, (2) management and planning, and (3) quality. The analysis methods used included (1) the Relative Importance Index (RII), (2) pairwise correlation matrix, (3) Kendall coefficient of concordance, and (4) Spearman’s rank correlation test.

3.2.1. Relative Importance Index (RII)

The Relative Importance Index (RII) is a widely recognized metric for ranking the factors examined in this study, and it is commonly employed globally for classification purposes. Ref. [34] used it to study the critical success factors to fast-track construction projects.

Additionally, it has been utilized to prioritize factors based on employer satisfaction regarding industrial training [35]. The following equation is used in this project for calculating RII:

This is example 1 of an equation:

$$RII={\displaystyle \frac{\sum {\mathit{W}}_{\mathit{i}}}{\mathit{A}.\mathit{N}}}={\displaystyle \frac{{\mathbf{1}\mathit{n}}_{\mathbf{1}}+{\mathbf{2}\mathit{n}}_{\mathbf{2}}+{\mathbf{3}\mathit{n}}_{\mathbf{3}}+{\mathbf{4}\mathit{n}}_{\mathbf{4}}+{\mathbf{5}\mathit{n}}_{\mathbf{5}}}{\mathbf{5}.\mathit{N}}},$$

(1)

where

W—the respondent’s weighting of each factor, which can range from 1 to 5.

n_i—he number of respondents for value of i.

A—the highest weight (in this project is 5).

N—the total number of respondents on the questionnaire.

3.2.2. Pairwise Correlation Matrix

The purpose of the pairwise correlation matrix is to measure the strength and direction of linear relationships between pairs of continuous variables. It helps to identify clear patterns, redundancy, or overlaps among critical success factors. If two CSFs have high positive correlation, it means experts consider them closely related or interdependent, which can influence how these factors are managed practically.

3.2.3. Kendall Coefficient of Concordance (W)

The Kendall coefficient is used to assess the level of agreement among multiple experts in their rankings of CSFs. Since the study involved multiple expert responses in Delphi rounds, Kendall’s W is ideal. It quantifies consensus clearly, indicating how much the experts agree on the prioritization of factors. High Kendall’s W means experts strongly agree, increasing findings’ credibility, as

Table 5. Kendall Coefficient Interpretation.

W	Interpretation
0	No agreement
0.10	Weak agreement
0.30	Moderate agreement
0.60	Strong agreement
1	Perfect agreement

explains. It specifically accommodates ordinal data (ranking data), which suits the expert-based Delphi method perfectly.

Equations (2) and (3) correspond to Kendall’s coefficient of concordance (W), which measures the agreement among multiple rankings.

$$W={\displaystyle \frac{12S}{m^2\left(n^3-n\right)-mT}},$$

(2)

$$S=\sum _{i=1}^n{\left(R_i-\overline{R}\right)}^2$$

(3)

where

W—Kendall’s coefficient of concordance, which ranges from 0 to 1.

S—the sum of squared deviations of ranks from the mean rank.

$R_i$—the sum of ranks for the i-th subject (or item) across all judges (raters).

$\overline{R}$—the mean of the ranks.

n—the number of subjects (or items) being ranked.

m—the number of judges (raters) who rank the subjects.

T—a correction factor for tied ranks, which accounts for ties in rankings.

3.2.4. Spearman’s Rank Correlation Test

The spearman’s rank coefficient is used to measure the consistency or reliability of ordinal rankings among participants across survey rounds. It was selected because research data involve ordinal rankings (experts ranking CSFs), as they does not require the assumption of normally distributed data, making them robust for ordinal scales used in expert ranking exercises. This ensures the stability and reliability of results across different survey rounds, therefore validating the robustness and repeatability of the study.

This non-parametric test, which does not necessitate the assumption of data normality, is computed using the following equation:

$$\mathit{r}=1-{\displaystyle \frac{6\sum {\mathit{d}}^2}{{\mathit{n}}^3-\mathit{n}}},$$

(4)

where

r—Spearman’s rank correlation coefficient.

d—difference between ranks assigned to variables for each factor.

n—number of identified factors in the study (in this project, it is 22).

The coefficient values can vary from +1 to −1, where +1 represents a perfect positive relationship, and −1 denotes a perfect negative relationship. The strengths of the intermediate values are outlined in

Table 6. Spearman’s Strength Dependance.

Value of the Spearman’s Coefficient |Absolute Value|	Strength of Correlation
0.00–0.19	Very weak
0.20–0.39	Weak
0.40–0.59	Moderate
0.60–0.79	Strong
0.80–1.00	Very strong

.

4. Findings

4.1. Identified CSFs—Interviews

After acquiring the EIR categories for the CSFs alignment and the CSFs that are related to BIM-FM integration from the literature review, the data were enhanced and advanced by experts’ inputs to provide a real-life experience point of view. Since the interview participants were carefully selected to have experience in the BIM and FM field, their inputs discussed the critical factors of the integration process across all the project stages. Moreover, the interviews discussed the CSFs in relation to FM systems: building management systems (BMS) and computer aided facilities management (CAFM).

Table 7. Identified CSFs from the interviews.

No.	Critical Success Factors (CSFs)	BMS						CAFM
		I-1	I-2	I-3	I-4	I-5	I-6	I-1	I-2	I-3	I-4	I-5	I-6
1	Asking for BIM from the start of the project			●	●	●		-		●	-	●
2	Providing BIM as part of the as-built submission in the handover			●	●	●		-		●	-	●
3	Adding guidelines for data usage in COBie in the specifications—preliminary stages			●	●	●		-		●	-	●
4	Issuing information capturing guidelines and how to transfer them into CAFM from the start of the project + asset information code language			●		-		-		●	-	●
5	Successful communication of FM requirements with the client					●		-			-	●
6	Planning ahead to avoid conflicts and issues between stakeholders			●		●		-		●	-	●
7	Including BIM in the FM requirements in early stages			●	●	●		-		●	-	●
8	Acquiring correct files data and format—QAQC			●		●		-		●	-	●
9	Organization and coordination leading to standardized data collection			●		●		-		●	-	●
10	Stakeholders’ commitment to protocols					●		-			-	●
11	Client working closely with IT team (FM integrator) to know how to accomplish what is needed						●	-			-		●
12	Proper and synchronized working of the system and the model (BIM viewer, not opening in CAFM application—external plugin)						●	-			-		●
13	Visualization of asset location	●	●	●	●	●		-	●	●	-	●
14	The smaller the BIM model size, the more efficient	●	●	●	●	●		-	●	●	-	●
15	Automatic scheduling for the equipment—FM maintenance	●		●				-			-
16	Faster integrating process with the 2D to CAFM/BMS—reduced file size	●		●				-		●	-
17	The need for accurate scripts to identify mistakes and mismatches in the data—QAQC		-	●		●		-	●	●	-	●
18	Adjoined work, automated registry (easy search of assets, accuracy)—QAQC		●			●		-	●		-	●
19	Centralized command station/center (reducing manpower, increasing efficiency in operation, better response time, and smart operations)		●		●	●		-	●		-	●
20	Interfacing all systems into a centralized platform		●	●		●		-	●	●	-	●
21	Adapting the asset registry by the MC (accurate asset keys, unique codes, barcodes, etc.)—QAQC		●			●		-	●		-	●
22	Consultants’ reviews—QAQC		●	●	●	●		-	●		-	●
23	Strong supervision from top management		●			●		-	●		-	●
24	Correct set of information in the handover (drawings, DDC, device IO list, and asset registry)—QAQC		●			●		-	●		-	●
25	FM and integrator’s preliminary checks—QAQC		●		●	●		-	●		-	●
26	FM reviews—QAQC		●	●	●	●		-	●	●	-	●
27	Adapting new technologies by FM (e.g., BIM)		●	●		●		-	●	●	-	●
28	Collaborating with system integrators for easy conversion of 2D to 3D GIS software and 3D models		●					-	●		-
29	Confirming 2D CAD drawings have assigned points from asset registry—QAQC		●	●		●		-	●	●	-	●
30	Developing two platform versions—pre-production version (testing) and integrated platform production version (operation)		●					-	●		-
31	Accurate IFC IDs and automated codes—QAQC		●	●				-	●	●	-
32	Separate but compatible controlling and maintenance systems—BACS/SCADA and MMS				●			-			-
33	Connected asset codes and tags in the controlling system—QAQC			●	●			-		●	-
34	Responsible stakeholder to fix all hand over data during the defect liability period			●	●	●		-		●	-	●
35	Breaking down the data into a more structured qualification manual for everyone to use		●		●			-	●		-

Key: Blank = not mentioned; ● = mentioned; - = not applicable.

presents a summary of the identified CSFs from the interviews, where each participant has a reference number. The table shows the frequency of the mentioned CSFs between the participants and the FM systems. For example, for factors like visualization of asset location, the smaller the BIM model size, the more efficient, and FM reviews—QAQC—are mentioned by most of the participants, which indicates their importance. On the other hand, factors such as spate but compatible controlling and maintenance systems—BACS/SCADA and MMS—were not frequently mentioned or applicable, which indicates that this is less critical for integration.

4.2. Identified CSFs—Workshop

The workshop aimed to analyze the primary data collected from the literature and interviews, select specific relevant items, categorize them into the 3PT analogy, and propose an initial link to the EIR categories. Participants of this workshop included two architects with BIM experience, one architect with BIM-FM experience, and three FM managers.

Table 8. The identified CSFs linked to the EIR and the definition of MT10. MT10: Ensuring the “successful transfer and ongoing management” of “3D models, alphanumeric data, and documents” for CAFM/FM systems.

Category	Sub-Categories	CSFs	Link to EIR	3PT	Source
Guidance ST 0.1	FM Requirements ST 0.1.1	Define the OIR, AIR, and FM information requirements to support the AM strategy	Commercial - Defined BIM/Project deliverables	Policy	Literature
		Communicate FM requirements with the client (including BIM as part of the submission)	Management - Collaboration process - Delivery strategy for asset info	Process	Interviews
		Provide BIM standards and guidelines	Management - Standards Commercial - Defined BIM/project deliverables	Product	Interviews
		Early participation of FM	Management
			- Collaboration process	Policy	Literature Interviews
		Update of information requirements during the defect liability period (DLP)	Management - Compliance plan for model and data	Process	Interviews
	Client needs ST 0.1.2	Identify client needs and using FM know-how to help improve BIM project outcomes	Commercial - Client strategic purpose Management - Roles and responsibilities	Process	Literature
		Understand client’s IT requirements	Commercial - Client strategic purpose Management - Roles and responsibilities	Technology	Interviews
	Technical: Link between BIM-FM systems ST 0.1.3	Understand the link between BIM and FM management systems	Technical - Software platform	Technology	Literature
		Seamless data formats for the integration	Technical - Data exchange formats	Product Technology	Interviews
		Adapt necessary plugins for adequate operations of FM systems	Management - System performance	Technology	Interviews
		Scalable file size (BIM) for better control and visibility	Management - System performance	Product	Interviews
		Adapt systems that can be synchronized to reduce information loss	Technical - Software platform	Technology	Interviews
		Capacity of BIM implementation system to exchange information among different BIM and non-BIM systems without data loss	Technical - Data exchange formats	Technology	Literature
		The use of interoperable systems to convert 2D to 3D BIM in existing buildings	Management - Compliance plan for model and data	Technology	Interviews
		Adapt two versions for FM systems (pre-production and production versions)	Management - Systems performance	Product	Interviews
Planning/Management ST 0.2	Skills ST 0.2.1	Upskill FM teams to leverage BIM capabilities in FM (to participate in client proposal development)	Technical - Trading	Policy	Literature Interviews
		Adopt new technologies for FM systems	Technical - Software platforms	Product/Technology	Interviews
		Accessible BIM software vendors for FM	Technical - Software platform	Technology	Literature
	Expectations 0.2.2	Set realistic expectations of what BIM can deliver	Commercial - Defined BIM/project deliverables Management - Health and safety and construction design management	Policy	Literature
		Stakeholders’ commitment and compliance to BIM standards and protocols	Management - Roles and responsibilities	Policy	Literature Interviews
		Strong supervision from top management	Management - Roles and responsibilities	Policy	Interviews
		Compatible integration systems	Technical - Software platforms	Technology	Interviews
	Data ST 0.2.3	Plan the data transfer and quality checking process for BIM project	Management - Compliance plan for model and data	Process	Literature
		Bi-directional data transfer and improvement of data handover processes and future possibilities	Management - Collaboration process - Systems performance	Process	Literature
		Common data environment (CDE)	Management - Planning the work and data segregation	Product	Interviews
Quality ST 0.3	QA/QC 0.3.1	Ensure access of good quality data from one place (BIM)	Management - Planning the work and data segregation	Product Policy	Literature
		Three-dimensional visualization of asset locations	Management - Planning the work and data segregation	Technology Product	Interviews
		Acquire correct files data and format	Management - Compliance plan for model and data Technical - Data exchange format	Policy Product	Interviews
		The need for accurate scripts to identify mistakes and mismatches in the data	Management - Compliance plan for model and data	Product Process	Interviews
		Making explicit design information and making it available to stakeholders so that the design, construction, or operation intent can be easily understood and evaluated	Management - Model viewing - Model coordination, quality control, and clash detection process	Product	Literature
		Effective stakeholders reviews (consultants, contractors, and FM)	Management - Coordination and clash detection process - Compliance plan for model and data	Policy	Interviews
		Accurate data (drawings, DDC, device IO list, asset registry, IFC IDs, automated codes, asset keys, unique codes, barcodes, etc.)	Management - Planning the work and data segregation	Product	Interviews
		Connected asset codes and tags in the controlling system from the asset registry (existing buildings)	Management - Planning the work and data segregation	Product	Interviews
		Developing a structured qualifications manual (FM and integrator’s preliminary checks)	Management - Compliance plan for model and data	Process	Interviews

presents the results of the workshop. The table combined the data from phase one, categorized them, and linked them to the EIR through the participants’ guidance. The selected literature factors focused mainly on the main theme (MT10) and other themes related to BIM-FM integration.

4.3. Identified CSFs—Survey

4.3.1. Data Collection

After identifying the CSFs through the workshop that combined the literature review results and interviews, a survey was conducted to validate and identify a hierarchy arrangement for the identified CSFs and further propose a final alignment with the EIR. The survey was distributed among experts with combined knowledge and experience in FM and building information modeling (BIM) irrespective of their location. However, since this study focuses on expert review, the participants in the survey were very selective; therefore, the Delphi method was selected for this study. This means that the survey was conducted in two rounds among selected experts. Ref. [33] mentioned that the Delphi method helps create new ideas and evaluate and verify the importance of factors and groups.

Each survey had two sections: The first section had a brief description of the research and questions about the participants’ experience and background. The second section asked the participants to rank the CSFs of each category: guidance, management and planning, and quality. The total CSFs to be ranked were 34 in the first round and 35 in the second round. However, the difference between the first and the second rounds was the CSF recommendation section for each category in the first round.

In the first round, 15 experts were sent the survey. They were asked to rate the CSFs of each category and propose any factor that may be important to consider. The second round of the survey also had 15 responses, which verified the answers of the first round and the newly added factor from the first round.

Table 9. Expert Demographics.

No.	Position	FM Years of Exp.	BIM Years of Exp.
1	Facilities Manager	1–5	1–5
2	Facilities Manager	21+	6–10
3	Academic (Researcher in BIM-FM)	1–5	1–5
4	Engineer (Maintenance)	6–10	1–5
5	Facilities Manager	21+	21+
6	Researcher in IT for construction	1–5	6–10
7	Quantity Surveyor	11–15	1–5
8	Academic (Researcher in BIM-FM)	11–15	6–10
9	Academic (Researcher in BIM-FM)	1–5	6–10
10	Engineer	1–5	1–5
11	Academic (Researcher in BIM-FM)	6–10	16–20
12	Academic (Researcher in BIM-FM)	1–5	11–15
13	Facilities Manager	11–15	11–15
14	Academic (Researcher in BIM-FM)	11–15	11–15
15	Engineer (Implementation)	6–10	1–5

shows the expert demographics of the survey participants.

4.3.2. Analysis

The Delphi method was used since the participant sample was relatively small. This method includes two rounds of surveys followed by verification processes to evaluate the data’s consistency, correlation, and correctness.

Since the two rounds of surveys included different scales, it was recommended that we combine both rounds and complete the pairwise comparison into groups. The principal component analysis (PCA) combined the second section of the two survey rounds to form new variables ready for analytical tools. This means that each category of the CSFs, namely guidance, management, planning, and quality, was combined from round one and round two of the survey to analyze each category separately.

The analytical tools and techniques used to identify the data consistency and correlation were the pairwise correlation matrix, Kendall coefficient of correlation, and Spearman’s rank correlation test, which are explained in the paragraphs below.

Relative Importance Index

Upon determining the RII value, which spans from 0 to 1, ranking of the factors is conducted, with a higher RII value signifying greater influence. In this research, RII facilitates ranking factors according to the scores provided by respondents.

Table 10. RII Analysis.

	Factor		RII	RII Ranking
Guidance	A	Define the OIR, AIR, and FM information requirements to support the AM strategy	0.28	1
	B	Communicate FM requirements with the client (including BIM as part of the submission)	1.32	32
	C	Provide BIM standards and guidelines	1.4	34
	D	Early participation of FM	1.133333	27
	E	Update of information requirements during the defect liability period (DLP)	0.6	3
	F	Identify client needs and use FM know-how to help improve BIM project outcomes	0.92	12
	G	Understand client’s IT	0.826667	7
	H	Understand the link between BIM and FM management systems	0.666667	5
	I	Seamless data formats for the integration	1.133333	27
	J	Adapt necessary plugins for adequate operations of FM systems	1.053333	24
	K	Scalable file size (BIM) for better control and visibility	1.013333	20
	L	Adapt systems that can be synchronized to reduce information loss	1.013333	20
	M	Capacity of BIM implementation system to exchange information among different BIM and non-BIM systems without data loss	1.133333	27
	N	The use of interoperable systems to convert 2D to 3D BIM in existing buildings	0.866667	8
	O	Adapt two versions for FM systems (pre-production and production versions)	0.893333	10
Planning and Management	A	Upskill FM teams to leverage BIM capabilities in FM (to participate in client proposal and development	0.866667	8
	B	Adopt new technologies for FM systems	0.986667	17
	C	Accessible BIM software vendors for FM	0.906667	11
	D	Set realistic expectations of what BIM can deliver	0.8	6
	E	Stakeholders’ commitment and compliance to BIM standards and protocols	1.493333	35
	F	Strong supervision from top management	0.973333	14
	G	Compatible integration systems	0.973333	14
	H	Plan the data transfer and quality checking process for the BIM project	1.093333	25
	I	Bi-directional data transfer and improvement of data handover processes and future possibilities	1.013333	20
	J	Common data environment (CDE)	1	18
Quality	A	Ensure access of good quality data from one place (BIM)	1.32	32
	B	Three-dimensional visualization of asset locations	0.626667	4
	C	Acquire correct files, data and formats	0.586667	2
	D	The need for accurate scripts to identify mistakes and mismatches in the data	1.146667	30
	E	Making explicit design information and making it available to stakeholders so that the design, construction, or operation intent can be easily understood and evaluated	1.093333	25
	F	Effective stakeholder reviews (consultants, contractors, and FM)	1.013333	20
	G	Accurate data (drawings, DDC, device IO list, asset registry, IFC IDs, automated codes, asset keys, unique codes, barcodes, etc.)	1	18
	H	Connected asset codes and tags in the controlling system from the asset registry (existing buildings)	1.213333	31
	I	Developing a structured qualifications manual (FM and integrator’s preliminary checks)	0.973333	14
	J	Centralizing data access to ensure consistency and reduce the risk of working with outdated or inaccurate information	0.933333	13

presents the individual rankings of all factors. Moreover, participants were requested to assess the significance of various groups of related factors to gauge their impact.

Pairwise Correlation Matrix

This analysis quantifies the strength and direction of a linear relationship between two variables. The correlation coefficient ranges from −1 to 1, where a value of 1 denotes a perfect positive linear relationship, −1 indicates a perfect negative linear relationship, and 0 signifies the absence of a linear relationship.

The p-value is computed to assess the statistical significance of the correlation. A commonly accepted threshold in statistical analysis is the 5% significance level (p-value < 0.05). If the probability that the observed or more extreme correlation occurs due to random chance is less than 5% (p < 0.05), the correlation is considered statistically significant at the 5% level. This suggests that the likelihood of the observed correlation being a result of random variation is sufficiently low, providing reasonable confidence that a genuine association exists between the two variables. Conversely, suppose the correlation does not achieve statistical significance at this threshold. In that case, there is insufficient evidence to infer a true relationship, implying that the observed correlation may be attributable to random fluctuations rather than an actual underlying association.

For the guidance group:

• Table 11. Correlation Matrix for Guidance Group.

  Pearson’s r	G1	G2	G3	G4	G5	G6	G7	G9	G10	G11	G12	G13	G14	G15
  G1	-	0.916	0.908	0.877	0.705	0.864	0.964	0.935	0.895	0.876	0.947	0.912	0.737	0.655
  G2	0.916	-	0.870	0.977	0.715	0.892	0.928	0.872	0.815	0.793	0.893	0.930	0.633	0.574
  G3	0.908	0.870	-	0.815	0.820	0.910	0.870	0.872	0.909	0.929	0.952	0.812	0.813	0.798
  G4	0.877	0.977	0.815	-	0.690	0.913	0.901	0.842	0.784	0.742	0.864	0.921	0.588	0.553
  G5	0.705	0.715	0.820	0.690	-	0.791	0.697	0.832	0.838	0.858	0.825	0.642	0.933	0.824
  G6	0.864	0.892	0.910	0.913	0.791	-	0.873	0.847	0.876	0.856	0.919	0.842	0.725	0.797
  G7	0.964	0.928	0.870	0.901	0.697	0.873	-	0.905	0.844	0.825	0.916	0.935	0.695	0.617
  G9	0.935	0.872	0.872	0.842	0.832	0.847	0.905	-	0.954	0.926	0.955	0.891	0.854	0.705
  G10	0.895	0.815	0.909	0.784	0.838	0.876	0.844	0.954	-	0.965	0.962	0.824	0.898	0.841
  G11	0.876	0.793	0.929	0.742	0.858	0.856	0.825	0.926	0.965	-	0.963	0.777	0.905	0.862
  G12	0.947	0.893	0.952	0.864	0.825	0.919	0.916	0.955	0.962	0.963	-	0.901	0.842	0.782
  G13	0.912	0.930	0.812	0.921	0.642	0.842	0.935	0.891	0.824	0.777	0.901	-	0.610	0.529
  G14	0.737	0.633	0.813	0.588	0.933	0.725	0.695	0.854	0.898	0.905	0.842	0.610	-	0.863
  G15	0.655	0.574	0.798	0.553	0.824	0.797	0.617	0.705	0.841	0.862	0.782	0.529	0.863	-

  White font represent strong correlation, and darker blue highlight represent higher positive correlation.

  shows the correlation matrix for this group, and Figure 2 proves that all correlations are significant, as none was masked;
• The PCA (principal component analysis) on “guidance” data was performed, resulting in the following principal components (PCs) and their explained variances:

  ○

  PC1 explains 85.15% of the variance.

  ○

  PC2 explains 8.09% of the variance.

  ○

  PC3 explains 2.16% of the variance.

  ○

  PC4 explains 1.76% of the variance.

  ○

  Further components each explain less than 1% of the variance.

  ○

  All data tested significant at 5%.

  ○

  Data trends show generally a good positive correlation between the factors.

For the management and planning group:

Table 12. Correlation Matrix for Management and Planning Group.

Pearson’s r	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10
M1	-	0.858	0.653	0.691	0.908	0.873	0.729	0.692	0.768	0.830
M2	0.858	-	0.792	0.448	0.755	0.764	0.741	0.530	0.630	0.619
M3	0.653	0.792	-	0.544	0.582	0.593	0.886	0.631	0.607	0.374
M4	0.691	0.448	0.544	-	0.797	0.727	0.805	0.967	0.911	0.684
M5	0.908	0.755	0.582	0.797	-	0.756	0.742	0.769	0.807	0.770
M6	0.873	0.764	0.593	0.727	0.756	-	0.724	0.771	0.871	0.904
M7	0.729	0.741	0.886	0.805	0.742	0.724	-	0.848	0.835	0.519
M8	0.692	0.530	0.631	0.967	0.769	0.771	0.848	-	0.921	0.687
M9	0.768	0.630	0.607	0.911	0.807	0.871	0.835	0.921	-	0.774
M10	0.830	0.619	0.374	0.684	0.770	0.904	0.519	0.687	0.774	-

White font represent strong correlation, and darker blue highlight represent higher positive correlation.

shows the correlation matrix for this group. The PCA on “management” data resulted in the following principal components and their explained variances:

• PC1 explains 76.46% of the variance;
• PC2 explains 9.52% of the variance;
• PC3 explains 8.39% of the variance;
• PC4 explains 2.98% of the variance;
• Further components each explain less than 2% of the variance;
• Data trends generally show a good positive correlation between the factors, as shown in Figure 3.

In the PCA, we observed that the first principal component (PC1) explains a significant portion of the total variance (76.46%). This high percentage suggests that PC1 captures a substantial underlying data structure. Since the majority of the variance is explained by the components planned to be retained, this typically indicates that proceeding with these components is reasonable.

For the quality group:

Table 13. Correlation Matrix for Quality Group.

Pearson’s r	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9
Q1	-	0.675	0.966	0.811	0.554	0.781	0.926	0.815	0.729
Q2	0.675	-	0.571	0.874	0.860	0.840	0.443	0.695	0.920
Q3	0.966	0.571	-	0.751	0.477	0.738	0.945	0.810	0.633
Q4	0.811	0.874	0.751	-	0.807	0.882	0.612	0.708	0.857
Q5	0.554	0.860	0.477	0.807	-	0.782	0.408	0.724	0.852
Q6	0.781	0.840	0.738	0.882	0.782	-	0.655	0.715	0.888
Q7	0.926	0.443	0.945	0.612	0.408	0.655	-	0.810	0.586
Q8	0.815	0.695	0.810	0.708	0.724	0.715	0.810	-	0.743
Q9	0.729	0.920	0.633	0.857	0.852	0.888	0.586	0.743	-

White font represent strong correlation, and darker blue highlight represent higher positive correlation.

shows the correlation matrix for this group. The PCA on “Q” data resulted in the following principal components and their explained variances:

• PC1 explains 77.57% of the variance;
• PC2 explains 13.72% of the variance;
• PC3 explains 3.76% of the variance;
• Further components each explain less than 2% of the variance.

Data trends show less significance than other groups; however, PC1 explains a significant portion of the variance (77.57%), indicating that it captures a substantial amount of information from the original dataset. And Figure 4 represent Correlation Matrix Heatmap. Since the retained components capture a large portion of the total variance, proceeding with these components could still provide a comprehensive understanding of the data.

Kendall Coefficient

The Kendall coefficient is a non-parametric statistic used to measure the ordinal association between two variables. It evaluates the strength and direction of relationships by comparing rankings within datasets, making it suitable for analyzing non-normally distributed and ordinal data.

Table 14. Kendall Coefficient Results.

Category	Kendall Coefficient	Interpretation
Guidance	0.695	Strong
Management and planning	0.587	Moderate to strong
Quality	0.625	Strong

represents the results of Kendall Coefficient and their interpretation.

Spearman’s Rank Correlation Test

Spearman’s rank correlation coefficient is frequently employed to assess the overall accuracy of data. For instance, ref. [34] utilized this coefficient to evaluate the consistency of data values in their study on construction safety factors. The results of this study are displayed in

Table 15. Spearman’s Rank Correlation Coefficient Results.

Category	Kendall Coefficient	Interpretation
Guidance	0.822	Very strong
Management and planning	0.716	Strong
Quality	0.727	Strong

.

5. Discussion

This paper further introduces a detailed interpretation of the findings and provides recommendations based on the insights gathered in previous sections. This study explored the influence of specific factors on integrating building information model (BIM) into FMS. An extensive literature review was conducted following meetings with experts to identify the key factors for investigation in this project. Consequently, two surveys were developed to gather insights from industry professionals to assess the impact of these factors. The survey data underwent a thorough analysis using the Relative Importance Index and Spearman’s rank correlation to ascertain the significance of the factors and the correlation levels among participants with varying backgrounds.

Earlier sections outlined various sources of information, methodologies, and data leveraged to derive meaningful conclusions. These sections were complemented by analyses and presentations aligned with the project objectives. The top ten critical success factors are as follows:

• Define the OIR, AIR, and FM information requirements to support the AM strategy;
• Acquire correct files, data, and formats;
• Update of information requirements during the defect liability period (DLP);
• Three-dimensional visualization of asset locations;
• Understand the link between BIM and FM management systems;
• Set realistic expectations of what BIM can deliver;
• Understand client’s IT requirements;
• The use of interoperable systems to convert 2D to 3D BIM in existing buildings;
• Upskill FM teams to leverage BIM capabilities in FM (to participate in client proposal and development;
• Adapt two versions for FM systems (pre-production and production versions).

Each of the above factors is outlined and discussed in the following sections, and recommendations and limitations are addressed concerning the top ten critical success factors (CSFs) essential for successfully integrating building information models (BIM) into facility management systems (FMS). By implementing these strategies, stakeholders can enhance data accuracy, streamline operations, and optimize the long-term efficiency of facility management processes.

5.1. Define the OIR, AIR, and FM Information Requirements to Support the AM Strategy

One key aspect discussed in the literature is the process flow and the relationship between various elements of information management within BIM. Specifically, the role of OIR and AIR in defining the information required for managing assets effectively through BIM systems is crucial. These requirements are vital for setting up a structured BIM execution plan that aligns with client needs and operational strategies of facility management.

However, achieving consensus on the exact scope and detail of these information requirements can be challenging due to differing stakeholder expectations; it is essential to establish clear organizational information requirements (OIR), asset information requirements (AIR), and facility management (FM) information requirements to effectively support the asset management (AM) strategy. Define these early in the project to ensure all stakeholders have a common understanding of the required outcomes, facilitating smoother integration and operational efficiency.

5.2. Acquire Correct Files, Data, and Formats

This emphasizes the frequent misalignments in semantic formats and the discrepancies that arise due to different stakeholders’ varying needs and responsibilities within a project, which can lead to significant challenges in maintaining data consistency and quality across the BIM and FM interface.

One notable paper [36] discussed the challenges associated with the effective adoption of BIM-centered FM information systems, particularly the customization of information structures for each application case and the dynamic nature of data supporting building maintenance. This study highlights the need for seamless interoperability and integration within BIM systems to facilitate managing and retrieving dynamic FM-related data, thereby enhancing usability for FM operations in a university building setting.

A significant challenge is the frequent incompatibility between software platforms and data formats, for which the use of industry-standard exchange formats alongside rigorous quality assurance processes is strongly recommended. This involves setting strict guidelines for data submission from all contractors and consultants to avoid data mismanagement and ensure seamless integration into the FM system.

5.3. Update of Information Requirements During the Defect Liability Period (DLP)

The defect liability period (DLP) is a crucial stage following project completion, during which contractors remain responsible for addressing any emerging defects. Ensuring the continuous update of information requirements within the BIM-FM framework is essential for efficient defect tracking and resolution. Research on BIM-IoT integration emphasizes that real-time quality monitoring significantly improves defect management by enabling timely detection and resolution [37]. Maintaining accurate and up-to-date defect records within BIM models reduces operational risks and enhances decision-making for facility managers. Additionally, keeping updated records during the DLP allows stakeholders to plan preventive maintenance and future renovations effectively, leading to better building performance and lifecycle management. Implementing real-time data updates within BIM ensures facility managers, contractors, and owners access relevant information, streamlining defect rectification and minimizing disputes.

A key challenge is ensuring consistent communication and timely updates during the DLP, which can be mitigated by integrating automated workflows and assigning clear responsibilities for data updates among stakeholders. Project management should implement protocols to regularly update the BIM model and its data during the defect liability period (DLP) to reflect any changes or corrections in asset information. This ensures the FM system utilizes the most accurate and up-to-date information, enhancing maintenance and management practices.

5.4. Three-Dimensional Visualization of Asset Locations

Three-dimensional visualization in BIM can be optimized to support facility management tasks, addressing both the technological capabilities and the practical challenges. One study highlights the application of 3D visualization within BIM models to assist facility management tasks, particularly emphasizing the significance of identifying the best 3D viewpoints to enhance the effectiveness of visual tasks related to facility management. This research indicates that proper 3D visualization techniques can substantially improve facility management operations’ success rate and accuracy, providing clearer views of the assets within a building [38].

There are also challenges associated with current 3D visualization efforts in BIM. The research points out that while there are advancements in the granularity and interoperability of building data, the corresponding granularity in 3D geometry visualization still faces hurdles. These challenges stem from the need to effectively manage and streamline large datasets within the BIM models without overwhelming the system, which is crucial for efficient facility management [39].

It is recommended to develop and utilize 3D visualization tools within BIM to help facility managers locate and manage assets accurately. This technology not only aids in routine maintenance but also enhances emergency response times by providing clear visuals of asset locations.

5.5. Understand the Link Between BIM and FM Management Systems

A study by Lidia Pinti et al. examined how BIM has been applied, particularly within the design and construction sectors, and explored its recent extension to facility management. The research highlights the growing digitalization of FM processes and the necessity for effectively integrating BIM-FM. The study pointed out the lack of a cohesive approach in implementing BIM for FM, particularly in public sectors, and called for a more standardized methodology to bridge this gap. This suggests that while BIM is well-established in design and construction, its application in FM is still developing, and further efforts are required to align both fields effectively [30].

A major challenge is the technological gap between design-focused BIM systems and FM software, for which developing middleware solutions and encouraging collaborative standards adoption are recommended to enable seamless integration. It is also advisable to educate and train FM teams on the benefits and functionalities of BIM, emphasizing how it can be integrated into existing FM systems, and to highlight the data flow, interoperability, and the potential for enhanced decision making capabilities provided by a fully integrated BIM-FM system.

5.6. Set Realistic Expectations of What BIM Can Deliver

Ref. [30] emphasized the need for a clearer understanding of BIM’s capabilities and limitations in the FM sector. It pointed out that a major challenge in adopting BIM for FM lies in the technology itself and the existing work processes and organizational structures. Effective integration requires understanding what information needs to be provided, when, and by whom and how this information supports FM operations. It also stressed that information exchange between BIM models and FM systems is complex and needs structured processes to be effective.

It is essential to communicate the realistic capabilities and limitations of BIM in facility management. Setting clear expectations helps align project goals with achievable outcomes, reducing the risk of project overruns and ensuring stakeholder satisfaction.

5.7. Understand Client’s IT Requirements

Understanding the client’s IT requirements is a critical component in successfully integrating and applying building information modeling (BIM) for facility management. Ref. [30] highlights the importance of understanding IT requirements in BIM implementation for facility management. It suggested that thoroughly comprehending the client’s IT requirements is essential for successfully integrating BIM into existing systems. Facility managers need to prioritize their IT requirements in detail to make the most out of BIM. This includes understanding what data are valuable for daily FM operations and ensuring the BIM system is compatible with existing IT infrastructure to effectively manage data retrieval, change management, and cost tracking [40].

It is recommended to engage with clients to comprehensively understand their IT requirements and ensure the BIM environment is compatible with their existing systems. This includes software, hardware, network requirements, and data security protocols.

5.8. The Use of Interoperable Systems to Convert 2D to 3D BIM in Existing Buildings

Ref. [41] studied manual vs. automated 3D models from 2D. It is a systematic review that outlined the current state and future research directions for automating the 3D BIM modeling process from 2D drawings of existing buildings. This research highlights that while considerable efforts have been made toward generating 3D geometric models from 2D plans, the full automation of this process, particularly incorporating rich semantic information, remains a challenge.

The challenge is the significant manual effort still required to generate semantically rich 3D models from legacy 2D drawings; investing in AI-driven tools and standardized modeling protocols is recommended to improve efficiency. This capability is crucial for integrating historical data with new models, supporting enhanced FM strategies.

5.9. Upskill FM Teams to Leverage BIM Capabilities in FM (To Participate in Client Proposal and Development)

Facility management teams can benefit significantly from structured training programs that focus on integrating BIM technologies. These programs should cover not only the technical aspects of BIM but also strategic application in FM processes to improve collaboration among stakeholders and optimize building management operations [42].

It is essential to invest in continuous training for FM teams to update them on the latest BIM technologies and practices. This upskilling is vital for enabling the teams to participate effectively in client proposals and development, ensuring that FM considerations are integrated from the design phase to operation.

5.10. Adapt Two Versions for FM Systems (Pre-Production and Production Versions)

The concept of integrating digital FM systems, including the use of BIM in facility management, is discussed extensively in the literature. The discussions often focus on developing digital FM systems to align with organizational requirements and the implementation challenges of integrating BIM into existing FM frameworks to improve asset management and operational efficiencies.

A significant challenge is managing version control and ensuring smooth transitions between pre-production and production systems; establishing robust change management protocols and sandbox environments is recommended to mitigate risks. Project management can develop and maintain two versions of the FM system—pre-production and production—to allow testing of new features or updates before they go live. This strategy minimizes downtime and potential disruptions in the operational environment, providing a sandbox for troubleshooting and innovation without risking system stability.

6. Conclusions

This research rigorously identified critical success factors for integrating building information models (BIM) into facility management systems (FMS) through comprehensive interviews, workshops, and surveys, followed by a Delphi method analysis to validate the findings. A successful BIM-FM integration is crucial to optimize the benefits of BIM and upskill facility management systems and overcome some obstacles that face facility managers, such as data fragmentation. In consequence, this paper addressed this gap by providing critical success factors found in the literature and real-world experience. The experts’ insights into the study validated and prioritized the critical factors for the integration, and the survey analysis helped in ranking the factors to identify the top ten CSFs. The top ten success factors that were unearthed, including defining key information requirements, ensuring data correctness, and enhancing 3D visualization, are foundational for effectively deploying BIM within FM practices. These validated factors guide facilities managers in optimizing BIM implementation and set a benchmark for future advancements in integrating BIM technologies with facility management operations. And

Table 16. Correlation Between Top 10 CSF and Recommendations.

Rank	Critical Success Factor	Group	Recommendation
1	Define the OIR, AIR, and FM information requirements to support the AM strategy	Guidance	Define clear information requirements early in the project to effectively support asset management (AM) strategies, ensuring seamless integration and operational efficiency
2	Acquire correct files, data, and formats	Quality	Standardize data formats and structures across the BIM project to enhance consistency and interoperability
3	Update of information requirements during the defect liability period (DLP)	Guidance	Establish protocols for regularly updating the BIM model during the defect liability period (DLP) to incorporate modifications and maintain accurate asset information
4	Three-dimensional visualization of asset locations	Quality	Utilize 3D visualization tools within BIM to enhance asset tracking and management for facility managers
5	Understand the link between BIM and FM management systems	Guidance	Provide training for FM teams on BIM functionalities, emphasizing data flow, interoperability, and improved decision making within an integrated BIM-FM system
6	Set realistic expectations of what BIM can deliver	Planning and Management	Set realistic expectations regarding BIM’s capabilities and limitations in facility management to align project objectives and prevent scope misalignment
7	Understand IT requirements by the client	Guidance	Collaborate with clients to assess IT requirements and ensure seamless compatibility between BIM and existing systems
8	The use of interoperable systems to convert 2D to 3D BIM in existing buildings	Guidance	Use interoperable solutions to convert 2D drawings into 3D BIM models, particularly for retrofitting older buildings
9	Upskill FM teams to leverage BIM capabilities in FM (to participate in client proposal and development	Planning and Management	Continuously upskill FM teams in the latest BIM technologies, enabling them to contribute to client proposals and integrate FM needs from design to operation
10	Adapt two versions for FM systems (pre-production and production versions)	Guidance	Maintain both pre-production and production versions of the FM system to test and refine updates before full implementation

provides a summary of the top critical success factors, their EIR categories, and the top recommendations to deal with them.

This study has several limitations that should be considered when interpreting its findings. First, the research was conducted with a limited number of participants, specifically experts with direct experience relevant to the research objectives. Although this approach facilitated detailed and high-quality insights, the relatively small and specialized sample size may limit the generalizability of the results. Second, the participants primarily represented perspectives from Qatar and similar regional contexts, which may not reflect broader international practices in BIM-FM integration. Third, this study did not extensively address critical aspects such as cost implications or interoperability challenges, which are crucial for comprehensive BIM-FM integration. Future research is encouraged to involve a larger and more geographically diverse participant group, incorporate real-world practical experiments, investigate cost-benefit analyses, and examine interoperability challenges to provide more comprehensive insights for industry practitioners.