Lean construction and BIM in construction projects: A literature review (2015–2025)

4.1.1. Subcategory: Productivity

The integration of Lean and BIM has become established as an effective strategy for improving productivity in construction projects. Several studies highlight that improved planning, activity coordination and reduced downtime contribute significantly to overall project performance (Aziz et al. 2024; Rashidian et al. 2024; Awe et al. 2025). According to Pérez et al. (2024), this synergy allows for more continuous workflows, while Mayouf et al. (2024) emphasise the importance of digital tools for anticipating clashes. For authors such as Faria et al. (2023) and Ismail et al. (2023), the use of 4D models and collaborative environments improves the understanding of schedules and strengthens the efficiency of on-site teams. Furthermore, Schery et al. (2023) and Zhao et al. (2023) agree that the early application of Lean + BIM increases operational capacity and reduces time losses associated with poor planning.

This concentration of evidence suggests that productivity gains are not an automatic byproduct of software adoption, but rather the result of synchronising digital workflows with pull-planning techniques that proactively eliminate bottlenecks before site execution begins.

4.1.2. Subcategory: Cost efficiency

Specialised literature recognises that Lean + BIM allows for more precise management of economic resources on construction sites. According to Rashidian et al. (2024) and Pishdad and Onungwa (2024), 5D modelling improves cost estimation and allows for continuous budget monitoring. Pérez et al. (2024) and Mayouf et al. (2024) maintain that this efficiency is reflected in the reduction of rework and errors, while Aziz et al. (2024) and Ismail et al. (2023) highlight the role of collaborative planning in reducing indirect costs. It is also observed that authors such as Faria et al. (2023) and Schery et al. (2023) link efficiency to the use of prefabricated components, which optimises logistics and shortens timelines. Zhao et al. (2023) and Awe et al. (2025) conclude that this integration not only improves financial control but also allows for greater predictability in the development of the project.

The literature demonstrates that 5D BIM and Lean cost controls shift financial management from a reactive posture (tracking post-construction overruns) to a proactive mechanism where cost predictability is achieved through rigorous pre-planning and supply chain optimisation.

4.1.3. Subcategory: Interdisciplinary coordination

Lean and BIM strengthen collaboration between specialities, promoting greater integration from the early stages of a project. Pérez et al. (2024) point out that collaborative models and common data environments allow for the detection of clashes before execution. Along these lines, Rashidian et al. (2024) and Faria et al. (2023) highlight that pull planning and visual management encourage the active participation of all stakeholders. For Schery et al. (2023) and Zhao et al. (2023), this coordination is key in complex projects, where information fragmentation can lead to serious failures. Furthermore, similar studies by Ismail et al. (2023) and Awe et al. (2025) show that interdisciplinary coordination facilitates joint decision-making, which helps reduce conflicts and improve the construction sequence.

This highlights that technical coordination tools (like clash detection) and social collaborative practices (like last planner sessions) must function concurrently; technology provides the platform for detection, while Lean principles provide the behavioural framework for joint problem-solving.

4.1.4. Subcategory: Quality improvement

Construction quality directly benefits from the combined implementation of Lean and BIM. Rashidian et al. (2024) indicate that traceability and continuous monitoring allow for the correction of errors before they impact the construction site. For Pérez et al. (2024) and Mayouf et al. (2024), digital models offer a more rigorous environment for technical verification, while Aziz et al. (2024) and Schery et al. (2023) highlight that visual management facilitates the detection of deviations from standards. Ismail et al. (2023) also emphasise the importance of continuous feedback for improving finishes, and Zhao et al. (2023) suggest that quality improves when prefabricated systems under factory control are incorporated. Overall, the studies agree that quality improvement is not only technical but also related to processes and customer satisfaction.

The reviewed studies collectively show that quality enhancement under Lean + BIM transcends defect correction, shifting towards a systemic verification process where factory-controlled prefabrication and digital models drastically reduce site variability.

4.1.5. Subcategory: Waste reduction

One of the most notable advantages of applying Lean + BIM is the reduction of waste in all its forms. According to Aziz et al. (2024) and Pérez et al. (2024), standardised processes and collaborative planning allow for the elimination of unnecessary activities. Rashidian et al. (2024) and Ismail et al. (2023) state that digital integration promotes more organised execution, while Faria et al. (2023) and Zhao et al. (2023) highlight that the use of 4D models reduces waiting times and improves the construction sequence. Schery et al. (2023) link this reduction to the logistics of materials and prefabricated components, and Awe et al. (2025) agree that operational efficiency translates into less rework and reduced resource use. This evidence suggests that Lean + BIM not only optimises the final result but also contributes to more sustainable construction.

By linking waste reduction directly to logistics and 4D sequencing, the literature underscores that environmental and operational sustainability are deeply intertwined; eliminating waiting times and material mishandling directly minimises the carbon and economic footprint of construction sites.

4.1.6. Subcategory: Data-driven decision making

Data-driven decision making is one of the pillars strengthened by the integration of Lean and BIM. According to Rashidian et al. (2024) and Pérez et al. (2024), digital environments allow access to real-time, up-to-date information, facilitating faster responses. Aziz et al. (2024) and Zhao et al. (2023) indicate that visual control systems and digital indicators improve the traceability of decisions. Ismail et al. (2023) and Awe et al. (2025) add that the use of analytical tools and predictive models allows for anticipating problems, reducing risks during execution. Meanwhile, Faria et al. (2023) and Schery et al. (2023) emphasise that data availability facilitates alignment between the different levels of project management, promoting more coherent and effective decisions.

The capability to process real-time information bridges the traditional gap between upper management planning and on-site execution, ensuring that strategic decisions are grounded in empirical operational indicators rather than intuition or outdated reports.

4.2.1. Subcategory: Technological barriers

Technological barriers significantly hinder the implementation of Lean, BIM and their integration due to a lack of adequate digital infrastructure, the technical complexity of the tools and poor interoperability between platforms. For example, the execution of Lean tools such as the Ultima planning system is limited in environments lacking digital resources (Moradi and Sormunen 2024), while inefficient practices such as ‘making-do’ persist in contexts without digital control such as Mandujano et al. (2016), Götz et al. (2020), and Demirdöğen et al. (2021). In the case of BIM, advanced and up-to-date tools are required, often with AI integration, which increases the technical requirements (Awe et al. 2025). Furthermore, interoperability issues are reported, especially in modular projects (Mayouf et al. 2024), and the lack of infrastructure in the public sector is a recurring barrier (Schery et al. 2023). Lean-BIM integration intensifies these challenges, as it demands integrated information flows and advanced computing capabilities (Götz et al. 2020; Demirdöğen et al. 2021; Alizadehsalehi and Hadavi 2023).

The evidence suggests that technology-induced friction stems less from the inherent limitations of software tools and more from a systemic mismatch between high-end digital requirements and the foundational digital maturity of traditional construction firms.

4.2.2. Subcategory: Cultural barriers

Cultural barriers represent a structural limitation that hinders the organisational transformation necessary to implement Lean, BIM or their integration. Many organisations maintain traditional hierarchical structures, resistance to change and a low willingness to engage in collaborative work (Alizadehsalehi and Hadavi 2023). The culture of improvisation, also called ‘making-do’, continues to be accepted in some environments, which slows down planning and standardisation, such as Mandujano et al. (2016), Sepasgozar et al. (2021), and Andújar-Montoya et al. (2020). In the case of BIM, a lack of trust in sharing digital models has been observed, motivated by fear of error or external judgement (Moradi and Sormunen 2024), and some companies adopt this technology superficially, without modifying internal processes (Andújar-Montoya et al. 2020). In Lean-BIM environments, fragmented organisational cultures hinder the alignment of objectives (Sepasgozar et al. 2021), while other studies highlight that successful cases are only achieved through a deep cultural transformation (Moradi and Sormunen 2022; Karaz et al. 2024).

Overcoming cultural inertia requires structural governance changes rather than superficial interventions, as traditional hierarchies and fear of transparency directly neutralise the collaborative ethos that both Lean and BIM demand.

4.2.3. Subcategory: Economic barriers

On the economic front, one of the main challenges is the perception that Lean and BIM involve high initial costs and that their benefits are not immediately apparent. In the case of Lean, although its process-oriented approach suggests low costs, its implementation requires investment in training and change management, which many organisations consider expensive (Garcés and Peña 2023). Similarly, in countries like New Zealand, it has been documented that Lean is perceived as an investment without immediate visible results (Likita et al. 2022). For its part, BIM faces criticism due to the high costs of software, hardware and training such as Eldeep et al. (2021) and Likita et al. (2022), which is especially restrictive in the public sector (Schery et al. 2023). Lean-BIM integration requires even greater investment, both in tools and in human resources and joint adoption processes (Faria et al. 2023; Pérez et al. 2024). Even in successful experiences, the learning curve and the total cost of implementation remain a concern (Hei et al. 2024).

The reluctance to invest highlights a persistent misalignment between short-term capital expenditures and long-term lifecycle savings, indicating that financial metrics must evolve to capture the qualitative and waste-reduction returns of Lean + BIM integration.

4.2.4. Subcategory: Training and skills barriers

The lack of specific training and skills constitutes a key cross-cutting barrier to the implementation of Lean, BIM and their integration. In the case of Lean, practical training in methodologies, such as the Last Planner System, 5S or VSM is required, which is not always available (Aziz et al. 2024). Several studies have indicated that the lack of adequate training has led to partial or erroneous implementations, such as Wu et al. (2022), Singh and Kumar (2020) and Nguyen and Akhavian (2019). BIM, for its part, requires technical mastery of the software, model interpretation and collaborative work skills – competencies that are often limited even when the technological tools are available (Eldeep et al. 2021; Schery et al. 2023). Furthermore, it has been identified that training designers alone is insufficient; all project stakeholders must be trained (Nguyen and Akhavian 2019). For Lean-BIM integration, the challenge is amplified, as it requires personnel with skills in both approaches, something uncommon in the current market (Sepasgozar et al. 2021). In this context, some authors propose specific educational programmes as a strategy to close this gap (Patching et al. 2023).

The skills gap acts as the ultimate bottleneck for integration; procuring advanced software or deploying continuous improvement philosophies remains ineffective without interdisciplinary professionals trained to bridge operational management with digital execution.

4.3.1. Subcategory: Use of 4D and 5D models

The adoption of 4D (time) and 5D (cost) models represents one of the main innovations in the digital transformation of the construction sector, with a clear convergence between Lean Construction and BIM (Mayouf et al. 2024; Pishdad and Onungwa 2024; Awe et al. 2025). The reviewed literature provides strong support for this trend, with documented applications encompassing planning, construction control and simulation (Rashidian et al. 2022; Alizadehsalehi and Hadavi 2023; Khodabocus and Seyis 2023; Mayouf et al. 2024). The 4D model has been shown to improve the sequencing and visualisation of activities (Sbiti et al. 2021; Alizadehsalehi and Hadavi 2023; Awe et al. 2025), while 5D has optimised cost estimation and control through its link with design (Zhao et al. 2023; Hei et al. 2024; Rashidian et al. 2024). Furthermore, experiences such as the delivery of prefabricated elements (Bataglin et al. 2019), the effect of Lean and BIM synergy (Nguyen and Akhavian 2019), and simulations with other tools (Jeong et al. 2016) have demonstrated a tangible improvement in coordination, workflow and project performance. However, challenges such as interoperability, low standardisation and lack of integration with project execution persist (Sbiti et al. 2021; Hei et al. 2024; Karaz et al. 2024; Rashidian et al. 2024).

The widespread adoption of 4D and 5D modelling signifies a paradigm shift from reactive schedule monitoring to proactive timeline and cost simulation, though their true potential is frequently bottlenecked by poor data interoperability and rigid legacy workflows.

4.3.2. Subcategory: Integration of lean + BIM frameworks

The literature shows a growing development of methodological frameworks that seek to articulate the principles of Lean Construction with the technological capabilities of BIM (Demirdöğen et al. 2021; Likita et al. 2022; Ismail et al. 2023; Khodabocus and Seyis 2023). This integration is seen as a path towards comprehensive efficiency in project management, by reducing waste, facilitating improved decision-making and collaboration. Articles addressing this trend include Rashidian et al. (2022, 2023, 2024), Sepasgozar et al. (2021), Tezel et al. (2020), Nascimento et al. (2017), Karaz et al. (2024) and Hei et al. (2024). For example, El Mounla et al. (2023) propose a Lean-BIM approach to improve performance in the design phase, and Alizadehsalehi and Hadavi (2023) analyse the synergies between Lean, BIM and Extended Reality. Similarly, Ahuja et al. (2017) apply qualitative analysis to demonstrate how integration contributes to lean and sustainable goals. Studies by Bataglin et al. (2019), Nguyen and Akhavian (2019), and Mitera-Kiełbasa and Zima (2025) document empirical benefits of prefabrication and collaborative design, and Karaz et al. (2024) dynamically models the effects of this synergy on poor practices. Despite these advances, articles by Moradi and Sormunen (2024) and Wu et al. (2022) warn of obstacles such as a lack of standardisation, insufficient training and cultural resistance within organisations.

The evolution of these frameworks highlights that combining philosophies requires more than theoretical alignment; it demands systematic procedural guidelines that bridge the operational pull-planning of Lean with the digital visualisation of BIM.

A critical comparison among these frameworks reveals a clear methodological division: while process-oriented models (such as those centred on Last Planner workflows and value stream mapping) prioritise behavioural alignment, pull-planning discipline, and waste reduction, technology-driven frameworks focus primarily on digital visualisation, automated clash detection, and common data environments. However, a significant gap remains in frameworks that achieve true bidirectionality (where real-time digital feedback from BIM models dynamically triggers and modifies Lean site-level tactical decisions rather than serving merely as a static visualisation medium).

4.3.3. Subcategory: Digitisation of collaborative processes

The digitisation of collaborative processes, understood as the synchronisation of information between actors through shared environments and integrated flows, has been widely addressed in the literature (Nascimento et al. 2017; Bataglin et al. 2019; Nguyen and Akhavian 2019; Ratajczak et al. 2019; Ardila and Francis 2020; Sbiti et al. 2021; Sepasgozar et al. 2021; Rashidian et al. 2022, 2024; Alizadehsalehi and Hadavi, 2023; Ismail et al. 2023; Patching et al. 2023; Schery et al. 2023; Hei et al. 2024; Herrera and Castañeda 2024; Pino Álvarez et al. 2024; Awe et al. 2025; Mitera-Kiełbasa and Zima 2025). Platforms such as collaborative BIM and common data environments have been shown to facilitate communication and information management in real time (Bataglin et al. 2019; Nguyen and Akhavian 2019; Sbiti et al. 2021; Alizadehsalehi and Hadavi 2023; Herrera and Castañeda 2024; Rashidian et al. 2024). However, gaps still persist related to the complete integration of the supply chain, the standardisation of tools, and digital training. Rashidian et al. (2022), Sepasgozar et al. (2021), Ardila and Francis (2020), Karaz et al. (2024), Mitera-Kiełbasa and Zima (2025), and Herrera and Castañeda (2024) highlight the need for digital governance that ensures interoperability and seamless coordination, while Ismail et al. (2023), Götz et al. (2020), and Patching et al. (2023) emphasise the value of collaborative systems from the design stage to implementation.

Common data environments serve merely as a technical medium; true collaborative digitisation depends on establishing robust digital governance and shared accountability structures across the entire supply chain.

4.3.4. Subcategory: Automation and predictive analytics

Automation and predictive analytics have emerged as strategic capabilities for optimising project planning and control. Thanks to BIM tools integrated with sensors, algorithms and automated workflows, it is possible to detect deviations, anticipate risks and generate solutions in real time. This trend is widely supported by research, such as that in the articles Awe et al. (2025), Pishdad and Onungwa (2024), Zhao et al. (2023), Schery et al. (2023), Alizadehsalehi and Hadavi (2023), Rashidian et al. (2022), Sbiti et al. (2021), Sepasgozar et al. (2021), Götz et al. (2020), Bataglin et al. (2019), Pino Álvarez et al. (2024), Herrera and Castañeda (2024), Karaz et al. (2024), and Pal et al. (2023), which present use cases in visual tracking, dynamic programming and instant feedback. Awe et al. (2025) highlight the incorporation of AI to improve 4D models, while Zhao et al. (2023), Sepasgozar et al. (2021), and Herrera et al. (2021) explore automated data capture and analysis systems for Lean management. Meanwhile, Karaz et al. (2024) demonstrate the potential of predictive simulation for evaluating practices such as ‘making-do’. Despite the demonstrated benefits, the articles Rashidian et al. (2022), Sbiti et al. (2021), and Pal et al. (2023) reveal limitations related to data quality and resistance to replacing manual controls with automated models, suggesting a gap between technological potential and practical adoption.

While AI and predictive algorithms offer unprecedented capabilities for real-time risk mitigation, a stark gap remains between technical forecasting potential and organisational readiness to trust automated insights over traditional manual controls.

4.3.5. Subcategory: Standardisation and repeatability of processes

Standardisation is a recurring theme in research on Lean and BIM as drivers of continuous improvement. In Lean, several studies (Nascimento et al. 2017; Bataglin et al. 2019; Tezel et al. 2020; Demirdöğen et al. 2021; Likita et al. 2022; Moradi and Sormunen 2022; Wu et al. 2022; El Mounla et al. 2023; Ismail et al. 2023; Khodabocus and Seyis 2023; Hei et al. 2024; Rashidian et al. 2024; Mitera-Kiełbasa and Zima 2025, among others) highlight that standardising workflows reduces variability, eliminates waste and facilitates tools such as the Last Planner System or Value Stream Mapping. In industrialised environments, these repetitive systems improve predictability and logistical efficiency (Bataglin et al. 2019).

In BIM, the standardisation of data structures (specifically leveraging open standards like openBIM [IFC]) and the comprehensive definition of the level of development (LOD), integrating both geometry and non-graphical information, minimise errors and improve traceability (Jeong et al. 2016).

In the Lean-BIM convergence, the literature emphasises benefits such as repetitive processes geared towards continuous improvement, early validation and replicability across projects (Mellado and Lou 2020; Moradi and Sormunen 2022). These approaches strengthen sustainability, integration maturity and sector performance through stable and predictable practices. Overall, the studies agree that standardisation drives knowledge management, training and the scalability of best practices, although challenges such as cultural resistance and adaptation to local contexts remain.

Standardisation acts as the essential backbone for scaling Lean-BIM integrations; without structured data libraries and uniform workflows, organisations risk repeating localised successes without achieving enterprise-wide scalability.

4.3.6. Subcategory: Cultural and organisational transformation

The effective implementation of Lean and BIM requires a profound transformation not only technological, but also cultural and organisational. Various studies, Rashidian et al. (2024), Faria et al. (2023), Schery et al. (2023), El Mounla et al. (2023), Alizadehsalehi and Hadavi (2023), Moradi and Sormunen (2024), Likita et al. (2022), Wu et al. (2022), Sepasgozar et al. (2021), Mellado and Lou (2020), Andújar-Montoya et al. (2020), Tezel et al. (2020), Bataglin et al. (2019), Nguyen and Akhavian (2019), Darabseh (2019), Nascimento et al. (2017), Jeong et al. (2016), Mandujano et al. (2016), Herrera and Castañeda (2024), Karaz et al. (2024), Hei et al. (2024), Moradi and Sormunen (2022), and Demirdöğen et al. (2021) demonstrate that sustainable change depends on adaptive structures, leadership commitment and continuous training. Alizadehsalehi and Hadavi (2023) highlight the importance of fostering a collaborative mindset to fully leverage Lean-BIM synergies, while Moradi and Sormunen (2024) identify cultural barriers as one of the main obstacles. Likita et al. (2022), Wu et al. (2022), and Sepasgozar et al. (2021) highlight the need to train all hierarchical levels and create organisational frameworks that promote learning. Demirdöğen et al. (2021) propose a maturity model that includes organisational culture as a key axis of digital integration. Despite these advances, resistance to change, contractual fragmentation and a lack of adequate incentives remain challenges for comprehensive transformation, as discussed by Bataglin et al. (2019) and Herrera and Castañeda (2024).

Ultimately, the success of any technological or methodological trend is bounded by organisational culture; unless leadership actively dismantles contractual fragmentation and risk-averse behaviours, advanced digital tools will only automate existing inefficiencies rather than eliminate them.