Optimal BIM staffing in construction projects using a queueing model

Highlights

• A method to evaluate the activities of BIM staff by introducing a time-dependent queueing model was proposed.

• The proposed framework is validated with data from three real-world projects in which BIM was applied.

• The effects of BIM staffing are quantitatively analyzed using time and cost indicators

• Optimal BIM staffing can be judged using the waiting costs of project participants.

Abstract

BIM staff plays the important role of providing required information from digital models to project participants. A dilemma is determining the appropriate capacity of BIM staff without sacrificing efficiency in terms of human resource costs. Despite the importance of BIM staffing, its effects on the productivity and performance of construction projects have rarely been investigated. This study presents a framework for quantifying the impact of BIM staffing. First, this study proposes a method to evaluate the activities of BIM staff by introducing a time-dependent queueing model. Second, the proposed framework is validated with data from three real-world projects in which BIM was applied. The effects of BIM staffing on the waiting time of project participants are quantitatively analyzed using time and cost indicators. The results show that decisions about optimal BIM staffing can be made by considering the waiting costs of project participants.

Introduction

Unexpected events nearly always occur during construction projects, i.e., design errors, reworks, and schedule delays [1]. Uncertainty and the unexpected events themselves can lead to additional transaction costs [2,3]. Therefore, communication and collaboration among project participants are essential to minimize disruption. BIM is intended to support project participants in recognizing problems ahead of time and finding solutions in the architecture, engineering, and construction (AEC) industry [4]. However, conventional work environments organized around two-dimensional computer aided design (CAD) programs remain common [5,6] because many project participants are reluctant to use BIM.

BIM makes it possible to accumulate information across a project's life cycle, including the planning, design, construction, and operational phases. That information can then be combined into a geometric model of the product in the working environment [7,8]. Appropriate BIM can provide information as required [9]. However, this ideal scenario can only be realized when all participants understand the fundamental principles of BIM and have the ability to use BIM applications appropriately. In many cases, participants have difficulty reaching the level of communication and collaboration required in the BIM context [10]. To bridge the gap between BIM utopia and the real world, specific BIM staff needs to be allocated to process the necessary information and manage the issues raised by various project participants [1,3,11]. Given that BIM staffing is an emerging issue, a framework to analyze its dynamic effects on project performance or efficiency is required to optimize human resource allocation and organizational relations. Within the popular research field of resource management and staff allocation in construction management [[12], [13], [14]], BIM staffing is likely to be a major issue.

Focusing on BIM staffing in the context of the dynamic relationships among project participants is unlike other research, which has mainly produced input and output analyses. For instance, several case studies have analyzed the return on investment (ROI) of BIM, which required an investigation of BIM investment costs and revenues [1,3,11]. Labor productivity for specific types of work, such as mechanical, electrical, and plumbing, is also measured in terms of input and output [15]. Existing studies have thus paid limited attention to quantitatively analyzing the direct and dynamic effects of allocated BIM staff on other project participants [3,11]. In particular, determining the appropriate number of BIM staff is an urgent issue; the BIM staff needs to be large enough to enhance the collaboration of project participants and optimize the working time (minimize waiting) without sacrificing the cost effectiveness of the human resources budget.

Optimizing work processes is not a new research topic; various researchers [[16], [17], [18], [19], [20], [21]] have developed simulation applications that use a queueing model. However, the main subjects of those simulations are the resources and tasks whose productivity needed to be optimized. The interactions among people, especially the working intervals caused by waiting time, have not been considered. We present a novel approach for measuring the efficiency of BIM staffing within the fundamental principles of an orthodox queueing model.

This paper presents a theoretical review of managerial issues and BIM: human resource allocation in construction and the role and responsibilities of BIM staff. We critically review previous research about BIM performance and explain the need for a new approach and method in this context, including a discussion of queueing systems. Then we identify the practical research problems in a preliminary real-world investigation of three projects that used BIM. Critical discussion and findings feed the development of our research framework for the case analyses. To quantify the effects of BIM staffing, we present a detailed framework for evaluating the activities of BIM staff using a queueing model. To validate the model, we use it to analyze three real-world projects in which BIM was applied during the construction phase. After that, we discuss the actual cases, including an overview of the projects studied and a detailed description of the data collected about the BIM requests for information (RFIs).