Performance Indicators for Construction Projects: A literature review

Many companies are using Performance Indicators to compare their construction projects and to assess how the strategic goals of the company are fulfilled. However, the construction industry lacks objective benchmarks, or a way to measure excellence across the industry. One reason for the absence of industry benchmarks is the lack of centralized data necessary to establish standards. All contractors using digital technology to manage their construction projects are generating data and information; however, many say they lack a single place to aggregate that information and knowledge of how to use it in a meaningful way. Well defined Performance Indicators can help companies to better measure project outcomes and to better control the construction works. In addition, utilisation of performance indicators and digital twin technologies lead to better scheduling forecasts, better allocation of resources and optimization of equipment usage, reduced number of accidents on construction sites and reduction of costs on construction projects.

Managers on the construction site, supervisors and investors can use performance indicators on emerging structures for monitoring of:

  • Progress and duration of various construction works (e.g., pouring the concrete, installation of the facade panels, construction of dry-wall elements.),
  • Equipment usage (e.g., cranes, scaffolding, delivery tracks),
  • Health and Safety conditions
  • Labour productivity
  • Deviation from original planning
  • Waste disposal
  • Use of available on-site space
  • Cost

 Performance Indicators impacting on resource efficiency

The construction sector is the largest consumer of raw materials in the EU and construction and demolition activities account for about 33% of waste generated annually. While efforts towards sustainable construction have increased, these have largely covered fragmented segments of the construction industry—i.e., focusing only on energy issues or carbon emissions—thereby omitting the “big picture”.  Therefore, a more comprehensive perspective is needed; one that more fully considers the trade-offs between different types of resources (i.e., materials, energy, equipment) and the functionality of the built object (social aspects) over the life-time of a built object.

Construction and demolition waste (CDW) accounts for more than a third of all waste generated in the EU. It contains a wide variety of materials such as concrete, bricks, wood, glass, metals and plastic. It includes all the waste produced by the construction and demolition of buildings and infrastructure, as well as road planning and maintenance. That’s why the European Commission introduced a new protocol on construction and demolition. Its overall aim is to increase confidence in the Construction and Demolition waste management process and the trust in the quality of Construction and Demolition recycled materials. This will be achieved by:

–       Improved waste identification, source separation and collection,

–       Improved waste logistics,

–       Improved waste processing,

–       Quality management,

–       Appropriate policy and framework conditions.

This Protocol has been developed for application in all 28 EU countries. According to (Kourmpanis, 2008) knowledge of the generated quantities of every waste stream constitutes the main parameter required for the development of an appropriate scheme for its management. Construction & Demolition (C&D) waste is one of the waste streams for which data related to the quantities generated is not easy to obtain. The data kept by the producers and authorities involved does not refer to waste quantities but could be used as a basis for the extraction of quantitative data, by using appropriate supporting calculation tools. All the producers and authorities involved in the generation and management of C&D waste (sources for the collection of data related to this waste stream) should be recorded and an inventory program could then be applied to obtain all the necessary data and information for the determination of the quantities of C&D waste.

At every stage of the construction process there are different opportunities for different professions in construction to reduce waste, and reuse or recycle products, components, and buildings, and for materials to move up the waste hierarchy so that ultimately material resources can continue to flow around a circular economy.  These opportunities are available to clients, designers, material suppliers, product manufacturers, distributors and construction and demolition contractors.  The waste management industry is also important in enabling those in construction to improve their waste performance.  The government has a key role to play in the setting of policy and regulation, as a construction client and building owner, as well as ensuring statistics are gathered to measure and monitor material use.

Construction projects are complex and dynamic in their nature. One of the main resources and constraints that affect the delivery of construction projects is the space available on site to execute site activities directly or indirectly (Dawood et al. 2005).  Spaces on construction sites have become more and more critical to the extent that new business models have emerged in Europe and the UK, where logistics companies use space buffers to free site space capacity, especially for construction projects built around large and busy cities.  In addition, construction projects are currently characterised by a high degree of fragmentation and specialization, which shape both the work on site and in the upstream supply chain (Kassem  et  al.  2012). Activities on construction sites are usually performed by multiple trades who require, at any point in time, different workspaces such as: working areas for laborers; material storage; equipment, and support infrastructure.      

Performance Indicators impacting on productivity

Even minor drops in the level of safety and productivity have a negative impact on working time and contribute to delays, which also affects the growing cost losses (Nabi, El-adaway, Dagli, 2019). According to Nabi et al. (2019) initial labour hours, maximum production rate, labour productivity, remaining work and target production were proposed as factors that may affect safety performance and productivity on the construction site. Initial labour hours represent the number of daily working hours multiplied by the number of workers. Maximum productivity rate is the highest possible labour productivity rate which can be obtained at current projects. Productivity rate factor should increase as a learning curve[1]. With time, as the workers acquire necessary knowledge to obtain the task and get higher familiarity with current work, the productivity is expected to increase. The two equations needed to calculate labour productivity rate and productivity rate were presented with the remaining factors used as output. Additionally, one of the formulas allows one to consider the seasonality of work at every stage of time because the productivity of blue-collar workers is strongly dependent on weather conditions.

Performance Indicators impacting on safe construction works

According to studies of Winge, Albrechtsen and Arnesen (2019) the construction industry in Europe still has one of the highest fatal accident rates, greater than one in five accidents at work. The article provides an overview of 12 different construction projects. The constructions were mostly new buildings, museums and university buildings, and rehabilitations of old buildings. Some of these projects included demolition and groundworks. As a result, it was possible to develop 16 factors that, to a greater or lesser extent, contributed to the classification of the project as a project with a high level of security or with a low level of security. The following indicators were used to develop the results:

  • WH – working hours recorded by the main contractor, subcontractors, and hired workers, excluding designers’ working hours.
  • LTI-rate – (Lost Time Injuries) per 1 million hours of work. These are injuries that result in more sick leave than just the day of injury. Reported by contractors to the client.
  • MTI-rate – (Medical Treatment Injuries) for 1 million working hours. Reported by contractors to the client.
  • TRI-rate – (Total Recordable Injuries LTI + MTI) per 1 million working hours. Reported by contractors to the client.
  • RUOs and SDs – (Registered Unwanted Occurrences and Site Deviations) include accidents and potentially accidental situations, as well as deviations from the regulations registered by contractors regarding mainly safe work analysis, work instructions, lack of personal protective equipment, scaffolding failure, no hazardous zones have been specified.
  • WTR – (Willingness To Report) RUO and SD per 1000 working hours.

There are two main types of safety indicators: lagging and leading indicators (Poh, Ubeynarayana, Goh, 2018). Lagging indicators (also negative or reactive indicators) are measuring workplace safety and health outcomes such as illness or injury rate. Due to the delayed nature of lagging indicators, developing the suitable leading indicators to help managers assess the safety and health risk of workplace is needed. The leading indicators (also positive and proactive indicators) are measuring activities at workplace, events and conditions which may determine safety and health outcomes, e.g., number of inspections, safety climate measures and aggregated training effectiveness score.

According to studies of Choe, Seo and Kang (2020) the most popular safety factors are related to total recordable incident rate, which are lagging indicators. It also turned out that more than half of the examined subcontractors declare that they use only injury rate as a safety indicator. Moreover, approximately 27% of workers do not report their injuries to their supervisors. Furthermore over 70% of white-collar workers said they use many of safety performance indicators on the construction site, while over 70% of blue-collar workers complain that total recordable incident rate is the only used safety performance indicator. The data was compiled on the basis of 341 survey data items collected from general contractors and subcontractors, both blue collar workers and white-collar workers in South Korea (Choe et al., 2020).

It is worth paying attention to the level of pollutions in the air because it can have a negative impact on health. According to Khamraev, Cheriyan and Choi (2021) 70-80% of all particles of suspended dust come from construction projects. The formula to calculate mean daily dose exposure (mg/kg x day-1) to a particulate matter[2] was proposed as an factor related to health indicators. The input data from which it is possible to use the formula is concentration of particulate matter (μg/m3), inhalation rate (m3/h) and exposure duration (years). Health risk performance was assessed among workers in residential buildings in Beijing. Results showed that blue collar workers of template and steel zone had the highest health risk, while blue collar workers in the office zone had the lowest health risk.

Construction industry is one of the noisiest to work in, and 14% workers exposed to blaring noise have considerable hearing difficulty (Zitzman, 2018). According to that, noise can be considering as a pollutant which has an impact on workers’ health. Kantova (2017) and Zitzman (2018) had identified sources of noises on the construction site and presented support software’s for calculation and evaluation of noise. Ways to reduce noise level were also presented.

In order to improve safety on the construction site Zhang et al. (2015) propose real-time location tracking system for workers, and to visualize workspace use. Workspace occupation parameters were computed depending on work activity level.

Performance Indicators impacting on cost reduction

The economic feasibility of building renovation was identified as a fundamental in many studies employing performance indicators related to the building renovation projects (Kylili et al., 2016). Performance Indicators can be related to direct, indirect, and shadow costs. Direct costs economic performance indicators: capital investment, importance of cost, economic performance, and affordability (1-10 priority level scale), suitability of initial cost, lifecycle cost, project profitability. Indirect costs economic performance indicators: adverse effect on the level of ground water (being agree or disagree in 1-5 scale), impact on tourism values, employment of labor, adaptability and flexibility (1-10 priority level scale), minimum variations cost (being agree or disagree in 1-5 scale), no increase material cost (being agree or disagree in 1-5 scale), stable labor costs, resetting cost of people. Stable labour costs were explained as keeping the cost of work on the project at a constant level. No increase material costs were explained as keeping the cost of materials used in the project at a constant level. All economic performance indicators of direct and indirect cost were presented for the sustainability of building renovation projects according to the research papers review (Kylili et al., 2016). Capital investment can be defined as a sum of money acquired by a company (Kenton, 2020). Initial cost, lifecycle cost, impact on tourism values, resettling cost of people and employment of labor are defined as being very suitable or no suitable in 1-5 scale. Adverse effect on the level of ground water was included in the economic performance indicator because the stakeholders would require minimizing the negative impact on the groundwater level, which would lead to an increase the cost of the project (Kylili et al., 2016). The Shadow cost factor is an environmental performance indicator measured in the currency euro. It represents the highest permissible level of environmental cost for the government per environmental damage unit that the government can endured (Kylili et al., 2016). Not explained indicators listed previously were only mentioned as important due to research review.

Performance factors are often used to minimize the cost of a project (Gabbar, Xiaoli, Abdelsalam, Honarmand (2014). Several economic indicators can be identified. Lifecycle cost or capital cost indicator can be used to assess the economic feasibility of available systems. Operation cost or generation cost can be used to determine fuel consumption and then can be related to fuel price. Risk cost can be analyzed as the equivalent cost for damages and delays caused by power interruptions. It mainly depends on the probability and duration of the interruption. The above factors have been proposed in order to determine the most appropriate energy source, among the wind turbine, solar panel, battery and fuel cell.

Percentage of rework can be used as performance indicator according to the study of Hegazy, Said, and Kassab (2011). Rework can be defined as the effort of re-doing some activity or process that was at the first time done incorrectly. The rework percentage can be calculated as a percentage of the total activity quantity. All data should be obtained from site reports. The research was made as the delay analysis in construction industry in Canada.

It is up to date to develop or to use low-cost sustainable materials as far possible. According to the studies of Arun, Baskar, Geethapriya, Jayabarathi, and Angayarkkani (2021), the cost-effective construction materials can be considered as a performance indicator. As cost effective construction materials e.g.: fly ash, foundry sand, expanded polystyrene, coconut shell, welded mesh, and geogrid can be used. Furthermore, using recycled expanded polystyrene as a construction material, it will be more friendly to environment. Because of that, by using less expensive and more common materials in current region, up to 26.11% cost of total building cost can be saved. Also, transportation cost can be reduced up to 30%, when more regional available materials could be used.

Due to Hammad, Akbarnezhad, and Rey, (2016) the transportation cost can be used as performance indicator. It is often the site engineers or project managers task to positioning temporary facilities on the construction site to minimize transportation cost between these facilities and minimize the cost of the materials handling. Minimisation of the transportation cost can be easily calculated, when the cost of operating transportation equipment, the travel frequency between facilities, and the distance between facilities are known.

According to the SWS Heating project (2019) the following economic indicators were identified: generated cost savings and production cost. Generated cost saving is the expected cost saving which is generated by the energy storage system in a group of buildings. Must be referred to a day or year period and characterized by specific number of cycles. Production costs include expenses like labour, raw materials, and consumable manufacturing supplies.

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References

American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (2015). ASHRAE Handbook: heating, ventilating and air-conditioning applications (I-P Edition). W. Stephen Costock.

Arun, M., Baskar, K., Geethapriya, B.S., Jayabarathi, M., Angayarkkani, R., (2021). Affordable housing: Cost effective construction materials for economically weaker section. Materials Today: Proceedings, 45, 7838-7844.

 Balaras, C. A., Dascalaki, E. G., Droutsa, K. G., Kontoyiannidis, S., Guruz, R., Gudnason, G., (2014). Energy and other Key Performance Indicators for Buildings – Examples for Hellenic Buildings. Global Journal of Energy Technology Research Updates, 1, 71-89

Choe, S., Seo, W., Kang, Y. (2020). Inter- and intra-organizational safety management practice differences in the construction industry. Safety Science, 128.

Gabbar, H. A., Xiaolo, M., Abdelsalam, A. A., Honarmand, N. (2014). Key performance indicators modeling for micro grid design and operation evaluation. International Journal of Distributed Energy Resources and Smart Grids, 10, 219-242.

Gore, S., Song, L., Eldin, N., (2012). Photo-modeling for Construction Site Space Planning.

Hammad, A.W.A., Akbarnezhad, A., Rey, D., (2016). A multi-objective mixed integer nonlinear programming model for construction site layout planning to minimize noise pollution and transport costs. Automation in Construction, 61, 73-85.

Hegazy, T., Said, M., Kassab, M., (2011). Incorporating rework into construction schedule analysis. Automation in Construction, 20, 1051-159.

Kantova, R. (2017). Construction Machines as a Source of Construction noise, Procedia Engineering, 190, 92-99.

 Kenton, W. (2020). Capital Investment. Retrieved from https://www.investopedia.com/terms/c/capital-investment.asp

Khamraev, K., Cheriyan, D., Choi, J. (2021). A review on health risk assessment of PM in the construction industry – Current situation and future directions. Science of the Total Environment, 758,

 Kylili, A., Fokaides, P. A., Jimenez, P. A. L. (2016). Key Performance Indicators (PIs) approach in buildings renovation for the sustainability of the built environment: A review. Renowable and Sustainable Energy Reviews, 56, 906-915

McLeod, S. (2019). Likert Scale Definition, Examples and Analysis. Retrieved from https://www.simplypsychology.org/likert-scale.html

Nabi, M. A., El-adaway, I. H., Dagli, C. (2020). A system Dynamics Model for Construction Safety Behavior. Procedia Computer Science, 168, 249-256

Poh, C. Q. X., Ubeynarayana, C. U., Goh, Y. M. (2018). Safety leading indicators for construction sites: A machine learning approach. Automation in Construction, 93, 375-386

University of Perugia (2019). Key Performance Indicators. Development and Validation of an Innovative Solar Compact Selective-Water-Sorbent-Based Heating System. Deliverable Report, Work Package 2, Deliverable 2.5.

Weisheng L., Ke C., Fan X., Wei P. (2018). Searching for an optimal level of prefabrication in construction: An analytical framework, Journal of Cleaner Production, doi: 10.1016/j.jclepro.2018.07.319

Winge, S., Albrechtsen, E., Arnesen, J. (2019) A comparative analysis of safety management and safety performance in twelve construction projects. Journal of Safety Research, 71, 139-152

Yang, X., Luo, X., Li, H., Luo, X., Guo, H. (2017). Location-basen measurement and visualization for interdependence network on construction sites. Advanced Engineering Informatics, 34, 36-45.

Zhang, S.; Teizer, J.; Pradhananga, N.; Eastman, C. M. (2017). Workforce location tracking to model, visualize and analyze workspace requirements in building information models for construction safety planning. Automation in Construction, 60, 74-86.

Zitzman, L. (2018). How Loud Is Construction Site Noise? Retrieved from https://blog.ansi.org/2018/10/how-loud-is-construction-site-noise/#gref


[1] A learning curve is an interrelationship between a learner’s performance on a work or task and the number of attempts or time which is required for the task to be done; learning curve is a process where employees develop a skill by learning from their mistakes; it can be presented as a direct proportion on a graph

[2] Particulate matter (also particle pollution): the term using for a mixture of solid particles and liquid droplets that can be found in the air.

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