Key Performance Indicators (KPIs) are a significant part of every successful construction project. Establishing KPIs that provide objective criteria for measuring project success is common in performance measurement on construction projects. A presumption is made that a project is successful if finished on time, within the agreed budget, and with the desired quality, often known as the "iron triangle." According to the evidence, this is far from the truth. In addition to the iron triangle, the construction industry must focus on other crucial success factors. Therefore, this study investigates the essential KPIs for construction projects in Saudi Arabia. This research employed a questionnaire survey as its major data source to determine the most critical KPIs for construction projects. The secondary data was collected from a comprehensive review of relevant literature, and the important performance indicators for construction projects in Saudi Arabia were selected and then evaluated using a questionnaire survey. The study found that the most important KPIs are Time, Cost, Quality, Safety, Sustainable Construction, Client Satisfaction, End-User Satisfaction, Risk management, Productivity of labour, and Profitability. This research adds to the corpus of knowledge on the Saudi Arabian key performance indicators for construction projects.
Research Article
Key Performance Indicators for Project Success in Saudi Arabian Construction Industry
https://doi.org/10.21203/rs.3.rs-2329589/v1
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Construction Project
Key Performance Indicator (KPI)
Project Delay
Project Cost
Saudi Arabia
The construction industry is crucial to every nation's growth. Buildings, roads, and bridges are physical infrastructure examples that may gauge economic progress. Developing a construction project requires many partners, methods, phases and stages of work and much input from the public and private sectors (Okudan et al., 2022). It is important to note that the degree of success in carrying out construction project development activities strongly depends on the quality of the different parties' managerial, financial, technical, and organizational performance (Lee et al., 2013; Takim & Akintoye, 2002). The word "performance" refers to how well an operation meets fundamental measures to fulfil its clients' demands. Ahadzie (2007) defines "performance" in terms of competence as the behavioral skills necessary to achieve the objectives of project-based organizations. The Baldridge National Programmed classifies performance into four (4) categories: product and service, customer-focused, financial & marketplace, and operational. While each category reflects performance, their respective focuses vary (Ofori et al., 2016). Within the framework of a construction project, the success of a project may be evaluated differently by construction companies based on their aims (Neyestani, 2016). What observed measure of success on one project may be considered an indicator of utter failure on another? In reality, it is difficult to determine if a project's performance is a success or a failure since the definition of success is ambiguous among project participants. When a construction project is completed on schedule, within budget, according to specifications, and to the satisfaction of all stakeholders, either individually or collectively, it is deemed successful (Omran et al., 2012). The construction projects are unique, novel, specialized, and time-sensitive. Due to the complexity and unpredictability of projects, project-based organizations face significant challenges. The success of construction projects is difficult to predict (Sun et al., 2017; Jong et al., 2019). This study aims to establish the relevance of KPIs to construction project success, identify the most important performance measures, and adopt a set of key performance indicators (KPIs) to be used by the Kingdom of Saudi Arabian (KSA) construction industry.
THE CONSTRUCTION INDUSTRY IN KSA
Since the 1970s oil discoveries, KSA has undergone a massive development boom. Saudi Arabia has the largest construction industry in the Middle East, spending over USD 120 billion annually and employing over 15% of the country's population (Al-Emad & Rahman, 2017). This surge in the construction industry increased the demand for governmental and private development projects (Al-Sulamy, 2015). According to Shoult (2006), Saudi Arabia's construction boom has been fueled by oil exports. His statement that oil exports account for 80% of the KSA's GDP implies that building activity rises and falls with oil prices. Saudi Arabia joined the world trade organization (WTO) in December 2005, enabling the construction sector to reach out to global organizations. Consequently, the country's GDP rose to the Middle East's highest. Population growth in Saudi Arabia is boosting the need for houses and infrastructures, promising a successful future for the country's construction industry (Mathar et al., 2020). According to a 2008 Saudi Ministry of Economy and Planning study, the construction industry produced 9% of the national GDP. The government concentrated on the construction industry with constant stimulation (Alharbi, 2020). In terms of infrastructure, the government was building railroads linking the north and south. Another line connects Jeddah to Dammam's king Abdul Aziz Port and Jubail's King Fahd Port. An extension of the holy city railway commenced in 2008. It serves Dammam, Jubail, Jeddah, Makkah, and Medina. Riyadh, Makkah, and Medina are all getting railways. Simultaneously, the government promotes private commercial real estate development initiatives (Alharbi, 2020; AlSehaimi, 2011).
Several significant infrastructure and development projects in Saudi Arabia's Vision 2030 are called "Giga projects." The "New Enterprise Operating Model" (NEOM) aims to build a city on the Kingdom's Red Sea coast's northwest coast using cutting-edge urban design and automation technologies. Sustainable technology, zero-carbon infrastructure, and a business-friendly administration will cost $500 billion in the NEOM future metropolis (Dasari et al., 2020). "THE LINE" is a million-person city that retains 95% of nature within NEOM, with no cars, no streets, and carbon emissions (Balabel & Alwetaishi, 2021). The second "Giga project" is the Red Sea. Large-scale tourist resort on Saudi Arabia's Red Sea coast. The Saudi Arabian government allocated more than $23 billion to build a full metro network in Riyadh, the capital city of the Kingdom and one of the largest cities in the Middle East. Riyadh Metro Project, 176 km across six lines and 85 stations, has been under construction since 2013 (Alshalalfah et al., 2018). Riyadh metro project is also part of vision 2030 and one of KSA's "Giga projects" (Habibi, 2019).
THE PROJECT PERFORMANCE MEASUREMENT IN CONSTRUCTION INDUSTRY
The New York Bureau of Municipal Research introduced performance assessment as a distinct procedure in the 1940s. The idea grew and improved during the 1960s and 1970s. In the 1970s, the accounting industry employed financial indicators (lagging indicators) to assess performance. The 1980s witnessed the rise of zero-based budgeting, which became a major concern in the 1990s (Nudurupati et al., 2007; Maya, 2016). Performance measurement can help answer three key questions: "How well does an organization perform?" "How well does an individual perform?" How well is the organization doing? "How much has the organization improved since last time?" (Maya, 2016). Performance measurement aims to improve program efficiency and organizational or project effectiveness by evaluating project performance, including financial and non-financial aspects (Lop et al., 2018). A lack of knowledge, poor contracts, insufficient planning, and a lack of vision are among the issues listed by Palalani in the year 2000. In a Construction project, essential participants engage in multiple ways, continually cooperating inside systems. Construction participants are both customers and suppliers, and their capacity to produce value is vital to successful projects (Love & Holt, 2000). The performance of each stakeholder in the Construction process is strongly interrelated (Lop et al., 2018). Construction projects are regarded as successful if they are completed on time, on budget, and to the customer's satisfaction (Lee et al., 2013; Takim & Akintoye, 2002; Neyestani, 2016; Nudurupati et al., 2007; Maya, 2016).
The Balanced Scorecard (BSC), European Foundation Quality Management (EFQM), Performance PRISM, KPIs, and Malcolm Baldridge for Performance Excellence (MBNQA) are five common performance assessment models used internationally for construction projects (Fig. 1) (Omran et al., 2012; Lop et al., 2018).
KEY PERFORMANCE INDICATORS (KPIs)
KPIs were established and introduced as one of the performance measurement tools, and it has since become the most prominent performance measurement metric in the construction industry, especially after "Rethinking Construction" (Ittner et al., 2003; Lop et al., 2018). Many construction organizations have introduced performance measurement via KPIs. KPIs in construction allow the industry to measure project and organizational performance (Ofori et al., 2016). A KPI measures the performance of an activity that is crucial to the success of an organization or a project (Okuden et al., 2022).
Generally, it is widely accepted that time, cost, and quality are the most important factors to consider when evaluating a project's performance. The success of a construction project can be evaluated using the fundamental criteria of cost, schedule, and quality, which have traditionally been used as hard key performance indicators (KPIs) in construction (Chan & Chan, 2014). According to a researcher, these three key components are known as the "iron triangle" (Atkinson, 1999; Leong et al., 2014).
Soft KPIs like customer and project participant satisfaction are important markers of project success. External data and project management systems are commonly used to create hard KPIs. On the other hand, soft KPIs are based on subjective indications supplied by respondents and can be acquired via surveys or interviews. Soft indicators that measure participant satisfaction with interpersonal interactions may be used to advocate for the importance of stakeholder collaboration in achieving project goals (Nzekwe‐Excel et al., 2010).
In response to the Egan Report, established a KPIs Framework for the UK construction sector, including seven groups: time, cost, quality, client satisfaction, client changes, business performance and health & safety and are characterized by the headline, operational and diagnostic indicators. The Headline Indicators measure a firm's overall "rude" state of health. The Operational Indicators bear on specific aspects of a firm's activities and should enable management to identify and focus on areas for improvement. The Diagnostic Indicators explain why specific headline or operational indicators changes may have occurred. Constructing Excellence in the United Kingdom provides KPI Wall charts for several groups in the UK construction sector each year. These are the UK Economic (all construction), Environment, Respect for People, Consultants, Construction Products, Repairs & Maintenance and Refurbishment (Housing), Non-housing, Housing, and infrastructure, and ME Contractor KPIs.
KPIs for the UK construction sector are divided into three categories (Roberts & Latorre, 2009):
- KPI charts for main sub-divisions;
- Graphs that provide additional analysis of the headline KPIs; and
- Additional indicators requested by users (e.g. contractor satisfaction with the client).
The Scottish Construction Industry's (SCI) KPI framework was first launched in 2007 by the Scottish Construction Centre (SCC) to encourage organizations at all levels within the SCI to use performance measurement. It comprises nine key performance indicators (KPIs): product, service, quality, time, cost, safety, environment, people, and business. The SCI KPIs are based on the KPI suite produced for the UK construction industry by the KPI Working Group. The primary distinction is the addition of "environment" to the SCC KPIs. While this demonstrates the growing importance of environmental concerns in the built environment, it is not a major global construction KPI (Crawford & Lewandowski, 2013).
The Danish construction industry for works have been developed the following fourteen (14) KPIs published by the Benchmark Centre for the Danish Construction Sector (BEC) in 2005: Actual construction time;
- Actual construction time concerning planned construction time;
- Defect remediation within the first year;
- The number of problems discovered during the handover process;
- Frequency of accidents;
- Ratio of contributions
- The margin of contribution per man-hour;
- The margin of contribution per wage crown
- The intensity of work in man-hours per m2;
- Productivity of labour;
- Price changes for the project throughout construction;
- Price per square meter; and
- Customer satisfaction with the construction process; (Rasmussen et al., 2017).
The Construction Industry Institute of the United States of America measures contractors' performance online using four key performance indicators (KPIs): performance, construction productivity, engineering productivity, and practices (Ofori-Kuragu et al., 2016).
This paper's evaluation addressed a wide variety of construction KPIs. The examination reveals many current KPIs, making it difficult for organizations unfamiliar with KPIs to choose appropriate KPIs for measurement. Despite the variety of KPIs reviewed, it is clear that some are utilized more often than others. The more popular KPIs might be used for construction KPIs for the Saudi Construction sector. Time, Cost, Quality, Defects, Productivity, and other construction-related KPIs appear to be recurring themes.
In order to accomplish the objectives, first, the data was collected via a thorough review of relevant literature; through the thorough analysis of related literature, the key performance indicators for construction projects in the Saudi Construction sector were identified. Second, a questionnaire study was performed as the primary source of data collection for this research in order to establish the most critical KPIs for the Saudi construction industry.
Regarding the sample size, the study used the following Slovin's Formula used for the sample data collection. According to Saudi Council Engineer (Aleqt, 2017), Arabia has 230943 registered engineers. For more accurate estimates, we have taken the largest number, which resulted from 24,5000 as the target research population.
C = margin of error, taken as 9% = 0.09.
N= Total population, taken as 245000.
n = Sample size.
Applying the equation:
The respondents were asked to evaluate the most important construction sector KPIs using a five-point Likert scale, and the researched factors were ranked based on the mean item score.
The quantitative data were analyzed using the Statistical Package for the Social Sciences (SPSS), a computer tool designed to analyze data pertaining to social phenomena. The program was used to generate various statistics, including descriptive statistics, which offer a basic overview of all components in the data. The advantages of utilizing SPSS include ranking, analyzing quantitative data, and doing multivariate analysis rapidly (Khosravi & Afshari 2011). SPSS also improves the presentation of data in a logical format, minimizing the time spent calculating scores. However, the quality of the outcomes is greatly reliant on the inputs, highlighting the need to capture the questionnaire's data accurately (Sharma et al., 2017; Sun, 2019).
The study used a 5-point Linkert scale, which provided a wider range of potential scores and increased the statistical analyses available to the researcher. The 5-point Linkert scale is in the following agreement form:
- Strongly Disagree (SD)
- Disagree (D)
- Neutral (N)
- Agree (A)
- Strongly Agree (SA)
The 5-point scale was transformed to a mean item score abbreviated as (MIS).
The computation of the Mean Item Score (MIS) was calculated from the total of all weighted responses and then relating it to the total responses on a particular aspect. The mean item score was adopted to rank the factors from highest to lowest. The Mean Item Score (MIS) is expressed and calculated for each item as follows:
Where.
n1 = number of respondents for strongly disagree;
n2 = number of respondents for disagree;
n3 = Number of respondents for neutral;
n4 = number of respondents for agree;
n5 = number of respondents for extremely likely or strongly agree;
N = Total Number of respondents
Descriptive analysis was used to determine the mean item score, and the standard deviation was then arranged in a descending manner to highlight the height and the least impact. The adequacy of the information depends on the reliability of the data collected from the questionnaire survey. The reliability of the survey data was checked, and the reliability test is important because of the basis for data analysis. Reliability is generally estimated by examining the consistency with which different items express the same concept (Shen et al., 2011). In this study, Cronbach's alpha coefficient method was used to test the reliability of the data. Ceng and Huang (2005) suggested that a value of Cronbach's alpha of 0.7 or higher normally indicates a reliable set of items. However, Hair et al. (2019) consider 0.60 to less than 0.70 as moderate and adequate for use in the study.
The Saudi Construction Industry Field Survey was conducted using a standardized questionnaire sent to the respondents. The 106 returned questionnaires, 85% of the 124 sent out, indicate a fairly excellent return rate (Neuman & Robson, 2014). Findings revealed 19.8% architects, 59.4% civil engineers, 14.2% electrical and 6.6% mechanical engineers. 60.4% have bachelor's degrees, 34.5% have master's, and 4.7% have PhD. When asked about respondents' work experience, the finding showed that 28.3% had between 5 and 10 years of work experience, 51.9% had 11-15 years of experience, and 19.8% had 16 years and above working experience in the construction industry.
Table.1 Demographic Profile of Respondents
|
Respondents information |
Frequency |
Percentage |
|
Education |
|
|
|
Bachelor's |
64 |
60.4 |
|
Master's |
37 |
34.5 |
|
PhD |
5 |
4.7 |
|
Profession |
|
|
|
Architect |
21 |
19.8 |
|
Civil Engineer |
63 |
59.4 |
|
Electrical Engineer |
15 |
14.2 |
|
Mechanical Engineer |
7 |
6.6 |
|
Organization |
|
|
|
Client |
11 |
10.4 |
|
Consultant |
42 |
39.6 |
|
Contractor |
53 |
50.0 |
|
Discipline |
|
|
|
Planning & Management |
16 |
15.1 |
|
Design |
25 |
23.6 |
|
Construction |
65 |
61.3 |
|
Working Experience |
|
|
|
5-10 years |
30 |
28.3 |
|
11-15 years |
55 |
51.9 |
|
16 years and above |
21 |
19.8 |
The respondent's extensive expertise is essential to acquiring high-quality data for any research. In a recent study, these knowledgeable respondents will offer the information needed based on their years of experience. Respondents with a combined employment history of over 11 years dominated the sample, making up 72% of the responses. This finding amply demonstrates the quality of the data gathered during the primary survey. According to the respondents, the most important performance indicators are as follows, based on the ranking using the computed standard devotion (SD), mean
score ( ), and Rank (R) for the listed construction industry's Key Performance Indicators (Table-2); time of project construction (SD=0.57852; x̅=4.3868; R=1); cost of project (SD=0.68726; x̅=4.1792; R=2); quality (SD=0.74232; x̅=4.1038; R=3); safety (SD=0.69732; x̅=4.0943; R=4); Sustainable Construction (SD=0.70888; x̅=4.0472; R=5); Client Satisfaction (SD=0.71040; x̅=3.9906; R=6); End-User Satisfaction (SD=0.78628; x̅=3.9717; R=7); Risk management (SD=0.78628; x̅=3.9528; R=8); Productivity of Labor (SD=0.81451; x̅=3.9434; R=9); and Profitability (SD=0. 79605; x̅=3.9340; R=10).
Table 2 - Construction Projects' Key Performance Indicators
|
KPIs |
Mean item score |
Standard deviation |
Rank |
|
Time of Project |
4.3868 |
0.57852 |
1 |
|
Cost of Project |
4.1792 |
0.68726 |
2 |
|
Quality of Project |
4.1038 |
0.74232 |
3 |
|
Safety |
4.0943 |
0.69732 |
4 |
|
Sustainable Construction |
4.0472 |
0.70888 |
5 |
|
Client Satisfaction |
3.9906 |
0.71040 |
6 |
|
End-User Satisfaction |
3.9717 |
0.78628 |
7 |
|
Risk management |
3.9528 |
0.82094 |
8 |
|
Productivity of Labor |
3.9434 |
0.81451 |
9 |
|
Profitability |
3.9340 |
0.79605 |
10 |
|
Defects |
3.9245 |
0.75212 |
11 |
|
Procurement |
3.9057 |
0.73715 |
12 |
|
Maintainability |
3.8962 |
0.79197 |
13 |
|
Human resource management |
3.8774 |
0.69970 |
14 |
|
Business Performance |
3.8019 |
0.85546 |
15 |
The SPSS statistical package was used to analyze the data. The reliability of the five-point scale used in the survey was determined using Cronbach's coefficient alpha, which determines internal consistency among variables. If Cronbach's alpha is 0.7 or more, the items are likely reliable (Shen et al., 2011; Xu et al., 2012). Item-total Statistics are shown in table no. 4; the first two columns indicated the scale mean and variance if the item was deleted. The mean and variance of the summated scores, excluding item 1, are 55.8302 and 23.399, respectively. The caption "Corrected Item-Total Correlation" were designed to identify the correlation of the item designated with the summated score for all other items, and summated score for all items is above 0.40. A rule of thumb is that these correlation coefficients should be at least 0.40, indicating that the correlation is fair (Sharma, 2016). The next caption, "Squared Multiple Correlation", is the predicted square of multiple correlation coefficient obtained by regressing the identified individual item on all the remaining items. Squared Multiple Correlation (R²) is the sample squared correlation coefficient between the response variable and the regression model's predicted value. It is between 0 and 1. The linear relationship between the response variable and predictors is better the closer it is to 1. The linear relationship gets worse the closer it is to 0 (Cohen et al., 2014). The predicted Squared Multiple Regression Correlation is for Items 1 and 2, 0. 674 and 0.440. Furthermore, the section "Cronbach's alpha if item Deleted" meant that if the researcher deleted one of the items, Cronbach's alpha values were almost the same, even smaller than the items deleted. It followed what had been said that the instrument had a higher consistency and reliability, so it was unnecessary to delete any item from the scale. Hair et al. (2019) consider the study moderate and adequate to be 0.60 to less than 0.70. That means that the five-point scale measurement was accurate because the overall value of the Coefficient alpha test was 0.717, which shows in Table 3, greater than 0.70, which means that this test was credible.
Table 3 – Internal Consistency (Cronbach's)
|
Reliability Statistics |
||
|
Cronbach's Alpha |
Cronbach's Alpha Based on Standardized Items |
N of Items |
|
0.717 |
0.723 |
15 |
Table 4- Item-Total Statistics
|
|
Scale Mean if Item Deleted |
Scale Variance if Item Deleted |
Corrected Item-Total Correlation |
Squared Multiple Correlation |
Cronbach's Alpha if Item Deleted |
|
Cost of Project |
55.8302 |
23.399 |
.430 |
.674 |
.712 |
|
Time of Project |
55.6226 |
22.771 |
.416 |
.440 |
.696 |
|
Quality of Project |
55.9057 |
21.972 |
.413 |
.414 |
.692 |
|
Safety |
55.9151 |
22.307 |
.496 |
.327 |
.695 |
|
Sustainable Construction |
55.9623 |
22.437 |
.566 |
.420 |
.698 |
|
Client Satisfaction |
56.0189 |
21.638 |
.493 |
.419 |
.684 |
|
End-User Satisfaction |
56.0377 |
22.360 |
.626 |
.497 |
.702 |
|
Productivity of Labour |
56.0660 |
21.377 |
.446 |
.665 |
.687 |
|
Profitability |
56.0755 |
22.280 |
.531 |
.698 |
.702 |
|
Procurement |
56.1038 |
22.665 |
.612 |
.557 |
.704 |
|
Risk management |
56.0566 |
24.111 |
.476 |
.486 |
.732 |
|
Maintainability |
56.1132 |
22.730 |
.471 |
.408 |
.709 |
|
Defects |
56.0849 |
21.964 |
.407 |
.518 |
.693 |
|
Human resource management |
56.1321 |
24.116 |
.516 |
.442 |
.724 |
|
Business Performance |
56.2075 |
22.471 |
.571 |
.635 |
.709 |
While the performance of the Saudi construction industry remains a cause of concern, it is anticipated that adopting a set of KPIs would improve construction industry participants in evaluating their performance to improve overall performance levels. The KPIs established in this research were part of a wider pool identified from the literature review and existing KPIs in leading economies with high-performing construction sectors. The approach in this study ensures that the outcomes of the literature study, questionnaire-based survey, and high return rate for the survey could be due to the respondents' high interest in the subject and, in part, to a short questionnaire design that made it easy to complete and return the questionnaires. The returns rate of 82% shows the respondent group as a good representation of the sample and thus reinforces generalizations that can be made for the overall Saudi construction industry. The accumulated total provided a measure of the respective measures' relevance, with higher Mean item score values indicating greater relevance and lower Mean item score values indicating less relevance. The indicators were ranked in order of relative importance to each other. Time of construction received the highest Mean Item score, followed by Cost of Construction and Quality. The fourth place with less score was safety and sustainability construction, followed by Client Satisfaction. Maintainability and Human resource management scored lower, and Business Performance obtained the lowest Means Item Score.
The inclusion of Quality, Cost, and Time in the first three KPIs is consistent with popular construction management literature, which identifies these measures as the ultimate goals of every construction client. The KPIs proposed in this paper are not the only important KPIs. They are the ones deemed most pertinent to the KSA construction industry. These KPIs can serve as a starting point for those in the KSA construction sector who are new to KPIs and performance measurement. They can be used as the foundation for benchmarking performance against best-in-class organizations, measuring performance, and setting targets for improving performance to internationally competitive levels by KSA construction players.
Construction projects significantly impact developing countries' economic, social, and environmental activities. When considering implementation, their sustainability performance should be thoroughly evaluated. Because effective evaluation indicators are rarely available in practice, the sustainability of construction projects is frequently under-assessed. Numerous performance measures are in use, and the sheer number of measures can cause issues for the construction project. Too many, too few, or inappropriate performance measures can have a negative impact on overall performance. In this paper, existing KPI groups were investigated in order to identify the most popular KPIs and the first formal set of KPIs for the KSA construction industry. Popular KPIs identified in the literature were subjected to a survey of selected individuals, and the survey results were validated. This paper established that using performance measures is an effective strategy to enhance project management success.
According to all respondents, the ten most significant key performance indicators for construction projects in Saudi Arabia are construction time, construction cost, quality, safety, sustainable construction, client satisfaction, end-user satisfaction, risk management, labour productivity, and profitability. Moreover, according to the reviewed literature, the most important key performance indicators (KPIs) for construction projects are scope and quality. Further investigation revealed that cost, time, and quality are the three basic and most important performance indicators in construction projects: safety, functionality, and Client Satisfaction.
However, these findings regarding KPIs indicate that project management, risk management, and quality assurance are all regarded as key indicators in the Saudi Arabian construction industry. This demonstrates the Saudi Arabian construction industry's dynamic character since the KPIs mentioned earlier has never been included in prior research of this kind. It is also recommended that future research be conducted to establish methods for measuring the qualitative indicators in the KPI suite developed in this research.
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No competing interests reported.