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Abstract: Accurate time estimation is very critical to ensure smooth operation and timely completion of any construction project delivery. In determining the time of the project completion the only known methodology currently used by JKR is based on prediction from the experience of completing past project. The cause of inaccurate of time estimation was determined by analysed the data from JKR's database and questionnaire. The study analysed the cause of the Extension of Time given to contractors. A total of one hundred fifty (150) questionnaires were distributed to JKR's staff and contractors involved in project management and construction fields to obtain construction professional experience that how much the delay causes have been affecting the timely completion of the projects. All the questionnaires were processed and analysed using statistical software. Results of the questionnaires were ranks based on the frequency and relative importance indices. Statistical software such as SPSS and Microsoft Excel was employed to detect the differences between the respondent groups with respect to overall agreed delay causes. From SKALA's record analysis was done to four criteria that related that could be related to delay of the project. The criterias were time, cost, location and causes of extension of time to the project. Based on the analysis conducted it was found that the project with lower cost would have lower risk of delay. By using current time estimation by JKR shows that 25.18% of building projects completed with out EOT and 74.82% were completed with EOT. Location of the project shows that the project at developed state had less delay project. From the cause of EOT shows that most of the delay was due to the management team by both JKR and the contractors. Scheduling should be used for the full project cycle and should fully use as tools for tracking and monitoring the project precisely to reduce the delay of the project.
In project management delivering the project within the stipulated time in the contract is the most important factor to be focused by the contractor and the implementer. Time is one of the three factors in project management should be given priority beside cost and quality. These three factors are related to each other and give an effect if one of these factors is neglected. Time estimation has been identified as one of the key performance to be addressed in providing best value to construction client. To predict the construction duration of project based variables which are construction duration, building type, procurement route, contractor selection method, type of client, contract value, building function and complexity of the building.
Construction management decisions are made based on schedules that are developed during the early planning stage of projects, many possible scenarios also should be taken into consideration during construction. Construction programs are of utmost importance for a successful timely delivery of buildings or infrastructure projects. A well developed project schedule model is a dynamic tool that can be used to predict the expected completion date of the project.
There is no specific tool in determining the accurate time for project duration practices in JKR. Most of the project durations were based on previous durations of the project which were not the same component of each projects. By using the previous experience it may not indicate the correct duration for the project. From this estimation of project duration, JKR use the history of project duration based on the cost of the project, the size of the project, location and complexity of the project. This method is used since the existence of JKR. No specific method to estimate the duration of the project.
+ Master Student, Faculty of Civil Engineering, Universiti Teknologi Malaysia.
++ Supervisor, PM Dr, Lecturer of Faculty of Civil Engineering, Universiti Teknologi Malaysia.
A well planned project implementation schedule is relatively significant to function accordingly in determining completion of project without delay as a result could affect the other activities expected by the end-user. Good schedule ensured the implementation of realistic; given ample time for activities such as design approval procurement, construction, tests the line and so on.
Improper scheduling will cause the projects having extension of time, or termination. This will affect the end user therefore involving additional expenses, including financial liability, employee relocation and storage of equipment and problems inventory. Delays in the completion of an entire project due to poor scheduling can also create havoc for owners who are eager to start using the constructed facilities (Gomar et al., 2002).
1.1 Problem Statement
Delivering the project within the stipulated time frame as stated in the contract to the client is utmost important to JKR as an implementer. The main problem in JKR's current practice is estimating accurate time in their project. Failing to meet datelines in delivering the project to the client will determine the performance of JKR. One of JKR's objectives is to deliver the entire project in time as agreed with the client. Inaccurate time estimation can lead to the delay in completion of the project. Inaccurate time estimation can cause the client additional operational cost.
Improper determination of the project duration would show the performance capability of JKR as a technical department in government. This is one of the reasons for project to be given an extension of time (EOT) beside other reason such as the contractor selected cannot give full commitment to the project. Base on the JKR's record most of the project have at least one EOT.
1.2 Aim of the study
The main aim of this study is to determine the cause of the delay in the construction phase that lead to inaccurate time estimation in JKR's project.
1.3 Objectives of the study
To identify the factors that contribute to delays in JKR projects
To study the relationship between JKR's estimated times with the actual completion base on 5 years historical data
To identifies factors to improve JKR time estimating
1.4 Scope of the study
This study was focused on building project by JKR only. Historical data for this study rely on project that had been completed within past six (6) years (2004 to 2010). Data were taken from JKR project database module, SKALA (Sistem Kontrak, Selia dan Lapor). The data extracted from SKALA mainframe was analysed and segregate accordingly. The data were extracted into smaller item base on the nature of work. The data were comprise of all projects that supervised by JKR. From that database only data on building project was extracted and analysed. Besides document search uses data from SKALA, questionnaire distributed to get related data from the person who involved directly with JKR project. Questionnaire was distributed to all JKR District Engineers, Head of Project Team (HOPT), Head of Design Team (HODT) and contractors involved in JKR project.
2.0 METHODOLOGY OF THE STUDY
The methodology used in conducting this study is through literature search, data collection from JKR's SKALA database and questionnaires survey to JKR's staff who directly involved in determining the time frame of the project and contractors.
Data collection gathered from the project database as stated in the scope of study. From the results, the questionnaires survey conducted among JKR staff within the category of the study to assess their opinions of the findings towards the objectives of the study. The qualitative data generated from the questionnaires have been analysed using statistical method to support the study findings.
Based on the records from SKALA (2004 to 2010) out of 3,027 projects supervised by JKR, 762 (25.18%) projects were delivered ahead and on time stated in contract. Total number of 2,265 (74.82%) projects was delivered beyond the datelines of the contract.
The questionnaire was, distributed via e-mail and was also distributed hand to hand, ordinary post, faxes etc. to the respondent. The sample consisted of JKR's engineering professionals working all over Malaysia and contractors involve in JKR project. There is no any logical or mathematical process for sampling was employed in this study.
The five points Likert-scale was used as an instrument in the field survey questionnaires. Respondents were asked to indicate their level of agreement or disagreement according to the following scale: 1 - Least Agreeable, 2 - Slightly Agreeable, 3 - Moderately Agreeable, 4 - Agreeable and 5 - strongly Agreeable. The aim of the questionnaire was to get the significant cause of the delay and the factors that can be considered to improve JKR time estimating for construction projects based on the respondents' experience and knowledge.
All returned questionnaires were browsed to identify errors, mission and ambiguities. All the data were coded before input into the database and analysed using statistical computer programs such as Microsoft Excel and Statistical Package for Social Science (SPSS) to generate diagnostic information used for analysing the data accordingly.
SKALA's data was used for real data analysing. Detail data were extracted from mainframe database and was authorised by the officer from SKALA Section. The data were a real-time data as for 1st. November 2010. Details of the data were extracted base on the extension of time given to contractors. All data were sorted base on type of construction (i.e., road, building, water works, ICT). All the relevant data was ranked based on frequency of occurrence. For this research only building projects were analysed for the cause of delay and for the percentage of EOT duration given to the contractor.
3.0 RESULTS AND DISCUSSION
Total of one hundred twenty (120) questionnaires were distributed to JKR's District Engineers, selected project team at JKR Headquarters and thirty (30) to contractors involved in JKR project. Only fifty one (51) respondents returned the questionnaire. (Appendix A)
The questionnaire was divided into three sections. Section A requested background information about the respondents. Section B of the questionnaire focused on the factors that contributed to delay of JKR project. Section C of the questionnaire was to indentify factors to improve JKR time estimating.
The data were analysed using frequency, mean value and relative importance index. Using mean value the question was ranked accordingly to get the final value that determines the objective was achieved.
3.1.1 Section A - Respondent background
Section A question mainly about the background of the respondent. The demography of the respondents were 42 (82.4%) from JKR inclusive of all discipline and nine (17.6%) from contractors.
Experience of the respondents was asked in this section, whereas the respondent was group and ranked based on working durations. The respondents with working experience less than five years were 23.52%, six years to ten years (17.65%), 11 years to 15 years (13.73%), 16 years to 20 years (9.80%) and more than 21 years were 27.45%. Discipline of the respondents was classified as Civil Engineer (49.02%), Mechanical Engineers (13.73%), Electrical Engineers (11.77%), Architect (9.80%), Quantity Surveyors (13.73%) and others were 1.96%.
3.1.2 Section B - Factors that contribute to delays of JKR project
In this section respondent were given 43 questions about the factors that contributed to delay of JKR project. The questions were divided into six main factors. The factors were experience, locations, financial, management, scheduling and monitoring of the projects. All the data were analysed using SPSS software and MS Excel. The data were first analysed on the reliability of the factors using Cronbach's Alpha. George and Mallery (2003) provide the following rules of thumb: ">0.9 - Excellent, > 0.8 - Good, > 0.7 - Acceptable, > 0.6 - Questionable, > 0.5 - Poor and < 0.5 - Unacceptable". Results of Cronbach's Alpha for Section A were acceptable as it ranged from 0.8607 to 0.9004. (Appendix A)
Ranking of the questions were conducted based on relative importance index (RII) using the formula
RII = âˆ‘W
A * N
where W is the weighting given to each factor by the respondents (ranging from 1 to 5), A is the highest weight (i.e. 5 in this case) and N is the total number of respondents. Kometa et al. (1994) used the relative importance index method to determine the relative importance of the various causes and effects of delays. The RII value had a range from 0 to 1 (0 not inclusive), higher the value of RII, more important was the cause or effect of delays. From analysis conducted the results were ranging from 0.49 to 0.87. The ranking were done based on highest RII to the lowest. The ranking would show the factors that contribute to delays of JKR project base on the questionnaire.
Next ranking would be based on the mean score from the questionnaire. The value of the mean is developed from SPSS software for each question. The score were ranging from 2.4 to 4.94. Nirmal Kumar Acharya et al. (2006) developed range for mean as
Very significant delay factors (Mean score above 3.5),
Moderately significant delay factors (Mean score between 3.0-3.5),
Moderately significant delay factors (Mean score between 2.5-3.0)
Slightly significant delay factors (Mean score between 1.5-2.5).
From that range the questions were arranged and top 5 of the question were selected. (Appendix B)
3.1.2 Section C - Indentifies factors to improve JKR time estimating.
In Section C, 24 questions were divided into seven factors. The factors were experience, cost, project size, location, the design aspect, scheduling and guidelines. The process of analysing the data was conducted same as in Section B. The results of reliability using Cronbach's Alpha were ranging from 0.6827 to 0.9087. The result is acceptable base on a range stated by George and Mallery (2003). The next method of analysing used in this section was relative importance index. The value ranged from 0 to 1 as mentioned by Kometa et al. (1994). The values of RII for this section were ranging from 0.682 to 0.894. It is acceptable and the top 5 of the ranking be analysed.
Next step was ranked the question using mean value. The values were ranging from 3.4118 to 4.4706. Based on Nirmal Kumar Acharya et al. (2006) the mean from the questionnaire were acceptable and top 5 of the question were chosen to determine the factor to improve JKR time estimating. (Appendix B)
3.2 Document Search from JKR's project database.
Completed project that recorded in SKALA database has been divided into time, cost and locations of the project. The cause of EOT given to the contractors were analysed to find what was the highest cause that lead to project cannot complete within the original estimated time in the contract.
The data from JKR's project database were sieved by type of project. Only building projects completed from 2004 to 2010 were selected for further analysis. Only data related to time or duration were analysed. From the database the contractual duration and actual completed durations were calculated. The ratio between actual and contractual duration in percentage were taken as one of the criteria for comparison. The data were ranged according to the ratio and tabulated as
<0% to -50%, Completed on time and ahead of schedule
1% to 25%,
26% to 50%,
51% to 75%, Completed behind schedule
76% to 100%
From the analysis only 25.18% of building projects completed without EOT and 74.82% were completed with EOT. This shows that almost 75% of JKR's building project was inaccurate time estimation. (Appendix C)
It was found that cost of project contributed an impact on the completion of the project. From the analysis carried out on the cost it shows that cost of project less that RM5 millions (41.03%) completed on time or ahead of schedule. Project that cost between RM51 millions to RM100 millions were the projects that completed behind schedule (100%). From the analysis it was found that low cost project can completed within or ahead of estimated time of the project. For the project with higher cost, the estimated time of the project cannot be achieved. (Appendix D)
Locations of the project gave an impact to completion of the project. From the data analysed 41.67% of projects in Putrajaya were completed on time or ahead of schedule and 88.9% of the projects in Perlis were completed behind schedule. The analysis shows that location of the project within developed state were the states that have more projects completed within or ahead of estimated time of the projects. In this analysis the state that have a completed project more than 25% ahead of estimated time were considered and the states are Putrajaya (41.67%), Kelantan (35.03%), Selangor (33.91%), Negeri Sembilan (31.21%), Johor (30.39%), Perak (29.74%), Kuala Lumpur (29.42%) and Pulau Pinang (26.88%). (Appendix E)
3.2.4 Cause of EOT
Beside the duration the cause of the EOT also analysed to find out what were the factor that cause JKR building project were given EOT. The cause of EOT were categorised as
Current issue (shortage of labour),
JKR's instruction (late issuing construction drawing),
special privilege (government's instruction for Variation of price (VOP)),
contractual need (supplementary agreement),
All causes of EOT analysed and categorised accordingly and frequency of occurrence were used to find the causes that frequently make the building projects not completed as per contract. The causes of the delay were ranked and arranged to find the most causes used for approving the EOT. From the analysis, it was found that the causes of that contributed to EOT were by Third Party (24.75%), Contractual Need (19.37%) and JKR's Instructions (11.12%). (Appendix F)
From the analysis conducted through a questionnaire on Section B, four factors were determined contributed to the delay of JKR projects. The factors were Monitoring (by JKR and Contractor), Experience (planning and scheduling), Management (design changes) and Financial (payment to sub-contractor) (Appendix B). Survey results by Chan and Kumaraswamy (1997) indicated that five major causes of delays were; poor site management and supervision, unforeseen ground conditions, low speed of decision making involving all project teams, client initiated variations and necessary variations of works.
Base on data from JKR database it was found that with the current method of time estimation for JKR projects, only 25.18% of projects completed on time as per contract and 74.82% were completed behind time stated in the contract and was given EOT to complete the project. According to Frimpong et al. (2000), indicated that 75% of the projects exceeded the original project schedule and cost whereas only 25% were completed within the budget and on time.
Analysing JKR's database of the project it shows that the estimated time by JKR were related with cost and location of the project. Low cost project can completed within the estimated time compare to high cost project. Location of the project contributed to delay of the project where most of the project in developed states completed within the time.
From the analysis of cause of JKR projects delay it was found that 24.75% were contributed by third party (supplier to the contractor).
In Section C, two factors needed to improve JKR time estimation. The factors were design aspect (JKR has to be clear what the client want and complexity of the design to take into account when determining the time for the project) and Scheduling (both JKR and Contractor need to understand the importance of scheduling as all planned works or tasks in work scheduling must be follow) (Appendix B).
With the fact that was stated above it is recommended that further research should be done in order to determine the method to improve time estimation in JKR projects. Further research can be done to produce mathematical formula for determining the time of the project.