Transactions on Information and Communications Technologies vol 19, 1997 WIT Press, ISSN

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1 KNOWLEDGE OF RISK IN CONSTRUCTION SCHEDULING John Christian Associate Dean of Engineering and M. P. Gillin Chair in Construction Engineering and Management, U.N.B., P.O. Box 4400, Fredericton, NB, CANADA. Bruce R. Mulholland Senior Engineer, NB Power, 515 King Street, Fredericton, NB, CANADA. Abstract The degree of uncertainty which surrounds the accuracy of a schedule in construction is one of the key factors which extends the expected finish dates on many construction projects. This paper describes a process that enables a systematic assessment of schedule uncertainty to be made using four dimensions of schedule uncertainty. The evaluation of a knowledge base of schedule related risks is described. A Hypercard application program provides an information module which is used so that schedule risks can be identified. A spreadsheet is used to model schedule risk and determine the expected project completion date, the importance of each risk, and other knowledge and statistical data. 1 Introduction The accurate evaluation of the time duration of activities and the completion time in a construction schedule is closely related to a formal assessment of the uncertainty in a project during the conceptual stage. In the research described in this paper the problems encountered on projects using traditional project scheduling processes which have developed over the past thirty years were considered. The inherent uncertain and risky environment in construction projects was reviewed. This information was then used to develop a knowledge base aimed at retaining intelligence learned from previous projects. If a system for the assessment of schedule risk could be developed, it was considered that the effectiveness of traditional project scheduling processes could be improved.

2 Data has been recorded in the construction industry to indicate that since the early 1970's construction project completion times have been increasing. At the same time the regular occurrences of schedule overrun has become a continuing source of concern for the construction industry and its clients. One study has indicated that 50% of completed projects overrun the planned schedule by one month or more. There are many reasons for an overrun in a schedule. The degree of uncertainty encountered in the internal and external environment of a project is a central factor in determining whether or not there will be a schedule overrun. Project uncertainty can influence the degree of predictability in the performance time of the engineering, procurement and construction sequences of a project and the effectiveness of project management. An underestimate of performance times leads to a reduction in the availability of resources and causes costly delays, whereas an overestimate affects planning effectiveness. Risk should therefore be identified and analyzed. The valuable knowledge and experience that results from constructing a facility are, however, not normally readily available for new projects, particularly for large and mega projects. Yet, it has been widely recognized that this type of information and experience improves the future ability of the construction industry to construct similar or related facilities. The shortage of past knowledge or loss of experience can create problems as this type of intelligence will eventually be unavailable for current and future projects. Employees who have retired, resigned, or die take their knowledge and experience with them. Yet, most construction companies must rely heavily on the expertise of their engineers and construction management staff to obtain and carry out their work. However, a significant amount of intelligence, in most cases undocumented, will leave the industry with the retirement of these experienced professionals, many of whom have gained important knowledge and experience during projects in the 1950's to the 1990's. 2 Determination of Schedule Risks In order to formally assess uncertainty in a construction project a list of schedulerelated risk factors, typical of construction projects, was developed. The list was compiled from an extensive survey of sources of project experience. The first source was the experience from work done by NB Power to identify and eliminate problems in the proposed construction of a second nuclear unit at the Point Lepreau Nuclear Generating Station. A comprehensive review of current literature focusing on articles that addressed schedule success and failure was the second source. A third information source was a series of reports concerning the state of the US construction industry produced by the Construction Industry Institute. Two risk analysis technologies were then reviewed in detail: 1. Risk identification and measurement processes, and 2. Computer technologies to support the execution of these processes.

3 Following this review, a computer-based risk factor documentation and identification system was developed using Hypercard software and a Macintosh computer. Procedures to assess the effects of the risks in a schedule were then developed. Figure 1 shows the effects of uncertainty on schedule predictions over the project lifecycle. 3 Knowledge Base of Schedule Related Risks Table 1 indicates some of the principal characteristics of successful and unsuccessful projects which have been determined to influence the effectiveness of the project management function ("Project Control for Engineering" 1986). Table 1 Characteristics of successful and unsuccessful projects Successful Projects Unsuccessful projects Well-defined scope Ill-defined scope Early, extensive planning Poor planning Good leadership and supervision Poor management and controls Involved, positive owner relationship Poor communication between functions Good liaison among participants Unrealistic schedules and budgets Quick response to changes Poor quality of personnel Engineering concerned with total project Excessive changes These characteristics define the factors that are significant in effective project management in a general way but a more precise and systematic procedure was considered necessary to create a knowledge base to assess schedule risk. In order to create a knowledge base of schedule related risks, four dimensions of schedule uncertainty were devised to provide the framework for a process to enable a systematic and structured assessment of schedule risk to be undertaken. Refer to Figure 2.

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5 Engineering Procurement Construction Management RISK IN A SCHEDULE Figure 2. Dimensions of uncertainty in a schedule Risk factors on most construction projects are very numerous. A database of schedule related risks on typical construction projects was therefore compiled using the sources of knowledge and experience previously mentioned. Extracts from the database are shown later in Table 2. 4 Assessment of Schedule Risk The assessment of schedule risk system developed includes three key features: 1. A hypertext information system for schedule risk identification 2. A model to describe and evaluate project uncertainty, and 3. Information to assist the users in selecting a realistic time duration. The system has some concepts that differentiate it from the traditional project scheduling processes. The concepts are: 1) it uses uncertainty and probability information, and 2) it works at a summary level or detail. This differs from the traditional project scheduling processes which tend to focus on detail and use deterministic most likely time estimates. Classic risk analysis is undertaken in three iterative phases. Refer to Figure 3. RISK IDENTIFICATION RISK MEASUREMENT RISK MANAGEMENT Figure 3. Risk analysis process 4. The system developed deals with the first two steps and is described in Figure

6 CONCEPTUAL PROJECT SCHEDULE KNOWLEDGE EXPERIENCE INTELLIGENCE INPUT RISK IDENTIFICATION Hypercard RISK MEASUREMENT Spreadsheet OUTPUT Schedule Times Risk Profiles Figure 4. System - Assessment of Schedule Risk 5 Hardware and Software Requirements The system was developed using a Macintosh PC and commercially available application programs called HyperCard and Excel. In the structure of the system, the HyperCard application provides an information module which can be used as a utility for the purposes of a schedule risk identification process. Refer to Figure 5. The Excel spreadsheet is the tool used for modelling the effects of the risks on the project performance time. Hypertext is a database management system that provides electronic connections in a non-linear way between both textual and graphic files of information. A Hypertext data base management system is composed of objects and links. The objects represent information that can be displayed on a computer screen. The links allow a user to traverse between the objects. The links provide a capability of organizing and then interactively finding information in the data base. The key advantage of Hypertext is that it allows the user to jump from idea to idea depending on the user's interests. By bringing together information linked with advice and references in a single-user-friendly data base, hypertext software can provide the means to store and expeditiously browse through large amounts of information. 6 Risk Identification Figure 5 shows the overall structure of the system. The system structure is hierarchical. It begins at the project level and branches to the four dimensions of schedule uncertainty: engineering, procurement, construction, and project management. Within each dimension specific risks are identified with pertinent

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8 7 Risk Analysis A frequent problem in traditional project scheduling processes is the difficulty of directly using the outputs to analyze and manage risks. The system which was developed can answer three key questions for the decision-maker: 1) What is the probability of achieving the planned schedule? (This tells the owner/project team if there is a problem). The probability can be read directly from a cumulative density function. 2) What is the worst the schedule can get? (This tells the owner/project team the size of the problem). The probability can be read directly from a cumulative density function. 3) What is the ranking of decision variables? (This tells the owner and project team what they need to do first, second,... etc., to improve the probability of achieving the planned schedule and/or reduce the risk of exposure). Extracts from the Excel database used for modelling the uncertainty in a project is shown in Table 2. Table 2 Extracts from Excel database used for modelling project uncertainty Risk # Risk source Imp. Description 30 Productivity M Actual engrg. hrs > planned 90 Design Criteria M Availability of well documented design standards 140 Drawing Production H Accuracy of # of dwgs. & hrs. per dwg., including CADD requirements 150 Early Engineering H Ability to complete engrg. deliverables, such as building layouts and loads for other disciplines 160 Engrg. Resources M An accurate assessment & schedule for resources 170 EIA Impacts H Environment assessment reqts. affecting the project scope 190 Scope Definition H Adequate scope definition at the initiation of the project

9 Using the optimistic, likely and pessimistic times, the analysis then gives the following information for each risk: Expected elapsed time for activity Variance of an activity's performance time distribution Relative importance Standard deviation of a performance time It is then possible to perform a sensitivity analysis. The purpose of the sensitivity analysis is to examine the effects on the schedule of changes to the planned strategies and tactics which explicitly or implicitly have been assumed for the project. 8 Use of Model The assessment of schedule risk is accomplished by: 1. Using procedures to systematically structure the project's uncertainty; 2. Using probability and decision-analysis techniques to measure the effects of risks on the performance time for each phase of the project; 3. Using a PERT based model to propagate the risks' effects on the overall project performance time, and 4. Analysing the outputs. The outputs of the risk modelling and analysis are probability statements and distributions indicating the critical path activities' risk profiles and the range of the probable project performance time. The strength and usefulness of the system is mainly derived by executing the procedures used to model the schedule risk. The modelling process identifies the routine and strategic risks that were used in establishing the base case schedule. The process therefore enables the decision-makers to explicitly recognize the choices and trade-offs between competing strategies and tactics which are involved in the execution of a project. The scheduling of major construction projects can greatly benefit from the integration of an assessment of schedule risk process with the traditional project scheduling processes. The outputs of the process indicate project performance time, the effects of uncertainties, and the probability of achieving the target schedule. The outputs also identify the main risk causes and provide the basis for corrective actions to reduce risk levels. A sample of the system's simulation capability is shown in Figures 6 and 7.

10 Risk # Risk Source Importance Level Confidence Level Correlation Description 30 Productivity M H N Actual engineering hrs > planned 31 Engr'g centres M H Y Geographic location of engineering staff 32 Engr'g resource pool M H Y Depth & qualifications of engineering replacement resources 33 Engr'g estimate M H Y Accuracy of the engineering estimate 34 Material substitution M M Y Redesign due to material substitution 35 Qualified staff M M Y Capability to perform the work in the allowable time frame 90 Design Criteria M M N Availability of well documented design standards 91 Code changes M H Y Changes to codes which affect the project design criteria 92 Site investigation H H Y Problems or engineering changes due to insufficient site investigation 93 Design standards M M Y Availability of well documented design standards 94 Technology M H Y Degree of uncertainty in the technology Figure 6. A Sample of the Systems Simulation Capability

11 Engineering Risks Importance Level Confidence Level T" opt T" nor" T"pes te Vt Rel. Imp. Ref. Imp. x Time Productivity M H % 7.53 Design Errors M L % 1.87 Design Criteria M M % 4.48 Engr'g & Procurement M H % 2.25 Drawing Production H M % 2.21 Early Engineering H M % 3.75 Engineering Resources M H % 3.72 EIA Impacts H M % 6.96 Scope Definition H M % 4.98 T" - construction time, te - expected activity performance time, Vt - variance (All times in months) Probability distribution Selected sched. time (Ts) Probability (T<Ts) Cumulative Density Function Prob. project time < Ts 0% 0% 1% 54% 91% 96% 99% 100% Figure 7. A Sample of the Systems Simulation Capability

12 9 Conclusions Problems exist with traditional project scheduling processes in construction. Many of the problems can be traced to the manner in which the traditional project scheduling processes are applied. Therefore, many of the problems which limit the effectiveness of construction schedules could be improved by planning in a more realistic manner. Schedules are prepared during the conceptual stage of a project, when uncertainty is usually high. One of the key problems with traditional project scheduling processes is that they do not explicitly evaluate project uncertainty. That is why traditional project scheduling processes, which use deterministic network based models, have often demonstrated relatively poor long range predictions. Furthermore, the processes currently being used do not record the causes of a delay. An increase in the effectiveness of traditional project scheduling processes can be achieved through the provision of an assessment of schedule risk. The system described in this paper for the assessment of schedule risk is a structured approach to enable the sources of risk in a project to be identified. Based on those risks the range of schedule outcomes can be determined. The system should also facilitate a transition from traditional deterministic scheduling to probabilistic decisionmaking schedule management. The system provides procedures to: 1. Describe the schedule risks. 2. Measure the schedule risk. 3. Analysis and edit the results. Experience with risk assessment indicates that by developing the input data and reviewing the results, the project team is able to understand and manage their projects more effectively. Keywords: Risk, uncertainty, construction schedules, hypercard, spreadsheet Bibliography 1. Bubbers, G., and Christian, J. (1992), "Hypertext and Claims Analysis." Journal Construction Engineering and Management ASCE, Vol. 118, p Christian, J. and Mulholland, B. (1996), "Uncertainty and Risk in Construction Projects", CSCE Annual Conference, Edmonton, Vol. 1, p Mulholland, B. and Christian, J. (1996), "The Development of a System for the Assessment of Schedule Risk", CSCE Annual Conference, Edmonton, Vol. 1, p Mulholland, B. (1995), "The Assessment of Schedule Risk in Construction

13 Projects", M.Sc.E. Thesis, University of New Brunswick, Canada. 5. "Project Control for Engineering" (1986), Publication 6-1, The Business Roundtable, New York. Acknowledgements The authors would like to acknowledge the cooperation of the New Brunswick Electric Power Commission and the University of New Brunswick. Funding by the Natural Sciences and Engineering Research Council of Canada is also gratefully acknowledged.