Abstract
Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions’ performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation.
Highlights
Projects ending later and costing more than planned are widespread phenomena in the construction industry [1,2]
Our project duration standard deviation estimates are not indisputably superior when compared to σK
As σK is already better than the project evaluation and review technique (PERT) estimate, we can expect our estimates to double PERT’s accuracy in absolute terms concerning its project duration standard deviation estimate
Summary
Projects ending later and costing more than planned are widespread phenomena in the construction industry [1,2]. This section considers in detail why activity duration variability is the major source of inaccuracy of all deterministic scheduling techniques and what can be done to (partially) overcome that problem. Activities in all projects, construction projects included, suffer from some degree of duration variability [18,19]. Projects are unique, which means that, even when contractors have extensive experience, subsequent projects may differ regarding clients, contract type, location, regulations, labor, equipment, subcontractors, stakeholders, and weather [20]. All these (and many other) factors constitute potential causes of uncertainty and, eventually, of activity duration variability [21]
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