Understanding Merge Bias in Schedule Risk Analysis

Valdahl, Jeffrey; Caddell, Christopher P.
June 2010
AACE International Transactions;2010, pRISK08.1
Academic Journal
In the performance of a probabilistic schedule analysis, more commonly known as a schedule risk analysis, the phenomena of "merge bias" impacts most project results. However, this impact is typically poorly understood by project teams and management, who the analysis is intended to benefit. Merge bias is mentioned in numerous papers and books, but with limited details on how it works and how the impact can be quantified. Simply put, merge bias is the impact of having two or more parallel paths of activities, each with its own variability, merge into one milestone. This paper provides a detailed discussion about how merge bias works and demonstrates the impact through two different scenarios: 1) an increasing number of parallel paths, and 2) two parallel paths with varying degrees of duration variability overlap. It also discusses how to consider and address merge bias in the construction of a schedule risk model. The use of schedule risk analysis to identify probabilistic project completion dates is becoming more common in current project management. This technique generally involves the development of a range of durations for activities in the schedule, followed by a Monte Carlo simulation of the schedule using specialized software. The concept of merge bias is a significant influence in this analysis, but is typically not well understood by project teams when interpreting results. If not fully accounted for, merge bias can lead to unrealistic target dates for key project milestones. Simply put, merge bias is the impact of having two or more parallel paths of activities, each with its own duration variability, merge into one schedule milestone. This schedule logic structure has a drastic effect on probabilistic dates for the milestone and any of its successors. The number of merging parallel paths and the level of overlap between them produce an increasing merge bias effect. Yet the impacts to the overall schedule can be easily shown and communicated to members of the project management team. This paper will demonstrate the merge bias effect, quantify the impacts because of increasing schedule complexity, and provide ways to improve understanding by project stakeholders with varying levels of scheduling knowledge.


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