This article analyzes the performance of the MoSCoW method to deliver all features in each of its categories: Must Have, Should Have and Could Have using Monte Carlo simulation. The analysis shows that under MoSCoW rules, a team ought to be able to deliver all Must Have features for underestimations of up to 100% with very high probability. The conclusions reached are important for developers as well as for project sponsors to know how much faith to put on any commitments made.
CITATION STYLE
Miranda, E. (2022). Moscow Rules: A Quantitative Exposé. In Lecture Notes in Business Information Processing (Vol. 445 LNBIP, pp. 19–34). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-08169-9_2
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