Moscow Rules: A Quantitative Exposé

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Abstract

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.

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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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