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Doing is normally distributed, learning is log-normal (hiandrewquinn.github.io)

software development Project Management Learning Curve Log-Normal Distribution

The article explores the difference between the distributions of doing (normally distributed) and learning (log-normally distributed) processes. It discusses how traditional project management techniques fail to account for the log-normal distribution of learning tasks, which leads to underestimation of the time and resources required for software development and other learning-intensive tasks. It also examines the implications of this discrepancy on employment practices, particularly in software development, where specific knowledge and tooling experience are highly valued.
Main Points
- Doing vs. Learning: Distribution DiscrepanciesThe concept of doing is commonly perceived as a normally distributed process, whereas learning curves, exemplified by the 'leaky pipeline' model, follow a log-normal distribution. This challenges conventional project management and estimation techniques, illustrating the inherent unpredictability and risk in learning-based tasks.
- Impact on Software Development and Job MarketThe prevalence of non-normally distributed learning processes impacts software development practices, job market expectations, and the overall approach to tackling new tasks. It underscores the necessity for realistic planning, acknowledgment of learning curves, and the strategic value of prior experience.
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