Learning, Unlearning and Re-learning Curves (Volume IV of the Working Guides to Estimating & Forecasting series) focuses in on Learning Curves, and the various tried and tested models of Wright, Crawford, DeJong, Towill-Bevis and others. It explores the differences and similarities between the various models and examines the key properties that Estimators and Forecasters can exploit.A discussion about Learning Curve Cost Drivers leads to the consideration of a little used but very powerful technique of Learning Curve modelling called Segmentation, which looks at an organisation's complex learning curve as the product of multiple shallower learning curves. Perhaps the biggest benefit is that it simplifies the calculations in Microsoft Excel where there is a change in the rate of learning observed or expected. The same technique can be used to model and calibrate discontinuities in the learning process that result in setbacks and uplifts in time or cost. This technique is compa
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