Time Prediction Methods and Principles

Abstract

The prominent approach for reducing a problem’s complexity is to decompose it into less complex subproblems, solve each of these, and then aggregate the subsolutions into an overall solution. In time prediction contexts, this approach is typically the basis of what has been referred to as the bottom-up method, the activity-based method, or predictions based on a work breakdown structure. Generally, across a range of domains, decomposition has been found to improve judgement quality and increase prediction accuracy (Armstrong et al in J Bus Res 68:1717–1731, 2015 [1]). In the domain of time predictions, however, there are also situations in which decomposition leads to overoptimistic and less accurate judgements (Jørgensen in Inf Softw Technol 46:3–16, 2004 [2]).