Predicting the Dynamics of Earned Value Creation in the Presence of Technical Debt

Technical debt, the long-term impact of decisions made to achieve a short-term benefit, has a unique impact on a project schedule. Technical debt does not impact the ability to complete the task on which it is incurred but rather impacts successor tasks causing unplanned schedule delays or budget increases. The impact of technical debt is uncertain and therefore must be modeled probabilistically. When unaccounted for and unmanaged, technical debt can build up in the project with increasing impact, eventually forcing forward progress to stop while the technical debt is remedied. Traditional project scheduling methods allow for uncertain task durations but do not provide explicit means of modeling the impacts of technical debt. Instead, they assume that each task is unaffected by the completion status of its predecessors and its duration is only dependent upon the initial estimates. This research addresses this gap by providing a novel model of the impact of technical debt on the project schedule through estimating the dynamics of value creation in the presence of technical debt. Equations are developed for estimating the probabilistic impacts of technical debt on the generation of earned value. These equations are then inverted and used to calculate task duration in the presence of technical debt and included in a Monte Carlo analysis. Comparisons are made to an existing Monte Carlo schedule analysis and technical debt impacts are explored.