A Working Week Simulation Approach to Forecast Personal Well-Being

Abstract

Billions of people work every week. Forecasting which tasks gets done in a working week is important because it could help workers understand (i) whether their workload is manageable and (ii) which task scheduling approach helps to maximize the amount of work done and/or minimize the negative consequences of unfinished work. Here we present a working week simulation prototype, R2, and showcase how it can be used to forecast the working week for three archetypical workers. We show that R2 forecasts are sensitive to different task loads, task scheduling strategies and different levels of emerging work complications. We also highlight how R2 supports a new type of validation setting, namely that of user self-validation, and discuss the advantages and drawbacks of this new validation approach. We provide R2 as an online platform to allow users to create their own worker profile and task lists, and believe the tool could serve as a starting point for more in-depth research efforts on user-centric working week modelling.