The core of this chapter consists of applications of models of aggregation to real-world time-series data of per-person action effects, using a number of different estimation techniques including analysis of variance, ordinary-least-squares regressions, and spectral analysis using Fourier’s transforms. The data sets were generated per-person in workplace settings. In each case, the analysis stopped with estimation of a univariate model of streams of per-person action effects in job performances. The illustrated estimations pertain to paid-employment activities within the bounds of specific institutional forms. The principal activities were understood and conducted within multi-person coordinations and competitive/cooperative relations. The time-series data of process outcomes, reflecting those dynamics, were compiled over months of multi-person per-person observations. Data for conditional variables could have been added, creating more complex multi-person multifactor contingency models. Present intent was restricted to illustration of what can be accomplished, however, rather than extending into the contingent dynamics of production, as would be found in a complete research monograph.