Abstract
This research proposes and investigates an equation for productivity in hybrid workflows regarding its robustness towards the definition of workflows as a hybrid probabilistic systems. The proposed equation and its derivations were formulated through a theoretical framework about information theory, probabilities and complex adaptive systems. By defining a productivity equation for organism-machine-environment interactions, discrete and continuous variables that constitute the systems can be controlled by a mathematical framework where prediction and monitoring aspects of optimization are possible without the limitation of strict empirical methods.
Highlights
Most human labor organizations emphasize control methods and optimization in order to achieve high standards of productivity
These random variables of the system consisting of information (I), processing (Ii ) and time (T), the event i can be predicted by the following mathematical framework
The mathematical modelling that describes information flows in the workflows can be defined as a probability event when from a given event i by Equation (1) of the interaction between given discrete information variables (I), individual experience individual experience/processing performances (Ii) and defining the time T as a function of I for the execution of individual or group work/between agents/machines reaching precision (P), assumes for i 7 inductive derivations and 8 definitions, like: A
Summary
Most human labor organizations emphasize control methods and optimization in order to achieve high standards of productivity. Considering only the physical aspects of labor routines (discrete variables) such as products properties or services quality, both identifiable with several methodologies nowadays [1], organizations fail to find a solution to achieve high standards of productivity where continuous variables are the main component of productivity. For this type of hybrid organization, where productivity is linked with human cognitive work (agents), machines and objects (environmental aspects), traditional methodologies of productivity do not express the possibilities of controlling events from a probabilistic perspective, of which events in this type of organizations occur. This article considers productivity in modern and complex contexts of human labor interactions with non-physical environments [1] or, in other words, hybrid organizations where non-physical information is the main component of productivity
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