Analysis of Probabilistic Distributions and Uncertainty of Information Flow at Administrative Workflows

Common methods found in the market such as LEAN, AGILE, SCRUM are short and insufficient to generate a
high level of efficiency in discrete-continuous variables based workflows and aspects of classification,
decidability and analysis remains mostly copies of successful cases. The new metric and theoretical framework
proposed in this article allows qualitative classification and analysis of workflows in close proximity to
qualitative theory of differential equations (QDE), raising the possibility of fulfill the gaps existent in the
commercial and popular methods. These metrics are also the result of research carried out in the view of the
difficulty of characterizing the solidity aspect of workflows and enabling continuous improvements as a
complex adaptive system (CAS).