Jonas Poelmans et al. talk at IEEE EEML 2013 (ICDM 2013)
Channel: trickLUster
Date: 2013-12-07

Process improvement programs rely heavily on
various techniques for the identification of deficiencies in the
processes and for the explanation of their root causes, in order to
formulate adequate remediating actions. Six-sigma and Lean
Management approaches are useful statistical techniques in this
context. In the practical application of such techniques, the
process analyst is often restricted by the semantic expressiveness
of the process analysis models. Many popular process modeling
techniques also suffer from limitations in the adequate
representation of probabilistic behavior in processes. The latter is
important, for example, for detecting the impact of exceptions
and variations in processes.
In this talk additional techniques are shown based on
Formal Concept Analysis (FCA). This is primarily based on the
semantic richness of FCA-schema's, which are partial ordering
lattices. It is shown how many-to-many transitions in processes
can easily be identified in an FCA-based Process representation.
These transitions are not only the expression of potential Value
Leaks as they also lead to explanations of their root causes. The
techniques described in this talk are not a replacement, but
rather an augmentation for Six-sigma and Lean Management
approaches.
In the talk several examples that are known in the Process
Mining literature are presented and discussed. The techniques
that are proposed are scalable and extend easily to large scale
examples.