SIMPT: Process Improvement Using Interactive Simulation of Time-aware Process Trees

TL;DR

SIMPT is an interactive, Python-based tool that combines process mining and simulation to enable process owners to explore future process scenarios and assess the impact of potential changes using historical event data.

Contribution

The paper introduces a novel interactive platform that automatically extracts process parameters from event logs and allows simulation of process modifications for improvement.

Findings

Enables automatic extraction of process parameters from event logs

Supports simulation of process changes to evaluate future scenarios

Provides an interactive web interface for process improvement

Abstract

Process mining techniques including process discovery, conformance checking, and process enhancement provide extensive knowledge about processes. Discovering running processes and deviations as well as detecting performance problems and bottlenecks are well-supported by process mining tools. However, all the provided techniques represent the past/current state of the process. The improvement in a process requires insights into the future states of the process w.r.t. the possible actions/changes. In this paper, we present a new tool that enables process owners to extract all the process aspects from their historical event data automatically, change these aspects, and re-run the process automatically using an interface. The combination of process mining and simulation techniques provides new evidence-driven ways to explore "what-if" questions. Therefore, assessing the effects of changes in process improvement is also possible. Our Python-based web-application provides a complete interactive platform to improve the flow of activities, i.e., process tree, along with possible changes in all the derived activity, resource, and process parameters. These parameters are derived directly from an event log without user-background knowledge.