SiMLQ

SiMLQ - from Data to Action! SiMLQ automatically constructs data-driven process Simulators (digital twins) by leveraging event log data, Machine Learning and Queueing theory. The resulting simulation model allows process managers to optimize resource allocation, boost productivity, and reduce costs. SiMLQ unlocks the full potential of data by allowing for quick deployment of simulation models and testing of process-improving actions. SiMLQ focuses on congested systems, where queueing (waiting) occurs. Examples of such systems range from customers waiting to be served, to inventory waiting for processing or transportation, to payments and invoices waiting to be generated or cleared, to cloud computing tasks waiting for available resources. SiMLQ’s capability to quickly adapt to such diverse applications illustrates its scalability. SiMLQ’s unique ability to work with incomplete event data (symptomatic of most real-life event logs), quickly generate effective simulations, and evaluate impact of actions on key performance metrics makes it unparallel in the industry. We Turn Data into Actions.