Our business process modeling blog shares the ideas, examples, and advice enterprise teams need to understand how work really runs and where it can improve.
Object centric process mining tracks multiple related objects such as orders, items, and shipments instead of a single case. This guide explains how it works, how it compares with traditional process mining, its benefits and limitations, and the tools available.
A beginner’s guide to process mining: what it is, the three main types, how it works, the key components, and the tools behind it, with a simple example to make it concrete.
Feature engineering decides model quality, and process data supplies the temporal and sequential features most datasets never capture.
Process mining in healthcare rebuilds every patient pathway from the timestamps your systems already record, exposing the waiting between departments that conventional reporting cannot see.
Generative AI makes process analysis conversational, but only stays accurate when it is grounded in real process data.
A comprehensive look at how companies actually apply process mining, the data it needs, and where it delivers value first.
Process intelligence is what happens when discovery, modeling, monitoring and prediction stop being separate tools.
Licensing is rarely the whole cost of process mining. A breakdown of pricing models, implementation effort and the expenses that surprise people.
No code changes who can do process analysis and how fast. A practitioner view of what that looks like day to day.
mindzie adds Python to its low code platform so analyses can be extended beyond what a drag and drop interface covers.
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The mindzie team can show you how the ideas from our process improvement blogs translate into real-world results, bringing together process intelligence, BPMN modeling, and AI-ready operational insight in your business environment.
