An X-Ray of your business processes
Together with AI experts at Copenhagen University, we have developed Gekkobrain FLOWS, a machine learning process mining tool, that will automatically mine and visualize all your business processes.
With FLOWS you will be able to understand your business process; your main flows and the diversions they inadvertently follow more often then not. Gekkobrain uses ML to automatically detect and understand your flows without any need to upload business blueprints or process templates. Gekkobrain gets it!
Features from Gekkobrain FLOWS:
- Visualization of all your business flows
- Choose date range freely
- Choose any starting point and any ending point freely
e.g. Procure-to-Pay or Order-to-Cash
- Compare good flows and bad flows
- Automatic detection of variations and reasons for bad flows
e.g. Why do we pay some invoices late?
- Multidimensional analysis across business process
- Integrated to Gekobrain DevOps for SAP
Gekkobrain FLOWS in Action
- Save time to understand and visualize your flows
- Identify bottlenecks
- Identity candidates for RPA
- Optimize processes (e.g. increase percentage of Perfect POs)
- Map process to logical solution components (for S/4HANA)
- Map custom code to process and logical solution components (for S/4HANA)
- Save money on problematic flows
Choose and any date range, starting point and ending point and see your business process flow. Label or classify your flows or save as scenarios.
Heatmaps for multidimensional analysis
Using classifications and scenarios, which can be entered manually or suggested by the machine learning algorithm, Gekkobrain FLOWS allows you to investigate root causes by using the FLOWS heatmaps, which correlate all dimensions on all documents in all selected processes to look for reasons for problems. E.g. to answer this question: “What’s the main reasons for paying certain (or many) invoices too late?
Want to learn more or request a demo of Gekkobrain FLOWS? Contact us using the form below and we will be in touch within 24 hours.