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eDromos - a unique process intelligence solution
Synesa Solutions Oy
eDromos - a unique process intelligence solution
Synesa Solutions Oy
eDromos - a unique process intelligence solution
Synesa Solutions Oy
eDromos - a unique process optimization tool combining process mining, simulation&advanced analytics
High performing and efficient processes are the
key to success in highly competitive world. Synesa eDromos is a unique process
optimization tool that gives you the upper hand in business by combining
process mining, simulation and analytics into a streamlined work flow. Its
unique approach reduces time, costs and workload needed to detect and isolate
problems in your business process, and an unprecedented automation for building
simulation models that allow you to safely test and evaluate alternative
approaches and changes in your processes without interruptions to your daily
operations.
Project management
The project structure included in the solution
allows you to place data configurations and analysis models in logical,
interconnected entities.
Data sources and data configurations
Upload
data to eDromos® from different data sources and prepare data in a data
configuration view for the actual analysis. Combine different data sources as
you want
and
enrich the data with new columns if necessary.
Unique and versatile process analytics
Utilize
Synesa’s own process configurator to describe the process with step-by-step and
detailed configurations (tell the data what you want to discover). In
addition to configurating the process, you can also describe a process without precise attributes.
Process maps, animations and detailed statistics
As a result of mining, you have access to a visual, animated and interactive process graph, equipped with statistics about the process entity and its stages. The results of mining and analysis can also be exported to dashboard views for continuous operative monitoring.
Pre-post analysis
With before-after analytics, you can evaluate the effects of process changes. In the view definition, place a fixed point in the middle and the events to be viewed on both sides of the fixed point with their timeframes: this allows you to see changes in process behavior and to evaluate the effectiveness of various process changes.
Simulation and a digital twin
Simulation conversion allows you to automatically convert the fact-based process model and its basic parameters into a simulation format. With this conversion, the simulation model does not have to be built from scratch, which has traditionally been the starting point for creating simulation models.
Predictive analytics
Machine-learning, neural networks, AI
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