Organisations have a vast amount of data stored in their systems. This data plays a crucial role in operation development. However, collecting the most relevant pieces of information from a huge dataset is challenging and time-consuming. eDromos is a process mining tool developed by Synesa Solutions, which allows processing of data into a visual and fact-based analysis of the current operations. The analysis of the current operations constructed by eDromos helps organizations identify the problematic areas in their operations and recognize the kind of changes that are needed to solve those problems. The software is easy to use and applicable in many different industries (e.g. examining the service paths and care episodes in the social and healthcare domain).

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eDromos can:
  • Mine big and complex process data sets based on a detailed process definition created by the user
  • Create interactive and exportable process graph visualizations with relevant statistics and color coded arcs displaying the frequencies of transitions between different activities
  • Display statistics windows containing activity and transition time durations, attribute frequencies,  distribution histograms, boxplots and more for each element of the graph
  • Extract only the relevant parts of the source data and export it for further use in other analytics and simulation softwares

eDromos helps you understand

  • what the current state of the operations is
  • how the current operations diverge from the planned operations
  • how operations could be developed

Synesa Solutions eDromosToSim conversion tool converts your process model into a simulation model. With a simulatio model you can experiment and evaluate how changes in your process affect its performance. Read more about eDromosToSim here

Using eDromos has multi-dimensional benefits

The visual and fact-based analysis of the current operations brings many benefits to the organisation, the staff and the patients.

Better understanding of the state of the current operations

Removal of overlapping work tasks

Increased quality and efficiency of patient treatment

Better organisation and resourcing of treatment

Reduction of work stress

Reduced expenses

The functions of eDromos
1. Presents the current state of operations in an organisation
2. Identifies the areas of development
  • eDromos constructs a visual and fact-based analysis of the current operations from the data stored in the system.
  • Instead of various graphs and statistics eDromos presents the current operations in a visual and chronological form that shows the relations between the different phases of the operations.
  • In the analysis created By eDromos we can identify the problematic areas such as the most common factors that slow down the treatment process.
  • The identification of the problems is essential when we want to plan and test development ideas.
eDromos allows us to view the current operations from different perspectives

The typical treatment processes of different patient groups

The problematic areas in treatment paths

Possible weaknesses in information systems

The point of view of the patient

The point of view of the health care staff

What makes eDromos unique?
It is realistic
  • The analysis of the current operations is based on the data stored in the organisation’s system, which makes it fact-based.
  • When operation development is based on facts and operations that are unique with each organisation, the suggested solutions are realistic and fit the needs of the organisation.
It is visual
  • Instead of separate graphs and tables eDromos constructs a visual and chronological model of the current operations.
  • When the operations are presented in a chronological form, it is easy to see the relations between different phases of the treatment process.
It is efficient
  • eDromos constructs the analysis of the current operations efficiently from the data in the system. This removes the need to collect data manually.
It is objective
  • With automated processing of data the analysis process is more efficient and there is no danger of mistakes and subjectivity that can occur with manual data collection. The result is a thorough analysis of the current operations that is based on facts instead of subjective assumptions.